WO2025182923A1 - Ophthalmic device, control method therefor, program, and recording medium - Google Patents

Abstract

A scan unit of an ophthalmic device according to an embodiment collects data by applying an OCT scan by a scan pattern without flyback to a fundus. A cross-sectional image generation unit generates a plurality of cross-sectional images respectively corresponding to a plurality of cross-sections of the fundus on the basis of the collected data. A blood vessel region identification unit identifies a plurality of blood vessel region groups respectively corresponding to the plurality of cross-sectional images, by detecting the blood vessel region groups from each of the generated cross-sectional images. A blood vessel region association unit performs association, among the plurality of blood vessel region groups identified from the plurality of cross-sectional images, between blood vessel regions that correspond to different cross-sections of the same blood vessel. A blood vessel map generation unit generates a blood vessel map on the basis of the result of the association of the blood vessel regions.

Description

Ophthalmic apparatus, its control method, program, and recording medium

(CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Provisional Patent Application No. 63/557,720, entitled "OPHTHALMIC OTICAL COHERENCE TOMOGRAPHY," filed February 26, 2024, the entire contents of which are incorporated herein by reference.

This disclosure relates to an ophthalmic device, a control method therefor, a program, and a recording medium.

Various types of imaging modalities are used in ophthalmology. Representative examples include fundus cameras, scanning laser ophthalmoscopy (SLO), slit lamp microscopes, and optical coherence tomography (OCT). OCT can be used for both structural and functional imaging.

Structural imaging using OCT is a technique that represents the spatial distribution of OCT signal intensity, which changes depending on the structure of the test object, as an image. Images generated using this technique are called OCT intensity images or simply intensity images.

One method of functional imaging using OCT is OCT blood flow measurement. OCT blood flow measurement is a Doppler measurement that uses OCT to determine blood flow dynamics, and is also called Doppler OCT. OCT blood flow measurement is a technique that repeatedly scans the cross section of a blood vessel with OCT measurement light to collect a data set, and determines the Doppler signal due to blood flow from the difference in this data set, as well as the angle (Doppler angle) between the blood vessel and the OCT measurement light, thereby determining the magnitude of retinal blood flow velocity. Furthermore, the blood flow volume can be calculated by multiplying the obtained blood flow velocity by the cross-sectional area of the blood vessel. In the field of ophthalmology, OCT blood flow measurement is typically applied to blood vessels in the fundus, and particularly retinal blood vessels. However, there have also been reports of OCT blood flow measurement of choroidal blood vessels.

U.S. Pat. No. 1,198,0419 U.S. Patent No. 8,175,685 U.S. Pat. No. 1,194,4382

The purpose of this disclosure is to improve fundus hemodynamic measurement using Doppler OCT.

In some embodiments, an ophthalmologic apparatus includes a scanning unit, a cross-sectional image generating unit, a vascular region identifying unit, a vascular region matching unit, and a vascular map generating unit. The scanning unit is configured to collect data by applying an optical coherence tomography scan using a scan pattern without flyback to the fundus of the subject's eye. The cross-sectional image generating unit is configured to generate multiple cross-sectional images corresponding to multiple cross sections of the fundus based on the data collected by the scanning unit. The vascular region identifying unit is configured to identify multiple vascular region groups corresponding to the multiple cross-sectional images by detecting vascular region groups from each of the multiple cross-sectional images generated. The vascular region matching unit is configured to match vascular regions corresponding to different cross sections of the same blood vessel among the multiple vascular region groups identified from the multiple cross-sectional images. The vascular map generating unit is configured to generate a vascular map indicating the distribution of blood vessels based on the results of the vascular region matching.

According to some embodiments, it is possible to improve fundus hemodynamic measurements using Doppler OCT.

FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. 10 is a flowchart illustrating the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 2 is a schematic diagram for explaining the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. 10 is a flowchart illustrating the operation of an ophthalmologic apparatus according to a non-limiting embodiment. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. 10 is a flowchart illustrating the operation of an ophthalmologic apparatus according to a non-limiting embodiment. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. 10 is a flowchart illustrating the operation of an ophthalmologic apparatus according to a non-limiting embodiment. FIG. 1 is a schematic diagram illustrating a configuration of an ophthalmologic apparatus according to a non-limiting embodiment. 10 is a flowchart illustrating the operation of an ophthalmologic apparatus according to a non-limiting embodiment.

Several non-limiting embodiments of the present disclosure will be described. This disclosure describes embodiments of ophthalmic devices (e.g., ophthalmic blood flow measuring devices, ophthalmic imaging devices, etc.), embodiments of methods for controlling ophthalmic devices, embodiments of programs, and embodiments of recording media. However, the categories of embodiments of the present disclosure are not limited to these.

Embodiments of the present disclosure can be employed to solve problems that arise when measuring fundus hemodynamics using Doppler OCT. There are a variety of problems that arise when measuring fundus hemodynamics using Doppler OCT.

Some embodiments of the present disclosure are intended to improve the quality of processes and tasks related to fundus hemodynamic measurements. Examples of processes and tasks of interest include, but are not limited to, alignment of the device optical system with the fundus, estimation of Doppler angles, and search for blood vessels to which measurements are to be applied.

Conventionally, alignment has been performed by referencing infrared observation images (real-time moving images) of the fundus. Some embodiments provide a novel alignment method that utilizes the positions of fundus blood vessels obtained from OCT images.

Furthermore, in the past, users would refer to an infrared observation image of the fundus or a previously acquired fundus photograph to determine the blood vessels and cross sections to which blood flow measurement should be applied. Some embodiments provide a novel method for generating orientation information (Doppler angle, its suitability, etc.) of fundus blood vessels. Furthermore, some embodiments use the generated orientation information to facilitate and reduce the effort required to specify blood flow measurement positions (blood vessels to be measured, cross sections to be measured, etc.). Furthermore, some embodiments improve the precision and accuracy of specifying blood flow measurement positions. Furthermore, some embodiments make it possible to predict blood flow measurement positions to a certain extent. This makes it possible to limit the measurement application area and analysis application area before actually applying fundus hemodynamic measurement, further facilitating and reducing the effort required to specify blood flow measurement positions.

Some embodiments of the present disclosure also address the following problem: The phase signal obtained by fundus hemodynamic measurement has a good contrast mechanism. However, when measurement is performed during the diastolic phase, when pulsation is relatively weak, the detected signal strength is low, which can result in poor measurement quality. When measurement is performed on veins, which have a weaker pulsation than arteries, or when measurement is performed at an unsuitable Doppler angle, the detected signal strength can also be reduced, resulting in poor measurement quality. Furthermore, fundus blood vessels run and are distributed in a complex three-dimensional manner. The actual blood vessel course can be determined by performing fundus imaging. Conventionally, this information has not been utilized. Some embodiments address this problem by generating a map of blood vessels suitable for fundus hemodynamic measurement.

It should be clear to those skilled in the art that the problems that can be addressed using the technology disclosed herein are not limited to the examples given above.

<Embodiment of Ophthalmic Apparatus>
Some non-limiting aspects of the ophthalmic apparatus according to the embodiment will be described below. The ophthalmic apparatus according to the embodiment has a function of performing OCT blood flow measurement and a function of processing data obtained by the OCT blood flow measurement.

The ophthalmic device of the aspect primarily described in this disclosure functions as an OCT device capable of performing OCT blood flow measurement (OCT scanning and image generation processing). Some other aspects of the ophthalmic device may not be capable of performing at least some of the processing involved in OCT blood flow measurement.

The OCT method may be any method, for example, spectral domain OCT or swept-source OCT. Spectral domain OCT is a method in which light from a low-coherence light source is split into measurement light and reference light, and return light from the test object is superimposed on the reference light to generate interference light. The spectral distribution of this interference light is detected with a spectrometer, and the detected spectral distribution is subjected to processing such as Fourier transform to construct an image. Swept-source OCT is a method in which light from a tunable light source is split into measurement light and reference light, and return light from the test object is superimposed on the reference light to generate interference light. The interference light is detected with a photodetector (such as a balanced photodiode), and the detection data collected in response to wavelength sweeping and measurement light scanning is subjected to processing such as Fourier transform to construct an image. In other words, spectral domain OCT is an OCT method that acquires spectral distributions using spatial division, while swept-source OCT is an OCT method that acquires spectral distributions using time division. Other OCT methods, such as time domain OCT, may also be used.

The ophthalmic device of the embodiment primarily described in this disclosure functions as a fundus camera capable of photographing the fundus. Other embodiments of the ophthalmic device may function as any ophthalmic imaging modality, such as an SLO, a slit lamp microscope, or a surgical microscope, in addition to or instead of functioning as a fundus camera.

In this disclosure, unless otherwise specified, no distinction is made between "image data" and the "image" that is the visual information based on it. Furthermore, unless otherwise specified, no distinction is made between the part or tissue of the subject's eye and its image (image data).

In some exemplary embodiments, the ophthalmologic apparatus does not need to have a fundus imaging function. Such an ophthalmologic apparatus has the function of acquiring a front image of the fundus from a storage device or recording medium. A typical example of a storage device is a medical image archiving system (medical image filing system). Also, typical examples of recording media are a hard disk drive or an optical disk.

At least a portion of the functionality of the elements of the embodiments of the present disclosure is implemented using circuitry or processing circuitry. The circuitry or processing circuitry may include any of a general purpose processor, a special purpose processor, an integrated circuit, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Application Specific Integrated Circuit (ASIC), a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), a Field Programmable Gate Array (FPGA)), conventional circuitry, and any combination thereof, configured and/or programmed to perform at least some of the disclosed functions. In this disclosure, a circuit configuration, unit, means, or similar term refers to hardware that performs at least some of the disclosed functions or that is programmed to perform at least some of the disclosed functions. The hardware may be hardware disclosed herein or known hardware that is programmed and/or configured to perform at least some of the described functions. If the hardware is a processor, which can be considered a type of circuit configuration, the circuit configuration, unit, means, or similar term refers to a combination of hardware and software, and the software is used to configure the hardware and/or processor.

The configuration of an exemplary ophthalmic device is shown in Figures 1 to 4. The ophthalmic device 1 in this example includes a fundus camera unit 2, an OCT unit 100, and an arithmetic and control unit 200. The fundus camera unit 2 is equipped with elements of a fundus camera capable of photographing the fundus and the anterior segment, and elements of an OCT scanner. The OCT unit 100 is equipped with elements of an OCT scanner. The arithmetic and control unit 200 includes one or more processors configured to perform various processes (calculation, analysis, control, etc.).

The fundus camera unit 2 will now be described. The fundus camera unit 2 includes an optical system for photographing the fundus Ef (and the anterior segment) of the subject's eye E. The digital image acquired by the fundus camera unit 2 is typically a front image. The fundus camera unit 2 can, for example, acquire observation images by video capture using near-infrared fixed light as illumination light, and can acquire photographed images by capture using visible flash light as illumination light.

The fundus camera unit 2 comprises an illumination optical system 10 and an imaging optical system 30. The illumination optical system 10 irradiates illumination light onto the subject's eye E. The imaging optical system 30 detects the return light of the illumination light irradiated onto the subject's eye E. In other words, the imaging optical system 30 photographs the subject's eye E illuminated by the illumination light. The OCT measurement light provided by the OCT unit 100 is guided to the subject's eye E via an optical path within the fundus camera unit 2. The return light of the OCT measurement light applied to the subject's eye E is guided to the OCT unit 100 via an optical path within the fundus camera unit 2.

The observation illumination light output from the observation light source 11 of the illumination optical system 10 is reflected by the concave mirror 12, passes through the condenser lens 13, and passes through the visible cut filter 14 to become near-infrared light.It is then focused near the imaging light source 15, reflected by the mirror 16, and passed through the relay lens system 17, relay lens 18, aperture 19, and relay lens system 20 to be guided to the perforated mirror 21, reflected by the mirror portion surrounding the central hole of the perforated mirror 21, passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the subject's eye E (fundus Ef). The return light of the observation illumination light projected onto the subject's eye E is refracted by the objective lens 22, passes through the dichroic mirror 46, passes through the central hole in the perforated mirror 21, passes through the dichroic mirror 55, passes through the photographing focusing lens 31, is reflected by the mirror 32, passes through the half mirror 33A, is reflected by the dichroic mirror 33, and is imaged on the light-receiving surface of the image sensor 35 by the imaging lens 34. The image sensor 35 detects the return light at regular time intervals (frame rate). The focus of the photographing optical system 30 is adjusted according to the photographing area.

The imaging illumination light output from the imaging light source 15 travels the same path as the observation illumination light and is projected onto the fundus Ef. The return light of the imaging illumination light from the subject's eye E travels the same path as the return light of the observation illumination light and is guided to the dichroic mirror 33, passes through the dichroic mirror 33, is reflected by the mirror 36, and is imaged by the imaging lens 37 on the light-receiving surface of the image sensor 38.

The liquid crystal display (LCD) 39 displays a fixation target (fixation target image) for guiding and fixing the gaze. The light beam output from the LCD display 39 is reflected by the half mirror 33A, reflected by the mirror 32, passes through the photographic focusing lens 31 and dichroic mirror 55, passes through the central hole in the perforated mirror 21, passes through the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the fundus Ef. This allows the subject to visually recognize the fixation target.

The alignment optical system 50 generates an alignment index for aligning the ophthalmic apparatus 1 with the subject's eye E. The alignment light output from the light-emitting diode (LED) 51 passes through the diaphragm 52, the diaphragm 53, and the relay lens 54, is reflected by the dichroic mirror 55, passes through the central hole in the perforated mirror 21, transmits through the dichroic mirror 46, and is projected onto the subject's eye E via the objective lens 22. The return light of the alignment light from the subject's eye E is guided to the image sensor 35 along the same path as the return light of the observation illumination light. Manual alignment and automatic alignment can be performed by referring to the received light image (alignment index image).

The focusing optical system 60 generates a split index used to adjust the focus of the subject's eye E. The focusing optical system 60 moves along the optical path (illumination optical path) of the illumination optical system 10 in conjunction with the movement of the photographing focusing lens 31 along the optical path (photographing optical path) of the photographing optical system 30. The reflecting rod 67 is inserted and removed from the illumination optical path. When adjusting the focus, the reflective surface of the reflecting rod 67 is positioned at an angle to the illumination optical path. The focusing light output from the LED 61 passes through the relay lens 62, is separated into two beams of light by the split index plate 63, passes through the two-hole diaphragm 64, is reflected by the mirror 65, is first imaged and reflected by the condenser lens 66 on the reflective surface of the reflecting rod 67, passes through the relay lens 20, is reflected by the perforated mirror 21, passes through the dichroic mirror 46, and is projected onto the subject's eye E via the objective lens 22. The return light of the focusing light from the subject's eye E is guided to the image sensor 35 along the same path as the return light of the alignment light. Manual focusing and autofocusing can be performed by referring to the received light image (split target image).

If the subject's eye E is highly hyperopic, a diopter correction lens 70 (plus lens) is placed in the imaging optical path between the perforated mirror 21 and the dichroic mirror 55. On the other hand, if the subject's eye E is highly myopic, a diopter correction lens 71 (minus lens) is placed.

The dichroic mirror 46 combines the optical path for imaging by the fundus camera unit 2 with the optical path for OCT (measurement arm). The dichroic mirror 46 reflects light in the wavelength band for OCT and transmits light in the wavelength band for imaging by the fundus camera unit 2. The measurement arm is equipped with, in order from the OCT unit 100 side, a collimator lens unit 40, a retroreflector 41, a dispersion compensation element 42, an OCT focusing lens 43, an optical scanner 44, and a relay lens 45. The retroreflector 41 is movable along the optical path of the OCT measurement light incident on it and is used to correct the optical path length according to the axial length and adjust the interference state. The dispersion compensation element 42 is used for dispersion compensation between the measurement arm and the reference arm. The OCT focusing lens 43 is movable along the measurement arm and is used to adjust the focus of the measurement arm. Focus adjustment of the ophthalmologic apparatus 1 is performed by coordinating the movement of the imaging focusing lens 31, the movement of the focusing optical system 60, and the movement of the OCT focusing lens 43. The optical scanner 44 is positioned at a position substantially conjugate with the pupil of the subject's eye E through alignment, and changes the direction of travel of the OCT measurement light. The optical scanner 44 is, for example, a galvano scanner capable of two-dimensional scanning.

The OCT unit 100 will now be described. The OCT unit 100 shown in Figure 2 is equipped with a spectral domain OCT optical system. This OCT optical system includes an interference optical system. This interference optical system splits light from a low-coherence light source (broadband light source) into measurement light LS (OCT measurement light) and reference light LR, and generates interference light LC by superimposing the return light of the measurement light LS projected onto the subject's eye E on the reference light LR. The generated interference light LC is detected by the spectroscope 130. This provides a signal indicating the spectral distribution of the interference light LC. This detection signal is sent to the arithmetic and control unit 200.

The light source unit 101 outputs broadband low-coherence light L0. The light source unit 101 includes an optical output device such as a superluminescent diode (SLD), LED, or semiconductor optical amplifier (SOA). The low-coherence light L0 output from the light source unit 101 is guided by optical fiber 102 to polarization controller 103, where its polarization state is adjusted, and then guided by optical fiber 104 to fiber coupler 105, where it is split into measurement light LS and reference light LR. The measurement light LS is guided by the measurement arm, and the reference light LR is guided by the reference arm.

The reference light LR is guided by optical fiber 110 to collimator 111, where it is converted into a parallel beam. It then passes through optical path length compensation element 112, which compensates for the optical distance between the measurement arm and reference arm, and dispersion compensation element 113, which compensates for dispersion between the measurement arm and reference arm, before being guided to retroreflector 114. Retroreflector 114 is movable along the optical path of the reference light LR incident thereon, and is used to correct the optical path length according to the axial length and adjust the interference state. After passing through retroreflector 114, the reference light LR passes through dispersion compensation element 113 and optical path length compensation element 112, and is converted from a parallel beam into a focused beam by collimator 116. It is then guided via optical fiber 117 to polarization controller 118, where its polarization state is adjusted, and then through optical fiber 119 to attenuator 120, where its light intensity is adjusted. It then reaches fiber coupler 122 via optical fiber 121.

Meanwhile, the measurement light LS is guided through the optical fiber 127 to the collimator lens unit 40, where it is converted into a parallel beam of light, passes through the retroreflector 41, dispersion compensation member 42, OCT focusing lens 43, optical scanner 44, and relay lens 45, is reflected by the dichroic mirror 46, is refracted by the objective lens 22, and is projected onto the subject's eye E. The measurement light LS is scattered and reflected at various depth positions in the subject's eye E. The return light of the measurement light LS from the subject's eye E travels backward through the measurement arm, is guided to the fiber coupler 105, and reaches the fiber coupler 122 via the optical fiber 128.

Fiber coupler 122 generates interference light LC by superimposing measurement light LS incident via optical fiber 128 and reference light LR incident via optical fiber 121. The generated interference light LC is guided to spectrometer 130 via optical fiber 129. In a non-limiting example, spectrometer 130 converts the incident interference light LC into a parallel beam using a collimator lens, resolves the parallel beam of interference light LC into multiple spectral components using a diffraction grating, and projects the multiple spectral components generated by the diffraction grating onto an image sensor via a lens. This image sensor is, for example, a line sensor, and detects the multiple spectral components of the interference light LC to generate an electrical signal (detection signal). The generated detection signal contains information on the spectral distribution of the interference light LC and is sent to the arithmetic and control unit 200.

The OCT unit 100 in Figure 2 described above employs the spectral domain OCT method. When the swept-source OCT method is used, the light source unit 101 includes a tunable light source (e.g., a near-infrared tunable laser) that rapidly changes the wavelength of the emitted light. Furthermore, in the optical system of the swept-source OCT method, the interference light LC generated by superimposing the measurement light LS and the reference light LR is split at a predetermined splitting ratio (e.g., 1:1) to generate a pair of interference light beams, which are then detected by a photodetector. This photodetector includes a balanced photodiode. The balanced photodiode includes a pair of photodetectors that respectively detect the pair of interference light beams, and outputs the difference between the pair of detection signals obtained by the pair of photodetectors. The photodetector sends this difference signal to a data acquisition system (DAQ). A clock is supplied to the data acquisition system from the light source unit 101. This clock is generated in the light source unit 101 in synchronization with the output timing of each wavelength swept within a predetermined wavelength range by the tunable light source. For example, the light source unit 101 splits light of each output wavelength to generate two split lights, optically delays one of the split lights, then combines the two split lights, detects the resulting combined light, and generates a clock based on the detection signal. The data collection system uses the clock provided by the light source unit 101 to sample the detection signal (differential signal) input from the photodetector. The data obtained by this sampling is provided for processing such as image generation.

In the example shown in Figures 1 and 2, optical path length changing elements (retroreflectors 41 and 114) are provided in both the measurement arm and the reference arm, but only one of them may be provided. Furthermore, the optical path length changing elements are not limited to retroreflectors. For example, the optical path length changing element of the reference arm may be a movable reflecting member (reference mirror). More generally, the ophthalmic device according to the present disclosure includes an element configured to relatively change the measurement arm length and the reference arm length (i.e., an element configured to change the optical path length difference between the measurement arm and the reference arm), and this element can be used to move the coherence gate position.

The arithmetic and control unit 200 will now be described. The arithmetic and control unit 200 performs various processes, such as controlling each part of the ophthalmic apparatus 1, various calculations, and various analyses. For example, the arithmetic and control unit 200 calculates the reflection intensity profile of a line (A-line) extending in the depth direction (z-direction) at each projection position of the measurement light LS by performing signal processing such as Fourier transform on the spectral distribution (interference signal, interferogram) acquired by the spectroscope 130. Furthermore, the arithmetic and control unit 200 generates image data by imaging the reflection intensity profile of each A-line. The arithmetic and control unit 200 may perform the same calculations as in image generation using conventional spectral domain OCT. The arithmetic and control unit 200 includes, for example, a processor, RAM, ROM, a hard disk drive, a communication interface, etc. Various computer programs are stored in storage devices such as hard disk drives. The arithmetic and control unit 200 may also include an operation device, an input device, a display device, etc.

The user interface 240 shown in Figure 3 will now be described. The user interface 240 has a display unit 241 and an operation unit 242. The display unit 241 includes, for example, the display device 3 of Figure 1. The operation unit 242 includes various operation devices and input devices. The user interface 240 may include a touch panel. In some exemplary embodiments, at least a portion of the user interface is provided as a peripheral device connected to the ophthalmologic apparatus 1.

The moving mechanism 150 shown in Figure 3 will now be described. The moving mechanism 150 is configured to move the optical system of the ophthalmologic apparatus 1. The moving mechanism 150, for example, moves at least the fundus camera unit 2 three-dimensionally.

The data input/output unit 290 shown in Figure 3 will be described. The data input/output unit 290 inputs data to the ophthalmic device 1 and outputs data from the ophthalmic device 1. A non-limiting embodiment of the data input/output unit 290 has a function for communicating with an external device (not shown), for example. The communication unit 290 has a communication interface according to the connection form with the external device. The external device may be, for example, any ophthalmic device. The external device may also be any information processing device, such as a Hospital Information System (HIS) server, a DICOM (Digital Imaging and Communication in Medicine) server, a doctor's terminal, a mobile terminal, a personal terminal, or a cloud server. Some exemplary embodiments of the data input/output unit 290 include a device that reads information from a recording medium (data reader) and a device that writes information to a recording medium (data writer). The embodiments of the data input/output unit 290 are not limited to these.

The processing system (arithmetic and control system) of the ophthalmic apparatus 1 will now be described. An example configuration of the processing system is shown in Figures 3 and 4. The control unit 210 and data processing unit 230 are provided in the arithmetic and control unit 200.

The control unit 210 includes a processor and controls each component of the ophthalmic apparatus 1. The control unit 210 includes a main control unit 211 and a memory unit 212. The main control unit 211 includes a processor and is configured to control each component of the ophthalmic apparatus 1 (including the components shown in Figures 1 to 3). The main control unit 211 may also be configured to control apparatuses, devices, and systems connected to the ophthalmic apparatus 1. The functions of the main control unit 211 are realized, for example, by cooperation between hardware including circuits and control software. The memory unit 212 stores various types of data. The memory unit 212 includes storage devices such as hard disk drives and solid state drives.

The following describes several controls performed by the main controller 211. The main controller 211 controls the imaging focusing driver (not shown) to synchronously move the imaging focusing lens 31 and the focus optical system 60. The main controller 211 controls the retroreflector (RR) driver 41A to move the retroreflector 41 of the measurement arm. The main controller 211 controls the OCT focusing driver 43A to move the OCT focusing lens 43 of the measurement arm. The main controller 211 controls the optical scanner 44 to deflect the measurement light LS according to a preset scan pattern. The main controller 211 controls the retroreflector (RR) driver 114A to move the retroreflector 114 of the reference arm. The main controller 211 controls the movement mechanism 150 to move the optical system (e.g., the fundus camera unit 2 and OCT unit 100).

The data processing unit 230 performs various types of data processing. For example, the data processing unit 230 applies various types of processing to images (fundus images, anterior segment images, etc.) acquired by the fundus camera unit 2. The data processing unit 230 also applies various types of processing to images acquired using OCT scanning (OCT images). The data processing unit 230 includes a processor. The data processing unit 230 is realized, for example, by the cooperation of hardware including circuits and data processing software.

The data processing unit 230 includes an image generation unit 220. The image generation unit 220 processes data collected by applying an OCT scan to the fundus Ef of the subject's eye E to generate OCT image data. The image generation unit 220 includes a processor. The functions of the image generation unit 220 are realized, for example, by cooperation between hardware including circuits and image generation software.

The image generation unit 220 is configured to perform a process of generating an OCT intensity image that represents the intensity of the interference signal as visual information, and a process of generating a phase image that represents the phase information of the interference signal as visual information. Next, a non-limiting example of the process of generating an intensity image will be described. A non-limiting example of the process of generating a phase image will be described later, along with an explanation of the theoretical aspects of OCT blood flow measurement.

The image generation unit 220 generates an intensity image based on the data (interference signal) acquired by the spectrometer 130. Similar to conventional spectral-domain OCT, this intensity image generation process includes signal processing such as A/D conversion, denoising, filtering, and fast Fourier transform (FFT). The fast Fourier transform converts the interference signal acquired by the spectrometer 130 into an A-line profile (a reflection intensity profile along the z direction). The A-line profile is visualized by applying imaging processing (a process that assigns pixel values to reflection intensity values) to the A-line profile. This results in A-scan image data. By arranging multiple A-scan images according to a scan pattern, a cross-sectional image (e.g., B-scan image data, circle scan image data, etc.) corresponding to that scan pattern is constructed. If another OCT method is used, the cross-sectional image generation unit 221 performs known processing appropriate for that type.

In some embodiments, the intensity image may be a dataset including a group of A-scan image data obtained by visualizing the reflection intensity profile of multiple A-lines arranged in the area where the OCT scan was applied. In other words, in some embodiments, the intensity image may be a dataset including a group of A-scan image data and their position information (coordinates). In another embodiment, the intensity image may be stack data constructed by embedding multiple B-scan images in a single three-dimensional coordinate system, that is, a dataset including multiple B-scan images and their position information. In yet another embodiment, the intensity image may be volume data (voxel data) generated by applying a voxelization process to the stack data. Stack data and volume data are non-limiting examples of three-dimensional image data in which pixel coordinates are defined using a three-dimensional coordinate system. The process of generating the three-dimensional image data is performed by the image generation unit 220.

The image generation unit 220 can process three-dimensional image data. For example, the image generation unit 220 can generate new image data by applying rendering to the three-dimensional image data. Rendering techniques include volume rendering, surface rendering, multi-planar reconstruction (MPR), maximum intensity projection (MIP), minimum intensity projection (MinIP), and average intensity projection (AIP). The image generation unit 220 can construct projection data by integrating (projecting) the three-dimensional image data in the z direction. The image generation unit 220 can construct a shadowgram by integrating (projecting) a portion of the three-dimensional image data (three-dimensional partial image data) in the z direction. The three-dimensional partial image data is extracted from the three-dimensional image data using any image segmentation method.

The ophthalmic device 1 can apply OCT blood flow measurement to the fundus Ef. Below, we will explain the theoretical aspects of OCT blood flow measurement, as well as some non-limiting aspects of OCT blood flow measurement.

A non-limiting embodiment of blood flow measurement applies two types of scans (main scan and supplementary scan) to the fundus Ef. The main scan repeatedly scans a region of interest (cross section of interest) that intersects the blood vessel of interest in the fundus Ef at a position of interest with the measurement light LS to obtain phase image data. Meanwhile, the supplementary scan scans a predetermined cross section (supplementary cross section) with the measurement light LS to estimate the inclination of the blood vessel of interest in the cross section of interest. In a non-limiting embodiment, the supplementary cross section may be, for example, a cross section (first supplementary cross section) that intersects the blood vessel of interest and is located near the cross section of interest. In another non-limiting embodiment, the supplementary cross section may be a cross section (second supplementary cross section) that intersects the cross section of interest and is aligned with the blood vessel of interest. The inclination of the blood vessel of interest is the angle between the measurement light LS projected onto the cross section of interest and the blood vessel of interest, which is the Doppler angle in Doppler OCT.

An example of when the first supplemental cross section is applied is shown in Figure 5A. In this example, as shown in fundus image D, one cross section of interest C0 located near the optic disc Da of the fundus Ef, and two supplemental cross sections C1 and C2 located nearby are set to intersect with the blood vessel of interest Db. One of the two supplemental cross sections C1 and C2 is located upstream of the blood vessel of interest Db relative to the cross section of interest C0, and the other is located downstream. The cross section of interest C0 and the supplemental cross sections C1 and C2 are oriented, for example, approximately perpendicular to the running direction of the blood vessel of interest Db.

Figure 5B shows an example of when the second supplementary cross section is applied. In this example, a cross section of interest C0 similar to the example shown in Figure 5A is set so as to be approximately perpendicular to the blood vessel of interest Db, and a supplementary cross section Cp is set so as to be approximately perpendicular to the cross section of interest C0. The supplementary cross section Cp is set along the blood vessel of interest Db. As an example, the supplementary cross section Cp may be set so as to pass through the central axis of the blood vessel of interest Db at the position of the cross section of interest C0.

It is desirable for the main scan in OCT blood flow measurement to collect data over a period that includes at least one cardiac cycle of the subject's heart. This makes it possible to determine blood flow dynamics in all cardiac phases. The time for performing the main scan may be a fixed, predetermined time, or a time set for each subject or test. This fixed time has traditionally been set to a time (e.g., 2 seconds) that is sufficiently longer than a standard cardiac cycle. Furthermore, the time set for each subject or test has traditionally been determined by referring to data from a biosignal detector such as an electrocardiograph.

The image generation unit 220 includes a cross-sectional image generation unit 221 and a phase image generation unit 222. The cross-sectional image generation unit 221 includes a processor, and its functions are realized, for example, by cooperation between hardware including circuits and cross-sectional image generation software. The phase image generation unit 222 includes a processor, and its functions are realized, for example, by cooperation between hardware including circuits and phase image generation software.

The cross-sectional image generation unit 221 generates an intensity image based on data collected by OCT scanning of the fundus oculi Ef. The intensity image generation process may be similar to conventional image generation methods used in spectral domain OCT.

The cross-sectional image generation unit 221 generates cross-sectional images (main cross-sectional images) representing time-series changes in the morphology of the cross-section of interest based on interference signals obtained by the spectroscope 130 during main scanning of the cross-section of interest of the fundus oculi Ef. As described above, during main scanning, the ophthalmic device 1 applies repeated scans to the cross-section of interest C0. This repeated scan includes multiple B-scans for the cross-section of interest C0. The interference signals generated sequentially by the spectroscope 130 in the multiple B-scans are input sequentially to the cross-sectional image generation unit 221. The cross-sectional image generation unit 221 generates one main cross-sectional image corresponding to the cross-section of interest C0 based on the interference signals corresponding to each B-scan. The cross-sectional image generation unit 221 repeats this process the number of times the B-scan is repeated in the main scanning, thereby generating a series of main cross-sectional images in chronological order. In this way, the cross-sectional image generation unit 221 generates multiple intensity images corresponding to multiple B-scans based on the data set collected by repeated scanning of the main scanning. In some exemplary embodiments, the image quality of the principal cross-sectional images can be improved by dividing a series of principal cross-sectional images obtained by main scanning into multiple groups, and applying image synthesis (e.g., averaging) to the principal cross-sectional images included in each group to generate multiple synthesized images.

The cross-sectional image generation unit 221 generates a cross-sectional image (supplementary cross-sectional image) representing the morphology of the supplementary cross-section based on the interference signal obtained by the spectroscope 130 during supplementary scanning of the supplementary cross-section of the fundus oculi Ef. The process of generating the supplementary cross-sectional image is performed in the same manner as the process of generating the main cross-sectional image. The supplementary cross-sectional image may be one cross-sectional image, or two or more cross-sectional images. In some exemplary embodiments, the image quality of the supplementary cross-sectional image can be improved by scanning the supplementary cross-section multiple times to generate multiple cross-sectional images, and then applying image synthesis to these cross-sectional images to generate a synthesized image. When the supplementary cross-sections C1 and C2 illustrated in FIG. 5A are applied, the cross-sectional image generation unit 221 generates a supplementary cross-sectional image corresponding to the supplementary cross-section C1 and a supplementary cross-sectional image corresponding to the supplementary cross-section C2. When the supplementary cross-section Cp illustrated in FIG. 5B is applied, the cross-sectional image generation unit 221 generates a supplementary cross-sectional image corresponding to the supplementary cross-section Cp.

The phase image generation unit 222 generates a phase image that represents the time-series changes in phase difference in the cross section of interest based on the interference signal obtained by the spectroscope 130 during the main scan. The interference signal used to generate the phase image may be the same as the interference signal used to generate the main cross section image by the cross section image generation unit 221. In this case, a natural positional correspondence is defined between the pixels of the main cross section image and the pixels of the phase image, making it easy to align the main cross section image and the phase image. In contrast, in some embodiments, the main cross section image and the phase image may be generated from different interference signals. In this case, for example, it is possible to align the main cross section image and the phase image using a known image registration method.

A non-limiting example of the process for generating a phase image will now be described. The phase image in this example is obtained by calculating the phase difference between adjacent A-line complex signals (i.e., signals corresponding to adjacent scanning points). In other words, the phase image in this example is generated based on the time-series changes in pixel values (brightness values) of the principal cross-sectional image. For any pixel in the principal cross-sectional image, the phase image generation unit 222 creates a graph showing the time-series changes in the brightness value of that pixel. The phase image generation unit 222 calculates the phase difference Δφ between two points in time t1 and t2 (t2 = t1 + Δt) separated by a predetermined time interval Δt on this graph. This phase difference Δφ is then defined as the phase difference Δφ(t1) at point t1 (or more generally, any point in time between points t1 and t2). By performing this series of processes for each of a number of preset points in time, the time-series changes in the phase difference at that pixel can be obtained. The time-series changes in the phase difference can be obtained by making the time interval Δt sufficiently small to ensure phase correlation. To achieve this, the scanning (main scanning) of the measurement light LS performs oversampling with the time interval Δt set to a value smaller than the time corresponding to the resolution of the cross-sectional image.

A phase image is an image obtained by visually representing the phase difference value for each pixel at each time point (imaging process). This imaging process includes, for example, processing that represents the phase difference value using predetermined display parameters (e.g., display color, brightness, etc.). Some forms of imaging process can use different display colors to indicate an increase in phase over time and a decrease in phase over time. For example, an increase in phase over time can be represented by red, and a decrease by blue. Furthermore, some forms of imaging process can represent the magnitude of phase change (amount of phase change) as the intensity of the display color. Some forms of imaging process described herein make it possible to visualize the direction and magnitude of blood flow. A phase image is generated by performing such imaging process on each pixel.

The data processing unit 230 includes, as exemplary elements for determining hemodynamic information, a vascular region identification unit 231 and a hemodynamic information generation unit 232. The hemodynamic information generation unit 232 may include a Doppler angle calculation unit 233, a blood flow velocity calculation unit 234, a vascular diameter calculation unit 235, and a blood flow amount calculation unit 236.

The vascular region identification unit 231 includes, for example, a processor operable according to a vascular region identification program. The hemodynamic information generation unit 232 includes, for example, a processor operable according to a hemodynamic information generation program. The Doppler angle calculation unit 233 includes, for example, a processor operable according to a Doppler angle calculation program. The blood flow velocity calculation unit 234 includes, for example, a processor operable according to a blood flow velocity calculation program. The vascular diameter calculation unit 235 includes, for example, a processor operable according to a vascular diameter calculation program. The blood flow volume calculation unit 236 includes, for example, a processor operable according to a blood flow volume calculation program.

The vascular region identification unit 231 analyzes an OCT image of the fundus and identifies an image region (vascular region) corresponding to a blood vessel in this OCT image. The vascular region identification unit 231 also analyzes a front image of the fundus (e.g., an observed image or photographed image acquired by the fundus camera unit 2) and identifies an image region (vascular region) corresponding to a blood vessel in this front image. The vascular region identification process performed by the vascular region identification unit 231 may be image processing using any image segmentation, and is performed, for example, by analyzing pixel values in the target image (e.g., threshold processing). In some embodiments, the vascular region identification unit 231 identifies a vascular region corresponding to the blood vessel of interest Db from each of the principal cross-sectional image, supplementary cross-sectional image, and phase image.

In some cases, the principal and supplementary cross-sectional images have sufficient resolution to be analyzed in the vascular region identification process, but the phase image does not have enough resolution to identify the boundaries of the vascular region. Even in such cases, since blood flow dynamics information is generated based on the phase image, it is necessary to identify the vascular region in the phase image with high accuracy. To achieve this, the process described below can be used, for example.

When the principal cross-sectional image and the phase image are generated based on the same interference signal, the natural positional correspondence relationship (described above) defined between the pixels of the principal cross-sectional image and the pixels of the phase image can be utilized. For example, the vascular region identification unit 231 can perform a process of analyzing the principal cross-sectional image to identify the vascular region, and a process of identifying the image region in the phase image that corresponds to the vascular region in the principal cross-sectional image based on the positional correspondence relationship. The image region in the phase image is used as the vascular region in this phase image. This allows the vascular region in the phase image to be determined with high accuracy. When the principal cross-sectional image and the phase image are generated based on mutually different interference signals, the vascular region in the phase image can be determined by using the results of image registration (described above) between the principal cross-sectional image and the phase image instead of the natural positional correspondence relationship described above.

The hemodynamic information generation unit 232 generates information indicating the hemodynamics of blood flow in the fundus blood vessels (hemodynamic information). The hemodynamic information may be information on any parameter (hemodynamic parameter) indicating the fundus hemodynamics. While this disclosure describes blood flow velocity and blood volume, hemodynamic parameters are not limited to these.

The hemodynamic information generation unit 232 generates hemodynamic information related to the blood vessel of interest Db. As described above, some embodiments of the hemodynamic information generation unit 232 include a Doppler angle calculation unit 233, a blood flow velocity calculation unit 234, a blood vessel diameter calculation unit 235, and a blood flow rate calculation unit 236.

The Doppler angle calculation unit 233 calculates an estimated value of the tilt of the blood vessel of interest based on the data of the supplementary cross section (cross-sectional data, supplementary cross-sectional image) collected by the supplementary scan. The calculated value may be, for example, a value based on the measured value of the tilt of the blood vessel of interest in the cross section of interest, or an approximate value thereof. As mentioned above, the tilt of the blood vessel of interest is a parameter equivalent to the Doppler angle in Doppler OCT. In other words, since the Doppler angle is the angle between the incident direction of the measurement light LS in the main scan for the cross section of interest and the direction of the axis of the blood vessel of interest (i.e., the tilt of the blood vessel of interest), the tilt of the blood vessel of interest is equivalent to the Doppler angle.

An example of actually measuring the gradient value of a blood vessel of interest will be described (first example of gradient estimation). When the supplementary cross sections C1 and C2 shown in Figure 5A are applied, the Doppler angle calculation unit 233 can calculate the gradient of the blood vessel of interest Db on the cross section of interest C0 based on the positional relationship between the cross section of interest C0, the supplementary cross sections C1, and the supplementary cross sections C2, and the vascular region identification result obtained by the vascular region identification unit 231.

The method for calculating the gradient of the blood vessel of interest Db will be described with reference to Figure 6A. The symbols G0, G1, and G2 respectively indicate the principal cross-sectional image of the cross-section of interest C0, the supplementary cross-sectional image of the supplementary cross-section C1, and the supplementary cross-sectional image of the supplementary cross-section C2. Furthermore, the symbols V0, V1, and V2 respectively indicate the vascular region in the principal cross-sectional image G0, the vascular region in the supplementary cross-sectional image G1, and the vascular region in the supplementary cross-sectional image G2. The z coordinate axis shown in Figure 6A substantially coincides with the incident direction of the measurement light LS. Furthermore, the distance between the principal cross-sectional image G0 (cross-section of interest C0) and the supplementary cross-sectional image G1 (supplementary cross-section C1) is indicated by d, and the distance between the principal cross-sectional image G0 (cross-section of interest C0) and the supplementary cross-sectional image G2 (supplementary cross-section C2) is also indicated by d. The distance between adjacent cross-sectional images, i.e., the distance between adjacent cross-sections, is called the inter-section distance.

The Doppler angle calculation unit 233 can calculate the gradient A of the blood vessel of interest Db in the cross section of interest C0 based on the positional relationship between the three blood vessel regions V0, V1, and V2. This positional relationship can be determined, for example, by connecting the three blood vessel regions V0, V1, and V2. As a specific example, the Doppler angle calculation unit 233 can identify the characteristic positions of each of the three blood vessel regions V0, V1, and V2 and connect these characteristic positions. This characteristic position may be, for example, one of the center position, center of gravity position, top (position with the smallest z coordinate value), and bottom (position with the largest z coordinate value). The characteristic positions may be connected by any method, such as connecting them with a line segment or an approximate curve (spline curve, Bezier curve, etc.).

Furthermore, the Doppler angle calculation unit 233 calculates the gradient A of the blood vessel of interest Db in the cross section of interest C0 based on the connecting lines connecting the characteristic positions identified from the three vascular regions V0, V1, and V2. If the connecting lines are line segments, the Doppler angle calculation unit 233 can calculate the gradient A based on the gradient of a first line segment connecting the characteristic position of the cross section of interest C0 to the characteristic position of the supplementary cross section C1, and the gradient of a second line segment connecting the characteristic position of the cross section of interest C0 to the characteristic position of the supplementary cross section C2. A non-limiting example of this calculation process may be calculating the average gradient of the two line segments. If the connecting lines are approximated curves, the Doppler angle calculation unit 233 can calculate the gradient A as the gradient of the approximated curve at the position where the approximated curve intersects with the cross section of interest C0. In the Doppler angle calculation process, the inter-section distance d is used, for example, when embedding the cross-sectional images G0 to G2 in an xyz coordinate system to find the connecting lines.

In the above example, the vascular region in three cross sections is considered. In some embodiments, the gradient may be calculated by considering two cross sections. As a non-limiting example, the gradient A of the blood vessel Db of interest in the cross section C0 may be calculated as the gradient of the first line segment or the gradient of the second line segment. Alternatively, the gradient A of the blood vessel Db of interest in the cross section C0 may be calculated based on two supplementary cross section images G1 and G2.

An example of calculating an approximate value of the gradient of a blood vessel of interest will be described (second example of gradient estimation). When the supplementary cross section Cp shown in Figure 5B is applied, the Doppler angle calculation unit 233 can analyze the supplementary cross section image corresponding to the supplementary cross section Cp to calculate an approximate value of the gradient of the blood vessel of interest Db on the cross section of interest C0.

The method for approximating the gradient of the blood vessel of interest Db will be explained with reference to Figure 6B. The symbol Gp indicates the supplementary cross-sectional image at the supplementary cross-section Cp. The symbol A indicates the gradient of the blood vessel of interest Db at the cross-section of interest C0, similar to the example shown in Figure 6A.

In this example, the Doppler angle calculation unit 233 can analyze the supplementary cross-sectional image Gp to identify an image region corresponding to a specific tissue of the fundus oculi Ef. For example, the Doppler angle calculation unit 233 can identify an image region (internal limiting membrane region) M corresponding to the internal limiting membrane (ILM), which is a superficial tissue of the retina. To identify the image region, for example, a known image segmentation method is used.

It is known that the internal limiting membrane and the fundus blood vessels are approximately parallel to each other. The Doppler angle calculation unit 233 calculates the gradient A _app of the internal limiting membrane region M on the cross section C0 of interest. The gradient A _app of the internal limiting membrane region M on the cross section C0 of interest is used as an approximation of the gradient A of the blood vessel Db of interest on the cross section C0 of interest.

Note that the slope A shown in Figures 6A and 6B is a vector representing the orientation of the blood vessel of interest Db, and its value may be defined arbitrarily. In some non-limiting examples, the value of the slope A can be defined as the angle (Doppler angle) formed between the slope (vector) A and the z-axis. Similarly, the slope A _app shown in Figure 6B is a vector representing the orientation of the internal limiting membrane region M, and its value may be defined arbitrarily. For example, the value of the slope A _app can be defined as the angle (approximate value of the Doppler angle) formed between the slope (vector) A _app and the z-axis. Here, the orientation of the z-axis substantially coincides with the incident direction of the measurement light LS.

As a third example of estimating the gradient of a blood vessel of interest, the Doppler angle calculation unit 233 can analyze the supplementary cross-sectional image Gp shown in FIG. 6B to identify an image region corresponding to the blood vessel of interest Db and determine the gradient of that image region at a position corresponding to the cross section of interest C0. At this time, the Doppler angle calculation unit 233 can, for example, curve-approximate the boundary or central axis of the image region corresponding to the blood vessel of interest Db, and determine the gradient of that approximate curve at a position corresponding to the cross section of interest C0. A similar curve approximation can also be applied to the image region corresponding to a specific tissue of the fundus Ef described above (for example, the internal limiting membrane region M).

The processing performed by the Doppler angle calculation unit 233 is not limited to the above example, and may be any processing that can obtain an estimated value of the inclination of the blood vessel Db of interest (e.g., the inclination value of the blood vessel Db itself, its approximate value, etc.) based on cross-sectional data collected by applying an OCT scan to a cross section of the fundus Ef.

The blood flow velocity calculation unit 234 calculates the blood flow velocity of blood flowing through the blood vessel Db at the cross section of interest C0 based on information on the time series change in phase difference obtained as a phase image. The calculated information may be the value of the blood flow velocity at a specific time point (blood flow velocity value), or the time series change in the blood flow velocity value (blood flow velocity change information). The blood flow velocity value may be a value at a specific cardiac phase selected from the cardiac cycle (for example, the R wave phase). The period for which the blood flow velocity change information is defined may be the entire period during which the main scan is applied to the cross section of interest C0, or a selected portion of that period.

When blood flow velocity change information is obtained, the blood flow velocity calculation unit 234 may calculate a statistical value of the blood flow velocity during the measurement period. This statistical value may be, for example, any of the mean value, standard deviation, variance, median, mode, maximum value, minimum value, local maximum value, and local minimum value. However, it is not limited to these. Furthermore, when blood flow velocity change information is obtained, the change in blood flow velocity can be visualized to generate visual information (for example, a graph, histogram, etc.).

The blood flow velocity calculation unit 234 calculates the blood flow velocity using the Doppler OCT technique, taking into account the gradient A (or its approximate value A _app ) of the blood vessel Db of interest in the cross section C0 calculated by the Doppler angle calculation unit 233. Specifically, the blood flow velocity calculation unit 234 can use the following formula: Δf=[2nv cos θ]/λ.

Where:
Δf represents the Doppler shift experienced by the scattered light of the measurement light LS;
n denotes the refractive index of the medium;
v denotes the flow velocity of the medium (blood flow velocity);
θ represents the angle between the incident direction of the measurement light LS and the flow vector of the medium;
λ indicates the center wavelength of the measurement light LS.

In some aspects, n and λ are known, Δf is obtained from the time-series change in the phase difference, and θ is the Doppler angle (obtained from the slope A or the approximate value A _app ). The blood flow velocity calculation unit 234 calculates the blood flow velocity v by substituting the medium refractive index n, the center wavelength λ of the measurement light LS, the Doppler shift Δf, and the Doppler angle θ into the above equation: v = [λΔf] / [2n cos θ]. Note that the method for calculating the blood flow velocity is not limited to the method described herein, and any method that can be used in Doppler OCT may be used.

The blood vessel diameter calculation unit 235 calculates the diameter of the blood vessel of interest Db in the cross section of interest C0. Examples of this calculation method include a first calculation method using a frontal fundus image and a second calculation method using a cross section image.

When the first calculation method is applied, an image of the area of the fundus Ef including the position of the cross section C0 of interest is captured in advance. The resulting frontal fundus image may be, for example, a frame of an observed image, a captured image (color image, fluorescent contrast image), or an OCT angiography image (motion contrast image).

The blood vessel diameter calculation unit 235 sets the scale in the frontal fundus image based on various factors that determine the relationship between the scale in the image and the scale in real space, such as the imaging angle of view (imaging magnification, scan dimensions), working distance, and information about the ocular optical system. This scale, for example, corresponds the spacing between adjacent pixels (pixel pitch) to the scale in real space (for example, pixel pitch = 10 micrometers). The blood vessel diameter calculation unit 235 can calculate the diameter of the blood vessel Db of interest in the cross section C0 of interest, i.e., the diameter of the blood vessel region V0, based on the scale set in the frontal fundus image and the pixels in the blood vessel region V0.

The second calculation method will now be described. In the second calculation method, a cross-sectional image of the cross-section of interest C0 is typically used. This cross-sectional image may be a principal cross-sectional image or another cross-sectional image. The scale of the cross-sectional image is determined based on the OCT measurement conditions, etc. In some embodiments, the cross-section of interest C0 is scanned as shown in FIG. 5A or 5B. The length of the cross-section of interest C0 is determined based on various factors that determine the relationship between the scale on the image and the scale in real space, such as the scan dimensions, working distance, and information about the ocular optical system. The blood vessel diameter calculation unit 235 can calculate the diameter of the blood vessel of interest Db in the cross-section of interest C0 by performing a process to determine the pixel pitch based on the length of the cross-section of interest C0 and a process similar to that of the first calculation method.

The blood flow rate calculation unit 236 calculates the blood flow rate in the blood vessel of interest Db based on the blood flow velocity calculated by the blood flow velocity calculation unit 234 and the blood vessel diameter calculated by the blood vessel diameter calculation unit 235. An example of this process is described below. Assume that the blood flow in the blood vessel is a Hagen-Poiseuille flow. Furthermore, the blood vessel diameter is represented by w, and the maximum value of the blood flow velocity is represented by Vm. In this case, the blood flow rate Q is expressed by the following equation: Q = [πw ² Vm]/8.

The blood flow calculation unit 236 calculates the blood flow Q by substituting the blood vessel diameter value w calculated by the blood vessel diameter calculation unit 235 and the maximum value Vm based on the blood flow velocity value calculated by the blood flow velocity calculation unit 234 into this formula.

The types of parameters calculated by the hemodynamic information generation unit 232 are not limited to the several parameters mentioned above. For example, the hemodynamic information generation unit 232 can calculate parameters obtained by relative measurement in addition to, or instead of, parameters obtained by absolute measurement such as blood flow velocity and blood flow rate. Some non-limiting examples of hemodynamic parameters that can be used in this embodiment will be described below.

When an inaccurate Doppler angle value is obtained, it is possible to extract and analyze a profile from an image showing the inside of a blood vessel, or to extract the shape of the pulse wave curve (waveform derived from the heartbeat) from the time course of an image showing the inside of a blood vessel. Several studies have demonstrated the usefulness of the relative values obtained in this way. It is also possible to extract specific characteristic parameters from the waveform of the pulse wave curve. The extracted characteristic parameters can be used for hemodynamic evaluation, disease evaluation, etc.

The flow of blood within blood vessels can be considered essentially laminar, with the flow velocity decreasing as the blood approaches the vessel wall due to the frictional drag from the vessel wall, and being greatest at the center of the vessel. Laminar flow is a parabolic flow, and the diastolic and systolic waveforms in the cardiac cycle can be read from the pulse wave. This makes it possible to determine the characteristics of these waveforms. For example, parameters relating to deviations from a specific waveform (presence or absence of deviation, degree, frequency, etc.) can be determined.

The blood flow velocity in veins is not necessarily constant, and slight changes (pulsations) are observed. It is also possible to calculate parameters that indicate these minute pulsations (absolute velocity parameters, relative velocity parameters, etc.).

<Non-limiting aspects of the ophthalmic device>
Several non-limiting aspects realized by applying the ophthalmic apparatus 1 having the hardware aspects, software aspects, and functional aspects described above will be described. In the following description, matters related to the ophthalmic apparatus 1 will be referred to and used as appropriate. Any matter related to the ophthalmic apparatus 1 can be at least partially combined with each aspect. Two or more aspects can be at least partially combined.

FIG. 7 shows the configuration of an ophthalmic device 1000 according to one non-limiting embodiment. The ophthalmic device 1000 includes a scanning unit 1010, a cross-sectional image generating unit 1020, a vascular region identifying unit 1030, a vascular region matching unit 1040, and a vascular map generating unit 1050.

The scanning unit 1010 is configured to collect data by applying an OCT scan to the fundus Ef of the subject's eye E. A non-limiting aspect of the ophthalmic apparatus 1 can achieve the functions of the scanning unit 1010 using the fundus camera unit 2 and the OCT unit 100.

The scanning unit 1010 can apply OCT scanning to the fundus oculi Ef using a scan pattern that does not involve a flyback. A flyback is an operation that moves the scan position to a predetermined initial position without collecting data. For example, in a raster scan consisting of multiple B-scans arranged parallel to each other and oriented in the same scanning direction, a flyback is an operation that moves the scan position (the target position for projecting the measurement light LS) from the end position of one B-scan to the start position of the next B-scan. A scan pattern that involves a flyback results in a longer period of time during which data collection is stopped, making it relatively disadvantageous for processing or operations that require speed. Some embodiments have been achieved by focusing on this issue, and aim to improve the quality of Doppler angle estimation and alignment performed, for example, in the preparation stage for the main scan (repeated scan) of OCT blood flow measurement.

Figures 8A to 8C show an example of a scan pattern that does not involve a flyback. The scan pattern in this example is a concentric pattern that is a combination of two circular patterns. Note that the number of circular patterns included in the concentric pattern may be any number, and may be three or more.

Figure 8A shows the fundus Ef. Reference numeral 1200 denotes the optic disc, and reference numeral 1200a denotes the central position of the optic disc 1200 (optic disc center). Reference numerals 1201 and 1202 denote two circular patterns. The centers of the two circular patterns 1201 and 1202 are both the optic disc center 1200a.

As shown in FIG. 8B, the radius of circular pattern 1201 is R1, and the radius of circular pattern 1202 is R2. Here, radius R2 is larger than radius R1. The region of the fundus Ef to which circular pattern 1201 is applied is a cylindrical side surface 1201b defined by a central axis 1201a passing through the optic disc center 1200a and radius R1. Furthermore, the region of the fundus Ef to which circular pattern 1202 is applied is a cylindrical side surface 1202b defined by a central axis 1202a passing through the optic disc center 1200a and radius R2. The central axis 1202a coincides with the central axis 1201a.

Figure 8C shows an example of an OCT scan using a scan pattern consisting of two circular patterns 1201 and 1202. In this example, the OCT scan is performed by performing a circle scan along circular pattern 1202 immediately after a circle scan along circular pattern 1201. More specifically, in this example, the OCT scan first starts a counterclockwise circle scan 1203a along circular pattern 1201 from position 1201c on circular pattern 1201. This circle scan 1203a is performed once or more than once. The circle scan 1203a along circular pattern 1201 ends at position 1201c. In this example, the OCT scan is performed by performing an operation 1203b (changing the orientation of the optical scanner 44) to move the scan target position from position 1201c on circular pattern 1201 to position 1202c on circular pattern 1202 immediately after circle scan 1203a. In this example, immediately after this operation (scan target movement) 1203b, the OCT scan begins a counterclockwise circle scan 1203c along the circular pattern 1202 from position 1202c on the circular pattern 1202. This circle scan 1203c is performed once or more than once. Note that data may be collected while the scan target movement 1203b is being performed. In other words, some aspects of the scan target movement 1203b may be a scan (data collection).

The scan patterns shown in Figures 8A to 8C are one example of a scan pattern that includes multiple patterns (two circular patterns 1201 and 1202) that do not each involve a flyback. Other scan patterns that have such features include a scan pattern that combines multiple closed curves having the same or different shapes, a scan pattern that combines multiple polygons having the same or different shapes, and a raster scan that combines multiple B-scans that are oriented alternately.

Furthermore, the scan pattern shown in Figures 8A to 8C is one example of a scan pattern that includes a concentric pattern, which is a combination of multiple concentrically arranged patterns. Other scan patterns with this configuration include a scan pattern that combines multiple closed curves that are concentrically arranged and have the same shape, and a scan pattern that combines multiple polygons that are concentrically arranged and have the same shape. The multiple cross sections of the fundus Ef scanned with this scan pattern include multiple concentric cross sections that respectively correspond to the multiple concentrically arranged patterns that make up the scan pattern. In the example shown in Figures 8A to 8C, two cylindrical side surfaces 1201b and 1202b correspond to such multiple concentric cross sections.

The scan pattern without flyback is not limited to the above examples and may be any pattern. For example, a spiral scan pattern, a Lissajous curve scan pattern, or similar scan patterns may be employed.

The cross-sectional image generating unit 1020 is configured to generate a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus Ef based on data collected from the fundus Ef by the scanning unit 1010. The cross-sectional image generating unit 1020 is realized by cooperation between hardware including circuits and cross-sectional image generating software. A non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the cross-sectional image generating unit 1020 using the data processing unit 230 (image generating unit 220).

When a scan pattern that is a combination of multiple patterns that do not involve a flyback is applied, the cross-sectional image generation unit 1020 generates a cross-sectional image corresponding to the cross section to which each of the multiple patterns that do not involve a flyback is applied.

When a scan pattern consisting of multiple concentric patterns, each of which does not involve a flyback, is applied, the scan unit 1010 collects data from multiple concentric cross sections corresponding to the multiple patterns. The cross-sectional image generation unit 1020 generates cross-sectional images corresponding to each concentric cross section based on the data collected from the multiple concentric cross sections.

In the example of Figures 8A to 8C, the scanning unit 1010 collects data from the cylinder side surface 1201b, which corresponds to the circular pattern 1201, and collects data from the cylinder side surface 1202b, which corresponds to the circular pattern 1202. The cross-sectional image generating unit 1020 generates a cross-sectional image depicting the cylinder side surface 1201b based on the data collected from the cylinder side surface 1201b, and generates a cross-sectional image depicting the cylinder side surface 1202b based on the data collected from the cylinder side surface 1202b.

When the scanning unit 1010 applies OCT scans to the fundus Ef multiple times using a scan pattern that does not involve flyback to collect multiple pieces of data, the cross-sectional image generating unit 1020 can generate multiple cross-sectional images corresponding to the multiple scans and synthesize these multiple cross-sectional images to generate a composite cross-sectional image. The synthesis of multiple cross-sectional images is, for example, averaging. The averaging reduces random noise such as speckle noise.

In the example of Figures 8A to 8C, the scanning unit 1010 performs a circle scan using a circular pattern 1201 multiple times to collect multiple pieces of data from the cylinder's side surface 1201b, and performs a circle scan using a circular pattern 1202 multiple times to collect multiple pieces of data from the cylinder's side surface 1202b. The cross-sectional image generating unit 1020 generates multiple cross-sectional images depicting the cylinder's side surface 1201b based on each of the multiple pieces of data collected from the cylinder's side surface 1201b, and generates multiple cross-sectional images depicting the cylinder's side surface 1202b based on each of the multiple pieces of data collected from the cylinder's side surface 1202b. Furthermore, the cross-sectional image generating unit 1020 synthesizes the multiple cross-sectional images of the cylinder's side surface 1201b to generate a composite cross-sectional image, and synthesizes the multiple cross-sectional images of the cylinder's side surface 1202b to generate a composite cross-sectional image.

If the scanning unit 1010 applies OCT scans to the fundus Ef multiple times using a scan pattern that does not involve flyback to collect multiple pieces of data, and the cross-sectional image generating unit 1020 generates multiple cross-sectional images corresponding to the multiple scans, the ophthalmologic device 1000 may select a cross-sectional image suitable for subsequent processing (e.g., identifying a vascular region) from among the multiple cross-sectional images generated. Here, evaluation of each cross-sectional image may be performed using any method. As a non-limiting example, Portilla-Simoncelli Statistics (PSS), an image texture feature based on human visual perception, may be used as the evaluation value. In this case, a cross-sectional image with a large PSS value is selected.

The vascular region identification unit 1030 is configured to analyze each cross-sectional image generated by the cross-sectional image generation unit 1020 and detect vascular region groups. This identifies multiple vascular region groups corresponding to the multiple cross-sectional images generated by the cross-sectional image generation unit 1020. A vascular region group includes one or more vascular regions. A vascular region is an image region corresponding to a cross section of a blood vessel.

The image analysis method for detecting vascular regions from cross-sectional images may be any method. For example, this image analysis may be any image segmentation method. The image segmentation method performed by the vascular region identification unit 1030 may be, for example, either or both of an image segmentation method using a machine learning algorithm (machine learning model) and an image segmentation method using a non-machine learning algorithm.

Non-limiting examples of image segmentation methods applicable to the vascular region identification unit 1030 include thresholding-based methods, edge detection-based methods, region-based methods, clustering-based methods, convolutional neural network (CNN)-based methods, transformer-based methods, generative adversarial network (GAN)-based methods, self-supervised learning (SSL)-based methods, graph-based methods, etc. The image segmentation performed by the vascular region identification unit 1030 may be a combination of two or more methods.

In some embodiments, the vascular region identification unit 1030 applies projection (image accumulation) in the A-scan direction (z direction) of the OCT scan applied to the fundus Ef by the scan unit 1010 to each cross-sectional image generated by the cross-sectional image generation unit 1020. This generates multiple projection images corresponding to the multiple cross-sectional images generated by the cross-sectional image generation unit 1020. Furthermore, the vascular region identification unit 1030 detects a vascular region group from the cross-sectional image that is the original image of the projection image (i.e., the cross-sectional image corresponding to the projection image) based on the brightness distribution in each generated projection image. Generally, the brightness of pixels corresponding to blood vessels is lower than the brightness of pixels corresponding to tissue other than blood vessels. The vascular region detection of this embodiment may include processing (e.g., threshold processing, binarization, etc.) to detect low-brightness regions in the projection image. Furthermore, this embodiment may combine a brightness-based image segmentation method with an image segmentation method based on an index other than brightness.

The vascular region identification unit 1030 is realized by the cooperation of hardware including circuitry and vascular region identification software. The non-limiting aspect of the ophthalmologic apparatus 1 can perform analysis processing to detect vascular regions from OCT cross-sectional images using the vascular region identification function realized using the data processing unit 230 (vascular region identification unit 231).

The vascular region matching unit 1040 is configured to match vascular regions corresponding to different cross sections of the same blood vessel among multiple vascular region groups identified from multiple cross-sectional images by the vascular region identification unit 1030.

For the purpose of explaining the vascular region matching process, two adjacent cross-sectional images will be referred to as the first cross-sectional image and the second cross-sectional image. Furthermore, the cross-section of the fundus Ef corresponding to the first cross-sectional image will be referred to as the first cross-section, and the cross-section of the fundus Ef corresponding to the second cross-sectional image will be referred to as the second cross-section. Furthermore, the vascular region group identified from the first cross-sectional image will be referred to as the first vascular region group, and the vascular region group identified from the second cross-sectional image will be referred to as the second vascular region group.

When the distance between the first cross section and the second cross section is sufficiently small, the vascular region association unit 1040 in a non-limiting embodiment determines the position of each vascular region (referred to as the first vascular region) in the first cross section image and the position of each vascular region (referred to as the second vascular region) in the second cross section image. The position of a vascular region may be the position of a feature point in the vascular region (e.g., the center position, the center of gravity position, the upper end position, the lower end position, etc.). Furthermore, the position of a vascular region may be information indicating its position in the cross section image in which it was detected (i.e., coordinates in a two-dimensional coordinate system representing the pixel position of the cross section image), or information indicating its position in a three-dimensional image including both the first cross section and the second cross section (coordinates in a three-dimensional coordinate system representing the position in the three-dimensional region), or other information that can be used to define the position.

It is rare for the course of blood vessels to change suddenly (discontinuously), and this is particularly rare in the relatively large blood vessels that are the subject of OCT blood flow measurement. Therefore, if the distance between the first cross section and the second cross section is sufficiently small, it can be assumed that there will be no significant discrepancy between the position of the blood vessel region (first blood vessel region) in the first cross-sectional image for one blood vessel and the position of the blood vessel region (second blood vessel region) in the second cross-sectional image.

Under this assumption, the vascular region association unit 1040 can identify pairs of first and second vascular regions corresponding to different cross sections of the same blood vessel by comparing the position of each vascular region in the first cross-sectional image with the position of each vascular region in the second cross-sectional image, and associate these with each other. For example, for any first vascular region belonging to a first vascular region group, the vascular region association unit 1040 may be configured to compare the position of the first vascular region with the position of each second vascular region belonging to a second vascular region group, identify the second vascular region that is the shortest distance from the first vascular region, and associate the identified second vascular region with the first vascular region.

If the distance between the first cross section and the second cross section is sufficiently small, not only can it be assumed that the positions of the first vascular region and the second vascular region corresponding to the same blood vessel are close to each other, but other assumptions can also be considered. For example, it can be assumed that the areas of the first vascular region and the second vascular region corresponding to the same blood vessel are substantially equal, or that the shapes of the first vascular region and the second vascular region corresponding to the same blood vessel are substantially equal. Furthermore, if the distance between the first cross section and the second cross section is sufficiently small, it can be assumed that no crossing of blood vessels occurs in the region between these cross sections, and therefore it can be assumed that the spatial order (positional order) of the multiple blood vessels depicted on both cross sections is the same. The vascular region matching unit 1040 can be configured to perform the vascular region matching process taking such assumptions into account.

The criteria for determining whether the distance between the first and second cross sections is sufficiently small may be determined arbitrarily, and may take into consideration, for example, the position of the area to which the OCT scan is applied on the fundus Ef, the state of the fundus blood vessels, etc. Furthermore, when OCT blood flow measurement is performed, the distance between the two supplementary cross sections C1 and C2 shown in FIG. 5A (supplementary cross section images G1 and G2 shown in FIG. 6A) is generally set to be sufficiently small, so in embodiments intended for similar applications, the distance between the first and second cross sections can be assumed to be sufficiently small.

In contrast, if the distance between the first cross section and the second cross section is not sufficiently small, the vascular region association unit 1040 in a non-limiting embodiment may be configured to, for example, determine the positional relationship between the first cross section and the second cross section, and the positional relationship between each vascular region belonging to the first vascular region group and each vascular region belonging to the second vascular region group, by referring to separately acquired images (frontal fundus images and/or three-dimensional fundus images). Furthermore, the vascular region association unit 1040 may be configured to identify pairs of first and second vascular regions corresponding to different cross sections of the same blood vessel by referring to the obtained positional relationship, and associate these with each other.

The vascular region matching unit 1040 is realized by the cooperation of hardware including circuits and vascular region matching software. The non-limiting aspect of the ophthalmologic apparatus 1 can perform analytical processing for matching between vascular regions using the vascular region matching function realized using the data processing unit 230.

The vascular map generation unit 1050 is configured to generate information (vascular map) indicating the distribution of blood vessels based on the results of the vascular region matching obtained by the vascular region matching unit 1040. The range of vascular distribution represented by the vascular map includes at least a portion of the area of the fundus Ef defined by the multiple cross sections corresponding to the multiple cross-sectional images generated by the cross-sectional image generation unit 1020.

The vascular map is information that indicates at least the positions (coordinates) of blood vessels (the same blood vessels mentioned above) corresponding to multiple vascular regions that have been associated with each other by the vascular region association unit 1040, and is information that indicates the distribution state of blood vessels in the fundus Ef. The vascular map may be visual information obtained by visualizing vascular positions, or may be unvisualized vascular position data. The visual information may be provided for image processing, image analysis, display, printing, etc. The vascular position data may be provided for data processing, data analysis, imaging (visualization), etc.

The vascular map generation unit 1050 is realized by the cooperation of hardware including circuits and vascular map generation software. The non-limiting aspect of the ophthalmic device 1 can perform processing for generating a vascular map using a vascular map generation function realized using the data processing unit 230.

Several operational examples of the ophthalmic device 1000 will be described. The processing content of the steps in each operational example is not limited and may be modified as desired. Furthermore, the order of the steps in each operational example is not limited and may be modified as desired.

Figure 9 shows an example of the operation of the ophthalmic device 1000. For a non-limiting example, see Figures 8A to 8C.

First, in step S1, the scanning unit 1010 applies an OCT scan using a scan pattern without flyback to the fundus Ef of the subject's eye E to collect data.

In a specific example of step S1, the OCT scan may be a combination of a circle scan 1203a along the circular pattern 1201, scan target movement 1203b, and a circle scan 1203c along the circular pattern 1202, as shown in FIG. 8C. This allows data to be collected from the cylinder side surface 1201b along the circular pattern 1201, and data to be collected from the cylinder side surface 1202b along the circular pattern 1202.

In step S2, the cross-sectional image generation unit 1020 generates multiple cross-sectional images corresponding to multiple cross sections of the fundus oculi Ef based on the data collected in step S1.

In a specific example of step S2, the cross-sectional image generation unit 1020 generates a cross-sectional image 1301 representing the cylinder side surface 1201b based on data collected from the cylinder side surface 1201b along the circular pattern 1201 in step S1 (see FIG. 10A). Furthermore, the cross-sectional image generation unit 1020 generates a cross-sectional image 1302 representing the cylinder side surface 1202b based on data collected from the cylinder side surface 1202b along the circular pattern 1202 in step S1 (see FIG. 10A).

In step S3, the vascular region identification unit 1030 detects vascular region groups from each of the multiple cross-sectional images generated in step S2. This identifies multiple vascular region groups corresponding to each of the multiple cross-sectional images.

In a specific example of step S3, the vascular region identification unit 1030 detects vascular region groups 1301a, 1301b, 1301c, and 1301d from the cross-sectional image 1301 generated in step S2 (see Figure 10A). Furthermore, the vascular region identification unit 1030 detects vascular region groups 1302a, 1302b, 1302c, and 1302d from the cross-sectional image 1302 generated in step S2 (see Figure 10A).

In step S4, the vascular region association unit 1040 associates vascular regions corresponding to different cross sections of the same blood vessel among the multiple vascular region groups identified in step S4.

In a specific example of step S4, the vascular region matching unit 1040 identifies pairs of vascular regions corresponding to different cross sections of the same blood vessel between the vascular region group 1301a, 1301b, 1301c, and 1301d corresponding to the cross-sectional image 1301 and the vascular region group 1302a, 1302b, 1302c, and 1302d corresponding to the cross-sectional image 1302. In this example, the following four vascular region pairs are identified: a first pair consisting of vascular region 1301a and vascular region 1302a corresponding to two cross sections of the first blood vessel; a second pair consisting of vascular region 1301b and vascular region 1302b corresponding to two cross sections of the second blood vessel; a third pair consisting of vascular region 1301c and vascular region 1302c corresponding to two cross sections of the third blood vessel; and a fourth pair consisting of vascular region 1301d and vascular region 1302d corresponding to two cross sections of the fourth blood vessel. The vascular region association unit 1040 associates the two vascular regions belonging to each pair. This results in association 1303a between the first pair, association 1303b between the second pair, association 1303c between the third pair, and association 1303d between the fourth pair.

In step S5, the vascular map generation unit 1050 generates a vascular map based on the vascular region matching results obtained in step S4.

In a specific example of step S5, the vascular map generation unit 1050 determines a first connection region connecting vascular regions 1301a and 1302a belonging to the first pair, a second connection region connecting vascular regions 1301b and 1302b belonging to the second pair, a third connection region connecting vascular regions 1301c and 1302c belonging to the third pair, and a fourth connection region connecting vascular regions 1301d and 1302d belonging to the fourth pair.

In the first pair, vascular region 1301a is the region on cylinder side surface 1201b along circular pattern 1201, and vascular region 1302a is the region on cylinder side surface 1202b along circular pattern 1202. The first connection region connects vascular region 1301a and vascular region 1302a. The first connection region has two ends, the first end being located in vascular region 1301a (cylinder side surface 1201b, circular pattern 1201) and the second end being located in vascular region 1302a (cylinder side surface 1202b, circular pattern 1202). The same applies to the second connection region based on the second pair, the third connection region based on the third pair, and the fourth connection region based on the fourth pair.

10B and 10C show two non-limiting examples of vascular maps. The vascular map 1310 in FIG. 10B represents a two-dimensional vascular distribution when viewed from a frontal perspective. Objects shown with dashed lines are included to aid in explanation and may not be visualized in the vascular map 1310. At least the circular patterns 1201 and 1202 may be visualized. Reference numeral 1311 denotes the optic disc. Reference numerals 1312a, 1312b, 1312c, and 1312d each denote a blood vessel.

Reference symbol 1313a indicates a first connection region connecting two vascular regions 1301a and 1302a belonging to the first pair. The first connection region 1313a corresponds to a portion of the blood vessel 1312a. Reference symbol 1313b indicates a second connection region connecting two vascular regions 1301b and 1302b belonging to the second pair. The second connection region 1313b corresponds to a portion of the blood vessel 1312b. Reference symbol 1313c indicates a third connection region connecting two vascular regions 1301c and 1302c belonging to the third pair. The third connection region 1313c corresponds to a portion of the blood vessel 1312c. Reference symbol 1313d indicates a fourth connection region connecting two vascular regions 1301d and 1302d belonging to the fourth pair. The fourth connection region 1313d corresponds to a portion of the blood vessel 1312d.

A frontal fundus image can be used to visualize the optic disc 1311 and/or blood vessels 1312a-1312d. This frontal fundus image may be, for example, a fundus camera image, an SLO image, or an OCT frontal image (projection image, an annular image, etc.).

The vascular map 1320 in Figure 10C represents a three-dimensional distribution of blood vessels. The vascular map 1320 may be three-dimensional data defined in a three-dimensional coordinate system, three-dimensional image data (volume data, stack data, etc.) that visualizes this three-dimensional data, or a rendered image of this three-dimensional image data (volume rendering image, etc.). Objects indicated by dashed lines are shown to aid in explanation and do not need to be visualized in the vascular map 1320. Note that the cylinder side surfaces 1201b and 1202b, as well as the circular patterns 1201 and 1202 (not shown), may be visualized. Reference numeral 1321 denotes the optic disc. Reference numerals 1322a, 1322b, 13222c, and 1322d each denote a blood vessel.

Reference symbol 1323a indicates a first connection region connecting two vascular regions 1301a and 1302a belonging to the first pair. The first connection region 1323a corresponds to a portion of the blood vessel 1322a. Reference symbol 1323b indicates a second connection region connecting two vascular regions 1301b and 1302b belonging to the second pair. The second connection region 1323b corresponds to a portion of the blood vessel 1322b. Reference symbol 1323c indicates a third connection region connecting two vascular regions 1301c and 1302c belonging to the third pair. The third connection region 1323c corresponds to a portion of the blood vessel 1322c. Reference symbol 1323d indicates a fourth connection region connecting two vascular regions 1301d and 1302d belonging to the fourth pair. The fourth connection region 1323d corresponds to a portion of the blood vessel 1322d.

The ophthalmic device 1000 capable of executing the processing procedures of this operational example collects data from the fundus Ef by OCT scanning using a scan pattern without flyback, generates multiple cross-sectional images corresponding to multiple cross sections, identifies multiple groups of vascular regions corresponding to the multiple cross-sectional images, and generates a vascular map by matching vascular regions corresponding to different cross sections of the same blood vessel. One advantage of the ophthalmic device 1000 is that it can quickly generate a vascular map by using a scan pattern without flyback. This makes it possible to use the vascular map in preparatory steps (e.g., Doppler angle estimation, alignment, search for blood vessels of interest, etc.) in OCT blood flow measurement (fundus blood flow dynamics measurement), thereby improving the quality of OCT blood flow measurement.

FIG. 11 shows the configuration of an ophthalmic device 1400 according to one non-limiting embodiment. Elements of the ophthalmic device 1400 that have the same names and symbols as elements of the ophthalmic device 1000 in FIG. 7 may have the same configuration and function as the corresponding elements in the ophthalmic device 1000, unless otherwise specified. However, this does not exclude the adoption of modified means, equivalent means, alternative means, etc. for the corresponding elements.

The ophthalmic device 1400 has similar elements to the ophthalmic device 1000, including a scanning unit 1010, a cross-sectional image generating unit 1020, a vascular region identifying unit 1030, a vascular region matching unit 1040, and a vascular map generating unit 1050. In addition to these, the ophthalmic device 1400 also has a scanning control unit 1060, a blood vessel designation unit 1070, a hemodynamic information generating unit 1080, a display control unit 1090, and a display device 1100.

The scan control unit 1060 is configured to control the scan unit 1010. For example, the scan control unit 1060 can control the scan unit 1010 to apply repeated scans of OCT blood flow measurement to a pre-specified blood vessel of interest in the fundus Ef. The blood vessel of interest may be designated automatically or manually. Automatic designation of the blood vessel of interest is performed, for example, by the blood vessel designation unit 1070 described below. Manual designation is performed, for example, by combining the display of an image of the fundus Ef using a user interface (the above-mentioned user interface 240) with a position designation operation on this displayed image.

The scan control unit 1060 is realized by cooperation between hardware including circuits and scan control software. In a non-limiting embodiment, the ophthalmologic apparatus 1 can realize the functions of the scan control unit 1060 using the control unit 240 (main control unit 211).

The vessel of interest designation unit 1070 is configured to analyze the vessel map 1051 generated by the vessel map generation unit 1050 and designate a vessel of interest to which OCT blood flow measurement is to be applied. As described above, the vessel map 1051 generated by the vessel map generation unit 1050 visualizes the distribution of multiple blood vessels in the fundus Ef. The vessel of interest designation unit 1070 may be configured to select a vessel of interest from among the multiple blood vessels presented in the vessel map 1051. The number of vessels of interest selected may be any number greater than or equal to one. The vessel of interest designated by the vessel of interest designation unit 1070 is treated as, for example, the vessel of interest Db shown in FIG. 5A or 5B.

The vessel of interest designation unit 1070 selects the vessel of interest based on preset criteria. These criteria are referred to as selection criteria. The selection criteria may include an index related to the direction of the vessel. Examples of such vessel direction indices include the magnitude of the Doppler angle (Doppler angle) in OCT blood flow measurement, the suitability of the Doppler angle in OCT blood flow measurement, etc.

In some embodiments, the preferred value for the Doppler angle in OCT blood flow measurement is approximately 80 degrees, and in actual measurements, the search for the blood vessel and cross section of interest is performed with a target range of 77 to 83 degrees. However, while measurements can be performed even if the Doppler angle is as small as 75 degrees, there is a problem of phase wrapping becoming more likely to occur, so it is considered desirable to set the lower limit of the target range to approximately 77 degrees. Furthermore, if the Doppler angle is as large as 85 degrees, there is a problem of a decrease in the strength of the detected Doppler signal, so it is considered desirable to set the upper limit of the target range to approximately 83 degrees. Note that this target range is a non-limiting example, and a different target range may be used.

Taking these actual circumstances regarding Doppler angles into consideration, the preferred range of Doppler angles in OCT blood flow measurement is typically set to between 77 degrees and 83 degrees. This range is referred to as the acceptable Doppler angle range. The ophthalmic device 1400 (for example, any element of the vascular map generation unit 1050, the vessel of interest designation unit 1070, and the hemodynamic information generation unit 1080) can estimate the Doppler angle of each blood vessel presented in the vascular map 1051. For details on this calculation method, please refer to the Doppler angle calculation unit 233 of the ophthalmic device 1 described above.

The vessel of interest designation unit 1070 compares the Doppler angle of each blood vessel displayed on the blood vessel map 1051 with the Doppler angle tolerance range. If the Doppler angle value of a certain blood vessel falls within the tolerance range, the vessel of interest designation unit 1070 determines that the Doppler angle of that blood vessel is good. If there are two or more blood vessels with good Doppler angles and only one blood vessel of interest is designated, the vessel of interest designation unit 1070 may be configured to select the blood vessel with the Doppler angle closest to the optimal value (typically 80 degrees). In some embodiments, each blood vessel with a good Doppler angle may be designated as a blood vessel of interest. In some embodiments, a predetermined number of blood vessels of interest may be selected from a plurality of blood vessels with good Doppler angles.

In addition to or instead of orientation information such as Doppler angle and suitability, the selection criteria may include other indices. Examples of other indices include blood vessel type (e.g., artery, vein), size (blood vessel diameter), tortuosity, and position (e.g., position relative to the optic disc). The blood vessel of interest designation unit 1070 can select a blood vessel of interest by considering two or more types of indices in stages or in parallel.

In another non-limiting example, the vessel of interest designation unit 1070 may be configured to designate a vessel selected by the user from among the multiple blood vessels presented in the vessel map 1051 as the vessel of interest. In this example, the ophthalmic device 1400 (display control unit 1090 and display device 1100) displays the vessel map 1051 (a visualized image of the vessel map 1051). The user can select a vessel of interest by referring to the displayed vessel map 1051. The operation of inputting the selected vessel of interest is performed using a user interface (e.g., the user interface 240 of the ophthalmic device 1) not shown.

The vessel of interest designation unit 1070 is realized by the cooperation of hardware including circuitry and software for designating the vessel of interest. The non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the vessel of interest designation unit 1070 using the data processing unit 230.

The hemodynamic information generation unit 1080 is configured to generate hemodynamic information for the blood vessel of interest designated by the blood vessel of interest designation unit 1070 based on data collected by the scanning unit 1010 when the scanning unit 1010 applies a scan for OCT blood flow measurement to the fundus Ef.

The hemodynamic information generation unit 1080 may have a configuration similar to that of the data processing unit 230 of the ophthalmologic apparatus 1. Specifically, the hemodynamic information generation unit 1080 may include the image generation unit 220, vascular region identification unit 231, and hemodynamic information generation unit 232 shown in FIG. 4.

In this embodiment, the scan control unit 1060 controls the scan unit 1010 to apply repeated scans for hemodynamic measurement to the blood vessel of interest designated by the blood vessel of interest designation unit 1070. As shown in Figures 5A to 6B, the repeated scans are applied to a specific cross section (cross section of interest) of the blood vessel of interest. In this embodiment, the cross section of interest may be set at any position in the blood vessel displayed on the blood vessel map 1051.

As a non-limiting example, when the blood vessel 1312a presented in the blood vessel map 1310 in FIG. 10B is designated as the blood vessel of interest, the scan control unit 1060 sets a cross section at an arbitrary position in the first connection region 1313a. For example, the cross section of interest may be set at a position equidistant from the two circular patterns 1201 and 1202 in the first connection region 1313a (i.e., a position midway between the two blood vessel regions 1301a and 1302a connected by the first connection region 1313a). This cross section of interest corresponds to the cross section of interest C0 shown in FIGS. 5A and 6A, and the two blood vessel regions 1301a and 1302a correspond to the two supplementary cross sections C1 and C2 (two supplementary cross section images G1 and G2).

The data collected by the scanning unit 1010 through repeated scans of the cross section of interest of the blood vessel of interest is referred to as OCT blood flow measurement data 1075. The blood flow dynamics information generating unit 1080 generates blood flow dynamics information 1085 of the blood vessel of interest designated by the blood vessel of interest designating unit 1070 based on the OCT blood flow measurement data 1075.

The hemodynamic information generation unit 1080 is realized by the cooperation of hardware including circuits and hemodynamic information generation software. The ophthalmologic apparatus 1 in a non-limiting embodiment can realize the functions of the hemodynamic information generation unit 1080 using the data processing unit 230.

The display device 1100 is any type of display. The display device 1100 may be the display unit 241 of the ophthalmic device 1, for example, the display device 3. The display device 1100 of this embodiment is a component of the ophthalmic device 1400. In another embodiment, the display device may be a peripheral device (external device) of the ophthalmic device.

The display control unit 1090 is configured to control the display device 1100 to display information. The display control unit 1090 is realized by cooperation between hardware including circuits and display control software. A non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the display control unit 1090 using the control unit 240 (main control unit 211).

The display control unit 1090 causes the display device 1100 to display information generated by the ophthalmic device 1400. Examples of information generated by the ophthalmic device 1400 include an image of the subject's eye E, information on the direction of blood vessels in the fundus Ef (Doppler angle, evaluation information, etc.), a blood vessel map, and information obtained by processing any of these (correction, analysis, evaluation, etc.). In addition, the display device 1100 causes the display device 1100 to display information (e.g., images) acquired by the ophthalmic device 1400 from outside.

Evaluation information, which is a non-limiting example of the blood vessel orientation information described above, will now be described. Evaluation information is information obtained by evaluating the Doppler angle of hemodynamic measurement. The hemodynamic information generation unit 1080 obtains information indicating the magnitude of the Doppler angle (Doppler angle information) using the method described above. Furthermore, the hemodynamic information generation unit 1080 applies a predetermined evaluation process to this Doppler angle information. This evaluation process, for example, evaluates the suitability of the magnitude of the Doppler angle in OCT blood flow measurement.

As mentioned above, the preferred range (target range) of the Doppler angle in OCT blood flow measurement may be set between 77 degrees and 83 degrees, with the most preferred value being set at approximately 80 degrees. In the evaluation process, the hemodynamic information generation unit 1080 compares the Doppler angle value of the target blood vessel with the target range. If the Doppler angle value falls within the target range, the hemodynamic information generation unit 1080 determines that the Doppler angle of the blood vessel is preferred and generates evaluation information indicating this determination result. On the other hand, if the Doppler angle of the blood vessel does not fall within the target range, the hemodynamic information generation unit 1080 generates evaluation information indicating that the Doppler angle of the blood vessel is not preferred. In some embodiments, the target range may be divided into multiple sections to allow for more detailed evaluation of cases where the Doppler angle is preferred. Furthermore, the range outside the target range may be divided into multiple sections to allow for more detailed evaluation of cases where the Doppler angle is not preferred.

If the ophthalmic device 1400 of this embodiment has the function of photographing the fundus from the front (for example, a function realized by a front photographing unit (not shown) corresponding to the fundus camera unit 2 of the ophthalmic device 1), and/or the function of externally receiving a front fundus image generated by photographing the fundus Ef from the front (for example, a front image receiving unit (not shown) corresponding to the data input/output unit 290 of the ophthalmic device 1), the display control unit 1090 can display the front fundus image and the vascular map 1051 on the display device 1100. For example, the display control unit 1090 can display the front fundus image on the display device 1100, and can also display the vascular map 1051 (an image obtained by visualizing this) on the front fundus image.

When displaying the vascular map 1051 on a frontal fundus image, it is necessary to perform alignment (registration) between the frontal fundus image and the vascular map 1051. This registration may be performed, for example, by a registration unit (not shown) included in the hemodynamic information generation unit 1080 or the display control unit 1090. The registration unit is realized by cooperation between hardware including a circuit and registration software. A non-limiting aspect of the ophthalmologic apparatus 1 can perform registration between the frontal fundus image and the vascular map 1051 using a registration function realized using the data processing unit 230. Some non-limiting examples of this registration are described below.

In a first non-limiting example, the registration unit is configured to perform registration between the vascular map 1051 and the frontal fundus image using the blood vessels displayed in the vascular map 1051 as landmarks. Each blood vessel displayed in the vascular map 1051 is located in the area between the circular pattern 1201 and the circular pattern 1202, and the two circular patterns 1201 and 1202 are centered on the optic disc center 1200a and have predetermined radii R1 and R2, respectively. By using this information, it is possible to limit the range for searching for portions in the frontal fundus image corresponding to the landmarks. If the vascular map 1051 is three-dimensional data such as the vascular map 1320 in FIG. 10C, projection may be applied to the vascular map 1051 to generate two-dimensional data (a frontal image such as the vascular map 1310 in FIG. 10B), and registration may be performed between this two-dimensional data and the frontal fundus image.

In a second non-limiting example, the registration unit is configured to perform registration between the vascular map 1051 and the frontal fundus image using both ends of each of the multiple blood vessels displayed on the vascular map 1051 as multiple landmarks. The both ends of each blood vessel displayed on the vascular map 1051 are a first end located on the circular pattern 1201 and a second end located on the circular pattern 1202. In this example, as in the first example, the search range can be limited. The processing procedure when the vascular map 1051 is three-dimensional data may also be the same as in the first example.

In the first and second examples described above, registration is performed using objects in the vascular map 1051 as landmarks. In contrast, a non-limiting third example uses at least one cross-sectional image from the multiple cross-sectional images used to generate the vascular map 1051. The registration unit in this example generates a circular image by applying projection to the cross-sectional image. The cross-sectional image is an OCT intensity image, in which blood vessels are depicted at low brightness. Even in a circular image generated as a projection of such a cross-sectional image, the brightness of pixels corresponding to blood vessels (vascular pixels) is lower than the brightness of pixels corresponding to other tissues. By using such multiple blood vessel pixels as multiple landmarks, registration can be performed between the circular image and the frontal fundus image. Using the results of this registration, registration can be performed between the cross-sectional image, which is the original image of the circular image, and the frontal fundus image. Furthermore, registration can be performed between the vascular map 1051 generated from this cross-sectional image and the frontal fundus image.

As described above, the ophthalmic device 1400 of this embodiment (e.g., any of the elements of the vascular map generation unit 1050, the vessel of interest designation unit 1070, and the hemodynamic information generation unit 1080) can estimate the Doppler angle of each blood vessel presented in the vascular map 1051. Furthermore, the ophthalmic device 1400 can generate a Doppler angle map by associating the position information of each blood vessel in the vascular map 1051 with the estimated Doppler angle. Furthermore, the ophthalmic device 1400 can generate evaluation information by applying an evaluation process to the estimated Doppler angle of each blood vessel in the vascular map 1051, and generate a Doppler angle evaluation map by associating the position information of each blood vessel with the evaluation information. Doppler angle maps and Doppler angle evaluation maps contain information indicating the distribution of blood vessel orientation. By visualizing such maps, visual information (orientation distribution image) representing the distribution of blood vessel orientation can be generated. The display control unit 1090 can display the orientation distribution image on the display device 1100. The display control unit 1090 may also display the orientation distribution image on the frontal fundus image. Registration between the frontal fundus image and the orientation distribution image may be performed by the registration unit described above.

A non-limiting example of the operation of the ophthalmic device 1400 will now be described. Figure 12 shows one example of the operation of the ophthalmic device 1400. Steps S11 to S15 may be performed in the same manner as steps S1 to S5 in Figure 9, respectively.

In step S16, the vessel of interest designation unit 1070 generates orientation information (Doppler angle, suitability, etc.) for each blood vessel presented in the vessel map 1051 generated in step S15.

In step S17, the vessel of interest designation unit 1070 designates a vessel of interest from among the multiple blood vessels presented in the vessel map 1051, based on the orientation information of each blood vessel generated in step S16. Note that in addition to or instead of the orientation information, the vessel of interest may be designated with reference to other selection criteria. Information on the designated vessel of interest is sent to the scan control unit 1060.

In step S18, the scan control unit 1060 controls the scan unit 1010 to apply repeated scans for hemodynamic measurement (OCT blood flow measurement) to the blood vessel of interest designated in step S17.

The blood vessels in the fundus Ef corresponding to the specified blood vessels of interest are searched for and identified, for example, by referring to an infrared observation image (real-time moving image) of the fundus Ef. At this time, alignment between the infrared observation image and the blood vessel map 1051 may be performed using a process similar to the registration described above.

In step S18, the scan control unit 1060 may control the scan unit 1010 to perform a repetitive scan (the aforementioned main scan) on the blood vessel of interest, as well as to perform a scan (the aforementioned supplementary scan) to newly determine the Doppler angle. The OCT blood flow measurement data 1075 collected by the repetitive scan (and the data collected by the supplementary scan) is sent to the hemodynamic information generation unit 1080.

In step S19, the hemodynamic information generation unit 1080 generates hemodynamic information 1085 for the blood vessel of interest designated by the blood vessel of interest designation unit 1070 based on the OCT blood flow measurement data 1075 collected by the repeated scan in step S17 (and data collected by the supplementary scan).

In some embodiments, the hemodynamic information generation unit 1080 calculates the blood flow velocity in the blood vessel of interest based on the OCT blood flow measurement data 1075 collected from the blood vessel of interest in step S17 and the orientation information (Doppler angle) of the blood vessel of interest calculated in step S16.

In some other aspects, the blood flow dynamics information generation unit 1080 calculates the Doppler angle of the blood vessel of interest based on the data collected in the supplementary scan of step S17, and calculates the blood flow velocity in the blood vessel of interest based on this Doppler angle and the OCT blood flow measurement data 1075 collected in the main scan of step S17.

Furthermore, the hemodynamic information generation unit 1080 may perform a process of calculating the vascular diameter of the blood vessel of interest and a process of calculating the blood flow volume based on this vascular diameter and the blood flow velocity.

In step S20, the display control unit 1090 causes the display device 1100 to display the hemodynamic information (blood flow velocity, blood flow volume, blood vessel diameter, Doppler angle, etc.) generated in step S19. The display control unit 1090 may also cause the display device 1100 to display any information obtained in this operation example (images, calculation results, analysis results, etc.). For example, the hemodynamic information generation unit 1080 may apply evaluation processing to the Doppler angle to generate evaluation information, and the display control unit 1090 may then cause the display device 1100 to display this evaluation information.

The ophthalmic device 1400 according to this embodiment has the functions and advantages described below in addition to the functions and advantages of the ophthalmic device 1000.

The ophthalmic device 1400 is capable of measuring the hemodynamics of the fundus. Furthermore, the ophthalmic device 1400 can automatically designate a blood vessel of interest based on a vascular map, or can assist in the task of designating a blood vessel of interest based on a vascular map. In addition, the ophthalmic device 1400 can automatically perform hemodynamic measurements of a designated blood vessel of interest using a vascular map. This facilitates and reduces the labor required to designate the position at which to apply hemodynamic measurements, and improves the precision and accuracy of this task. Therefore, the ophthalmic device 1400 of this embodiment facilitates easier, more labor-saving, and faster examinations, contributing to improved examination quality.

The ophthalmic device 1400 provides a novel method of generating orientation information for fundus blood vessels by obtaining information on the course of blood vessels from images obtained by fundus imaging. The orientation information generated by the ophthalmic device 1400 contributes to simplification and labor savings in the task of specifying blood flow measurement positions, and contributes to improved precision and accuracy of the task. Furthermore, the orientation information generated by the ophthalmic device 1400 provides the magnitude of the Doppler angle and its evaluation results, making it possible to predict the optimal blood flow measurement position.

The ophthalmologic device 1400 can provide visual information showing various types of information, such as vascular maps, fundus images, Doppler angles, and evaluation information. This allows the user to understand information about the subject's eye (fundus).

Figure 13 shows the configuration of an ophthalmic device 1500 according to one non-limiting embodiment. Elements of the ophthalmic device 1500 that have the same names and symbols as elements of the ophthalmic device 1400 in Figure 11 may have the same configuration and function as the corresponding elements of the ophthalmic device 1400, unless otherwise specified. However, this does not exclude the use of modified, equivalent, or alternative means for the corresponding elements.

The ophthalmic device 1500 has the same elements as the ophthalmic device 1400: a scanning unit 1010, a cross-sectional image generating unit 1020, a vascular region identifying unit 1030, a vascular region matching unit 1040, a vascular map generating unit 1050, a scan control unit 1060, and a blood flow dynamics information generating unit 1080. In addition to these, the ophthalmic device 1500 also has an observation image generating unit 1110, a movement control unit 1120, and a movement mechanism 1130.

The observation image generation unit 1110 is configured to generate an infrared observation image (real-time moving image) of the fundus oculi Ef. A non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the observation image generation unit 1110 using the fundus camera unit 2.

The movement mechanism 1130 is configured to move the scanning unit 1010. In a non-limiting embodiment, the ophthalmologic apparatus 1 can achieve the functions of the movement mechanism 1130 using the movement mechanism 150.

The movement control unit 1120 is configured to control the movement mechanism 1130. The movement control unit 1120 is realized by cooperation between hardware including circuits and movement control software. A non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the movement control unit 1120 using the control unit 210 (main control unit 211) and the data processing unit 230.

The vascular map 1051 generated by the vascular map generation unit 1050 is input to the movement control unit 1120. Furthermore, the infrared observation image generated by the observation image generation unit 1110 is input to the movement control unit 1120 in real time. The movement control unit 1120 compares the vascular map 1051 with the infrared observation image (a frame of a real-time moving image), calculates the deviation between the vascular map 1051 and the infrared observation image, and controls the movement mechanism 1130 based on this deviation. Calculation of the deviation between the vascular map 1051 and the infrared observation image may be performed, for example, using a method similar to the registration described above. The movement control unit 1120 controls the movement mechanism 1130 so as to cancel out the calculated deviation. Specifically, the movement control unit 1120 calculates the deviation of each frame of the infrared observation image (or each frame obtained through thinning processing) relative to the vascular map 1051, and compares each sequentially calculated deviation with a predetermined threshold. The movement control unit 1120 repeats this series of processes until the deviation becomes smaller than the threshold value. This achieves alignment of the infrared observation image with the vascular map 1051, and realizes new alignment using the vascular map 1051. Note that in parallel with the series of processes described here, alignment may be performed using the vascular map 1051, which is updated in real time, and the infrared observation image (real-time moving image), by repeatedly performing OCT scanning and data processing to generate the vascular map 1051.

A non-limiting example of the operation of the ophthalmic device 1500 will now be described. Figure 14 shows one example of the operation of the ophthalmic device 1500. Steps S31 to S35 may be performed in the same manner as steps S1 to S5 in Figure 9, respectively.

In step S36, the ophthalmic device 1500 starts alignment. Specifically, the ophthalmic device 1500 starts generating an infrared observation image of the fundus oculi Ef using the observation image generation unit 1110, and starts operation of the movement control unit 1120 and the movement mechanism 1130.

In step S37, the movement control unit 1120 calculates the deviation of the infrared observation image relative to the vascular map 1051 generated in step S35 and compares the calculated deviation with a threshold value. This process is repeated until the deviation becomes smaller than the threshold value (step S38: No). When the deviation of the infrared observation image relative to the vascular map 1051 becomes smaller than the threshold value (step S38: Yes), the processing procedure proceeds to step S39.

In step S39, the scan control unit 1060 controls the scan unit 1010 to apply repeated scans for hemodynamic measurement (OCT blood flow measurement) to the blood vessels of interest in the fundus oculi Ef. The blood vessels of interest may be designated in the same manner as in the ophthalmic apparatus 1400 (blood vessel designation unit 1070) described above.

In step S40, the hemodynamic information generation unit 1080 generates hemodynamic information for the blood vessel of interest based on the OCT blood flow measurement data 1075 collected by the repeated scan in step S39.

In addition to the functions and effects of the ophthalmic device 1400, the ophthalmic device 1500 according to this embodiment can provide a novel alignment method that utilizes a vascular map that indicates the position of fundus blood vessels obtained from OCT images.

Figure 15 shows the configuration of an ophthalmic device 1600 according to one non-limiting embodiment. Elements of the ophthalmic device 1600 that have the same names and are assigned the same reference numerals as elements of the ophthalmic device 1400 in Figure 11 may have the same configuration and function as the corresponding elements of the ophthalmic device 1400, unless otherwise specified. However, this does not exclude the adoption of modified, equivalent, or alternative means for the corresponding elements.

The ophthalmic device 1600 has the same elements as the ophthalmic device 1400, including a scanning unit 1010, a cross-sectional image generating unit 1020, a vascular region identifying unit 1030, a vascular region matching unit 1040, a vascular map generating unit 1050, a scan control unit 1060, and a blood flow dynamics information generating unit 1080. In addition to these, the ophthalmic device 1500 has a movement mechanism 1130, a movement control unit 1140, and a projection image generating unit 1150. The movement mechanism 1130 has the same configuration and functions as the movement mechanism 1130 of the ophthalmic device 1500 in FIG. 13.

In this example, the vascular map 1051 is three-dimensional data such as the vascular map 1320 in Figure 10C. The projection image generation unit 1150 generates a projection image by applying a projection in the A-scan direction (z direction) of an OCT scan of the fundus Ef to the vascular map 1051. This projection of the vascular map 1051 is not limited to a projection onto the vascular map 1051, but may also be a projection onto multiple cross-sectional images 1021, which are the original images of the vascular map 1051.

If the vascular map 1051 is two-dimensional data such as the vascular map 1310 in Figure 10B, there is no need to provide a projection image generation unit 1150. Alternatively, a projection image generation unit 1150 may be provided that is configured to operate when the vascular map 1051 is three-dimensional data and not operate when the vascular map 1051 is two-dimensional data.

The projection image generation unit 1150 is realized by the cooperation of hardware including circuits and projection image generation software. The ophthalmologic apparatus 1 in a non-limiting embodiment can realize the functions of the projection image generation unit 1150 using the data processing unit 230.

The movement control unit 1140 is configured to control the movement mechanism 1130. The movement control unit 1120 is realized by cooperation between hardware including circuits and movement control software. A non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the movement control unit 1120 using the control unit 210 (main control unit 211) and the data processing unit 230.

The projection image generated from the vascular map 1051 by the projection image generation unit 1150 is input to the movement control unit 1140. In this embodiment, the vascular map 1051 is repeatedly generated, and a projection image is generated from each vascular map 1051 (or each vascular map 1051 obtained through thinning processing).

A non-limiting example of the operation of the ophthalmic device 1600 will now be described. Figure 16 shows one example of the operation of the ophthalmic device 1600. Steps S51 to S55 may be executed in the same manner as steps S1 to S5 in Figure 9, respectively. Steps S51 to S55 are executed repeatedly. As a result, a blood vessel map 1051 is generated sequentially. The time interval for generating the blood vessel map 1051, i.e., the time interval for applying a scan to the fundus Ef, may be constant. The blood vessel map 1051 generated sequentially is input sequentially to the projection image generation unit 1150.

In step S56, the projection image generation unit 1150 applies projection to the vascular map 1051 that is sequentially input to generate a projection image. The projection images that are sequentially generated in response to the input of the vascular map 1051 are sequentially input to the movement control unit 1140.

In step S57, the movement control unit 1140 compares the two input projection images, calculates the deviation between these projection images, and compares the calculated deviation with a threshold value. This process is repeated until the deviation becomes smaller than the threshold value (step S58: No). When the deviation becomes smaller than the threshold value (step S58: Yes), the processing procedure proceeds to step S59. The deviation becoming smaller than the threshold value means that the movement of the subject's eye E is sufficiently small and the position of the subject's eye E is stable.

The processing of step S57 includes, for example, a step of detecting a connection area corresponding to a blood vessel from two consecutive projection images, a step of using the detected connection area as a landmark to calculate the positional error between the two projection images, and a step of comparing this positional error (deviation) with a threshold value.

In addition to evaluating the deviation between projection images, alignment evaluation may be performed based on the distribution of landmarks in a single projection image. For example, the positions of feature points of the fundus oculi Ef can be estimated based on the distribution of landmarks in a single projection image. The scan in step S51 is a circle scan centered on the optic optic nerve center, and the landmarks in a single projection image are arranged on a circle. Therefore, the center of the circle formed by connecting these landmarks corresponds to the optic optic nerve center. The movement control unit 1140 can control the movement mechanism 1130 so that the center of the circle detected in this manner is positioned at the center position of the projection image. More generally, the movement control unit 1140 can control the movement mechanism 1130 so that the center of the circle detected is positioned at a predetermined position in the projection image.

In step S59, the scan control unit 1060 controls the scan unit 1010 to apply repeated scans for hemodynamic measurement (OCT blood flow measurement) to the blood vessels of interest in the fundus oculi Ef. The blood vessels of interest may be designated in the same manner as in the ophthalmic apparatus 1400 (blood vessel designation unit 1070) described above.

In step S60, the hemodynamic information generation unit 1080 generates hemodynamic information for the blood vessel of interest based on the OCT blood flow measurement data 1075 collected by the repeated scan in step S59.

In addition to the functions and effects of the ophthalmic device 1400, the ophthalmic device 1600 according to this embodiment can provide a novel alignment method that utilizes a vascular map that indicates the position of fundus blood vessels obtained from OCT images.

FIG. 17 shows the configuration of an ophthalmic device 2000 according to one non-limiting embodiment. The ophthalmic device 2000 includes a scanning unit 2010, a three-dimensional image generating unit 2020, a cross-sectional image extracting unit 2030, a vascular region identifying unit 2040, a vascular region matching unit 2050, and a vascular map generating unit 2060.

Any of the matters described or suggested in this disclosure, such as the matters relating to the ophthalmic device 1000 in FIG. 7, the matters relating to the ophthalmic device 1400 in FIG. 11, the matters relating to the ophthalmic device 1500 in FIG. 13, and the matters relating to the ophthalmic device 1400 in FIG. 15, can be combined with the ophthalmic device 2000 of this embodiment.

The scanning unit 2010, like the scanning unit 1010 of the ophthalmic apparatus 1000 described above, is configured to collect data by applying an OCT scan to the fundus Ef of the subject's eye E. In particular, the scanning unit 2010 collects data by applying an OCT scan to a three-dimensional region of the fundus Ef. Non-limiting examples of this OCT scan include a raster scan and a Lissajous scan. A non-limiting aspect of the ophthalmic apparatus 1 can realize the functions of the scanning unit 2010 using the fundus camera unit 2 and the OCT unit 100.

The three-dimensional image generating unit 2020 is configured to generate a three-dimensional image of the fundus oculi Ef based on data collected from a three-dimensional region of the fundus oculi Ef by the scanning unit 2010. The generated three-dimensional image may be, for example, stack data or volume data. The three-dimensional image generating unit 2020 is realized by cooperation between hardware including circuits and three-dimensional image generating software. A non-limiting aspect of the ophthalmologic apparatus 1 can realize the functions of the three-dimensional image generating unit 2020 using the data processing unit 230 (image generating unit 220).

The cross-sectional image extraction unit 2030 extracts cross-sectional images from the three-dimensional image generated by the three-dimensional image generation unit 2020. In particular, the cross-sectional image extraction unit 2030 extracts multiple cross-sectional images corresponding to multiple cross sections of the fundus oculi Ef from the three-dimensional image. The multiple cross sections correspond to a scan pattern without a flyback. The scan pattern without a flyback may be, for example, any of the scan patterns described above regarding the scan unit 1010 of the ophthalmic device 1000, such as the concentric circular scan shown in Figures 8A to 8C. The cross-sectional image extraction unit 2030 is realized by cooperation between hardware including circuits and cross-sectional image extraction software. A non-limiting aspect of the ophthalmic device 1 can realize the functions of the cross-sectional image extraction unit 2030 using the data processing unit 230.

The vascular region identification unit 2040 is configured to detect vascular region groups from each of the multiple cross-sectional images extracted from the three-dimensional image by the cross-sectional image extraction unit 2030, and thereby identify multiple vascular region groups corresponding to these multiple cross-sectional images. The vascular region identification unit 2040 has the same functions as the vascular region identification unit 1030 of the ophthalmic device 1000 described above. The vascular region identification unit 2040 is realized by cooperation between hardware including circuits and vascular region identification software. A non-limiting aspect of the ophthalmic device 1 can realize the functions of the vascular region identification unit 2040 using the data processing unit 230 (vascular region identification unit 231).

The vascular region matching unit 2050 is configured to match vascular regions corresponding to different cross sections of the same blood vessel among multiple vascular region groups identified from multiple cross-sectional images by the vascular region identification unit 2040. The vascular region matching unit 2050 has the same functions as the vascular region matching unit 1040 of the ophthalmic device 1000 described above. The vascular region matching unit 2050 is realized by cooperation between hardware including circuits and vascular region matching software. A non-limiting aspect of the ophthalmic device 1 can achieve the functions of the vascular region matching unit 2050 using the data processing unit 230.

The vascular map generation unit 2060 is configured to generate a vascular map showing the distribution of blood vessels based on the vascular region matching results obtained by the vascular region matching unit 2050. The vascular map generation unit 2060 has the same functions as the vascular map generation unit 1050 of the ophthalmic device 1000 described above. The vascular map generation unit 2060 is realized by cooperation between hardware including circuits and vascular map generation software. The ophthalmic device 1 of a non-limiting aspect can realize the functions of the vascular map generation unit 2060 using the data processing unit 230.

Figure 18 shows an example of the operation of the ophthalmic device 2000.

First, in step S71, the scanning unit 2010 applies OCT scanning to a three-dimensional region of the fundus Ef of the subject's eye E to collect data. The collected data is sent to the three-dimensional image generating unit 2020.

In step S72, the three-dimensional image generation unit 2020 generates a three-dimensional image of the fundus oculi Ef based on the data collected from the three-dimensional region of the fundus oculi Ef in step S71. The generated three-dimensional image is sent to the cross-sectional image extraction unit 2030.

In step S73, the cross-sectional image extraction unit 2030 extracts, from the three-dimensional image generated in step S72, a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus oculi Ef corresponding to a scan pattern without flyback. For example, the cross-sectional image extraction unit 2030 extracts, from the three-dimensional image generated in step S72, two cross-sectional images corresponding to two concentric circle scans (concentric circle scans). The extracted cross-sectional images are sent to the vascular region identification unit 2040.

In step S74, the vascular region identification unit 2040 detects vascular region groups from each of the multiple cross-sectional images extracted from the 3D image in step S73. This identifies multiple vascular region groups corresponding to each of the multiple cross-sectional images. The identified multiple vascular region groups are sent to the vascular region association unit 2050.

In step S75, the vascular region matching unit 2050 matches vascular regions corresponding to different cross sections of the same blood vessel among the multiple vascular region groups identified in step S74. The results of this vascular region matching process are sent to the vascular region matching unit 2050.

In step S76, the vascular map generation unit 2060 generates a vascular map based on the vascular region matching results obtained in step S75.

The ophthalmic device 2000 capable of executing the processing procedures of this operational example generates a 3D OCT image of the fundus of the subject's eye, extracts from the 3D OCT image multiple cross-sectional images corresponding to multiple cross sections corresponding to a scan pattern without flyback, identifies multiple groups of vascular regions corresponding to the multiple cross-sectional images, and generates a vascular map by associating vascular regions corresponding to different cross sections of the same blood vessel. This vascular map can be used in preparatory steps (e.g., Doppler angle estimation, alignment, search for blood vessels of interest, etc.) in OCT blood flow measurement (fundus blood flow dynamics measurement). Therefore, the ophthalmic device 2000 of this embodiment contributes to improving the quality of OCT blood flow measurement.

As mentioned above, various features can be combined with the ophthalmic device 2000 of this embodiment. In particular, the features related to the ophthalmic device 1000 in FIG. 7, the features related to the ophthalmic device 1400 in FIG. 11, the features related to the ophthalmic device 1500 in FIG. 13, and the features related to the ophthalmic device 1400 in FIG. 15 can be combined with the ophthalmic device 2000. An ophthalmic device obtained by such a combination exhibits the functions and effects of the combined features, and further exhibits synergistic functions and effects between the combined features and the ophthalmic device 2000. Furthermore, an ophthalmic device obtained by combining multiple features with the ophthalmic device 2000 exhibits synergistic functions and effects between two or more of the multiple features, and synergistic functions and effects between two or more of the multiple features and the ophthalmic treatment 2000. Those skilled in the art will be able to understand these functions and effects from this disclosure.

Other Embodiments
It will be understood by those skilled in the art that the present disclosure also provides embodiments in categories other than ophthalmic devices. For example, the present disclosure may provide an embodiment of a method for controlling an ophthalmic device, an embodiment of a method for controlling an ophthalmic information processing device, an embodiment of a program for causing a computer to execute each step of any of the methods, and an embodiment of a computer-readable non-transitory recording medium on which any of the programs is recorded. The recording medium may take any form. For example, the recording medium may be any of a magnetic disk, an optical disk, a magneto-optical disk, and a semiconductor memory.

Some embodiments are methods for controlling an ophthalmic device having a scanning unit and a processor that performs OCT scans. The method according to this embodiment causes the processor to perform scan control, cross-sectional image generation processing, vascular region identification processing, vascular region correspondence processing, and vascular map generation processing. The scan control controls the scanning unit to collect data by applying an OCT scan using a scan pattern that does not involve flyback to the fundus of the subject's eye. The cross-sectional image generation processing generates multiple cross-sectional images corresponding to multiple cross sections of the fundus based on data collected from the fundus under scan control. The vascular region identification processing identifies multiple vascular region groups corresponding to the multiple cross-sectional images by detecting vascular region groups from each of the multiple cross-sectional images generated. The vascular region correspondence processing associates vascular regions corresponding to different cross sections of the same blood vessel among multiple vascular region groups corresponding to the multiple cross sections. The vascular map generation processing generates a vascular map showing the distribution of blood vessels based on the results of the vascular region correspondence processing. The method according to this embodiment enables the ophthalmic device to perform the processing steps shown in FIG. 9 described above.

It is possible to create a program that causes an ophthalmic device including a computer to execute the method according to this embodiment. It is also possible to create a computer-readable non-transitory recording medium on which such a program is recorded. This non-transitory recording medium may be in any form, including, for example, a magnetic disk, optical disk, magneto-optical disk, and semiconductor memory. Any of the features described in this disclosure may be combined with the method, program, and recording medium according to this embodiment.

Some embodiments are methods for controlling an ophthalmic device having a scanning unit and a processor that performs OCT scanning. The method of this embodiment causes the processor to perform scan control, 3D image generation processing, cross-sectional image extraction processing, vascular region identification processing, vascular region correspondence processing, and vascular map generation processing. The scan control controls the scanning unit to apply an OCT scan to a 3D region of the fundus of the subject's eye to collect data. The 3D image generation processing generates a 3D image of the fundus based on data collected from the 3D region of the fundus under the scan control. The cross-sectional image extraction processing extracts, from the 3D image generated by the 3D image generation processing, multiple cross-sectional images corresponding to multiple cross sections of the fundus corresponding to a scan pattern without flyback. The vascular region identification processing detects vascular region groups from each of the multiple cross-sectional images extracted from the 3D image, thereby identifying multiple vascular region groups corresponding to these multiple cross-sectional images. The vascular region correspondence processing associates vascular regions corresponding to different cross sections of the same blood vessel among multiple vascular region groups corresponding to multiple cross sections. The vascular map generation process generates a vascular map showing the distribution of blood vessels based on the results of the vascular region association process. The method according to this embodiment enables the ophthalmologic apparatus to execute the process steps shown in FIG. 18 described above.

It is possible to create a program that causes an ophthalmic device including a computer to execute the method according to this embodiment. It is also possible to create a computer-readable non-transitory recording medium on which such a program is recorded. Any of the features described in this disclosure can be combined with the method, program, and recording medium according to this embodiment.

Several embodiments of the present disclosure have been described above with reference to the drawings. However, these are non-limiting examples, and various configurations other than those described above may also be adopted.

Furthermore, in the multiple flowcharts used in the above explanation, multiple steps (processes) are described in order. However, the order in which the steps are performed in each embodiment is not limited to the order described. In each embodiment, the order of the steps shown in the figures can be changed to the extent that the content is not affected. Furthermore, the above embodiments can be at least partially combined to the extent that the content is not contradictory.

Some or all of the above embodiments may also be described as follows. However, embodiments of the present disclosure are not limited to the following notes.

[1] a scanning unit that applies an optical coherence tomography scan using a scan pattern without flyback to the fundus of the subject's eye to collect data;
a cross-sectional image generating unit that generates a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus based on the data collected by the scanning unit;
a vascular region specifying unit that specifies a plurality of vascular region groups corresponding to the plurality of cross-sectional images by detecting a vascular region group from each of the plurality of cross-sectional images;
a vascular region associating unit that associates vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a blood vessel map generating unit that generates a blood vessel map indicating the distribution of blood vessels based on a result of the association.

[2] The scan pattern includes a plurality of patterns each of which does not involve a flyback.
The ophthalmic device according to item 1 above.

[3] The scan pattern includes a concentric pattern that is a combination of the plurality of patterns arranged concentrically,
the plurality of cross sections of the fundus include a plurality of concentric cross sections respectively corresponding to the plurality of patterns;
the scanning unit applies an optical coherence tomography scan using the concentric pattern to the fundus to collect data;
the cross-sectional image generation unit generates the plurality of cross-sectional images corresponding to the plurality of concentric cross sections, respectively, based on the data collected by the optical coherence tomography scan using the concentric pattern;
The ophthalmic device mentioned above.

[4] The concentric pattern includes a concentric circular pattern that is a combination of a plurality of circular patterns arranged concentrically,
the plurality of concentric cross sections include a plurality of cylindrical side surfaces that are concentrically arranged and correspond to the plurality of circular patterns, respectively;
the scanning unit applies an optical coherence tomography scan using the concentric circle pattern to the fundus to collect data;
the cross-sectional image generating unit generates the plurality of cross-sectional images corresponding to the plurality of cylindrical side surfaces, respectively, based on the data collected by the optical coherence tomography scan using the concentric circle pattern.
The ophthalmic device mentioned above.

[5] a scanning unit that applies optical coherence tomography scanning to a three-dimensional region of the fundus of the subject's eye to collect data;
a three-dimensional image generating unit that generates a three-dimensional image of the fundus based on the data collected by the scanning unit;
a cross-sectional image extracting unit that extracts, from the three-dimensional image, a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus, the cross-sectional images corresponding to a scan pattern without a flyback;
a vascular region specifying unit that specifies a plurality of vascular region groups corresponding to the plurality of cross-sectional images by detecting a vascular region group from each of the plurality of cross-sectional images;
a vascular region associating unit that associates vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a blood vessel map generating unit that generates a blood vessel map indicating the distribution of blood vessels based on a result of the association.

[6] The scan pattern includes a plurality of patterns each of which does not involve a flyback.
The ophthalmic devices listed above.

[7] The scan pattern includes a concentric pattern that is a combination of the plurality of patterns arranged concentrically,
the plurality of cross sections of the fundus include a plurality of concentric cross sections respectively corresponding to the plurality of patterns;
the cross-sectional image extraction unit extracts the plurality of cross-sectional images corresponding to the plurality of concentric cross sections from the three-dimensional image;
The ophthalmic devices listed above.

[8] The concentric pattern includes a concentric circular pattern that is a combination of a plurality of circular patterns arranged concentrically,
the plurality of concentric cross sections include a plurality of cylindrical side surfaces that are concentrically arranged and correspond to the plurality of circular patterns, respectively;
the cross-sectional image extraction unit extracts the plurality of cross-sectional images corresponding to the plurality of cylinder side surfaces, respectively, from the three-dimensional image;
The ophthalmic devices listed above are number 7.

[9] The vascular region specifying unit
generating a plurality of projection images corresponding to the plurality of cross-sectional images by applying a projection of the optical coherence tomography scan in an A-scan direction to each of the plurality of cross-sectional images;
for each of the plurality of projection images, detecting a blood vessel region group from a corresponding cross-sectional image based on a luminance distribution in the projection image;
Any one of the ophthalmic devices 1 to 8 above.

[10] A scan control unit that controls the scanning unit so as to apply repeated scans to a pre-specified blood vessel of interest in the fundus;
and a hemodynamic information generating unit that generates hemodynamic information in the blood vessel of interest based on data collected by the repeated scans.
Any one of the ophthalmic devices 1 to 9 above.

[11] Further comprising a blood vessel of interest designation unit that analyzes the blood vessel map and designates the blood vessel of interest.
The above 10 ophthalmic devices.

[12] The plurality of cross-sectional images include a first cross-sectional image and a second cross-sectional image,
The vascular region specifying unit
detecting a first blood vessel region from the first cross-sectional image;
detecting a second blood vessel region from the second cross-sectional image;
the vascular region associating unit associates the first vascular region and the second vascular region with each other as different cross sections of the blood vessel of interest;
The hemodynamic information generating unit
generating first position information indicating a position of the first vascular region;
generating second position information indicating a position of the second vascular region;
generating Doppler angle information indicating the magnitude of the Doppler angle in the optical coherence tomography blood flow measurement for the blood vessel of interest based on the first position information and the second position information;
12. The ophthalmic device according to claim 10 or 11.

[13] The hemodynamic information generating unit generates the hemodynamic information in the blood vessel of interest based on the data collected by the repeated scans and the Doppler angle information.
The above 12 ophthalmic devices.

[14] The hemodynamic information generating unit generates evaluation information by applying an evaluation process to the magnitude of the Doppler angle;
Further, a display control unit is provided to display the evaluation information on a display device.
14. The ophthalmic device according to claim 12 or 13.

[15] An observation image generating unit that generates an infrared observation image of the fundus;
a movement mechanism that moves the scanning unit;
a movement control unit that controls the movement mechanism based on a displacement of the infrared observation image relative to the blood vessel map,
When the deviation becomes smaller than a preset threshold, the scan control unit executes the control of the scan unit.
15. The ophthalmic device according to any one of 10 to 14 above.

[16] The vascular map generating unit generates a new vascular map based on new data newly collected from the fundus by the scanning unit;
a projection image generator that applies a projection of the optical coherence tomography scan in an A-scan direction to the vascular map to generate a first projection image, and applies the projection to the new vascular map to generate a second projection image;
a movement mechanism that moves the scanning unit;
a movement control unit that controls the movement mechanism based on a deviation between the first projection image and the second projection image.
15. The ophthalmic device according to any one of 10 to 14 above.

[17] A method for controlling an ophthalmic apparatus having a scanning unit and a processor that performs an optical coherence tomography scan, comprising:
the processor,
a scan control that controls the scan unit to apply an optical coherence tomography scan using a scan pattern without flyback to the fundus of the subject's eye to collect data;
a cross-sectional image generation process for generating a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus based on the data;
a vascular region specifying process for detecting a vascular region group from each of the plurality of cross-sectional images to specify a plurality of vascular region groups corresponding to the plurality of cross-sectional images;
a vascular region association process for associating vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a vascular map generation process for generating a vascular map showing the distribution of blood vessels based on the result of the association.
method.

[18] A method for controlling an ophthalmic apparatus having a scanning unit and a processor that performs an optical coherence tomography scan, comprising:
the processor,
a scan control that controls the scanning unit to collect data by applying an optical coherence tomography scan to a three-dimensional region of the fundus of the subject's eye;
a three-dimensional image generation process for generating a three-dimensional image of the fundus based on the data;
a cross-sectional image extraction process for extracting, from the three-dimensional image, a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus, the cross-sectional images corresponding to a scan pattern without a flyback;
a vascular region specifying process for detecting a vascular region group from each of the plurality of cross-sectional images to specify a plurality of vascular region groups corresponding to the plurality of cross-sectional images;
a vascular region association process for associating vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a vascular map generation process for generating a vascular map showing the distribution of blood vessels based on the result of the association.
method.

[19] A program that causes a computer to execute method 17 or 18 above.

[20] A computer-readable non-transitory recording medium on which the program set forth in 19 above is recorded.

This disclosure is merely an example of how to implement the invention. Anyone who intends to implement the invention may make any modifications (omissions, substitutions, additions, etc.) within the scope of the spirit of the invention.

1000 Ophthalmic apparatus 1010 Scan unit 1020 Cross-sectional image generating unit 1030 Blood vessel region identifying unit 1040 Blood vessel region matching unit 1050 Blood vessel map generating unit

Claims (20)

a scanning unit that applies an optical coherence tomography scan using a scan pattern without flyback to the fundus of the subject's eye to collect data;
a cross-sectional image generating unit that generates a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus based on the data collected by the scanning unit;
a vascular region specifying unit that specifies a plurality of vascular region groups corresponding to the plurality of cross-sectional images by detecting a vascular region group from each of the plurality of cross-sectional images;
a vascular region associating unit that associates vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a blood vessel map generating unit that generates a blood vessel map indicating the distribution of blood vessels based on a result of the association. the scan pattern includes a plurality of patterns each of which does not involve a flyback;
The ophthalmic device of claim 1. the scan pattern includes a concentric pattern that is a combination of the plurality of patterns arranged concentrically;
the plurality of cross sections of the fundus include a plurality of concentric cross sections respectively corresponding to the plurality of patterns;
the scanning unit applies an optical coherence tomography scan using the concentric pattern to the fundus to collect data;
the cross-sectional image generation unit generates the plurality of cross-sectional images corresponding to the plurality of concentric cross sections, respectively, based on the data collected by the optical coherence tomography scan using the concentric pattern;
The ophthalmic device of claim 2. The concentric pattern includes a concentric circular pattern that is a combination of a plurality of circular patterns arranged concentrically,
the plurality of concentric cross sections include a plurality of cylindrical side surfaces that are concentrically arranged corresponding to the plurality of circular patterns, respectively;
the scanning unit applies an optical coherence tomography scan using the concentric circle pattern to the fundus to collect data;
the cross-sectional image generating unit generates the plurality of cross-sectional images corresponding to the plurality of cylindrical side surfaces, respectively, based on the data collected by the optical coherence tomography scan using the concentric circle pattern.
The ophthalmic apparatus of claim 3. a scanning unit that applies optical coherence tomography scanning to a three-dimensional region of the fundus of the subject's eye to collect data;
a three-dimensional image generating unit that generates a three-dimensional image of the fundus based on the data collected by the scanning unit;
a cross-sectional image extracting unit that extracts, from the three-dimensional image, a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus, the cross-sectional images corresponding to a scan pattern without a flyback;
a vascular region specifying unit that specifies a plurality of vascular region groups corresponding to the plurality of cross-sectional images by detecting a vascular region group from each of the plurality of cross-sectional images;
a vascular region associating unit that associates vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a blood vessel map generating unit that generates a blood vessel map indicating the distribution of blood vessels based on a result of the association. the scan pattern includes a plurality of patterns each of which does not involve a flyback;
The ophthalmic device of claim 5. the scan pattern includes a concentric pattern that is a combination of the plurality of patterns arranged concentrically;
the plurality of cross sections of the fundus include a plurality of concentric cross sections respectively corresponding to the plurality of patterns;
the cross-sectional image extraction unit extracts the plurality of cross-sectional images corresponding to the plurality of concentric cross sections from the three-dimensional image;
The ophthalmic device of claim 6. The concentric pattern includes a concentric circular pattern that is a combination of a plurality of circular patterns arranged concentrically,
the plurality of concentric cross sections include a plurality of cylindrical side surfaces that are concentrically arranged and correspond to the plurality of circular patterns, respectively;
the cross-sectional image extraction unit extracts the plurality of cross-sectional images corresponding to the plurality of cylinder side surfaces, respectively, from the three-dimensional image;
The ophthalmic device of claim 7. The vascular region specifying unit
generating a plurality of projection images corresponding to the plurality of cross-sectional images by applying a projection of the optical coherence tomography scan in an A-scan direction to each of the plurality of cross-sectional images;
for each of the plurality of projection images, detecting a blood vessel region group from a corresponding cross-sectional image based on a luminance distribution in the projection image;
The ophthalmic device according to any one of claims 1 to 8. a scan control unit that controls the scanning unit so as to apply repeated scans to a pre-specified blood vessel of interest in the fundus;
and a hemodynamic information generating unit that generates hemodynamic information in the blood vessel of interest based on data collected by the repeated scans.
The ophthalmic apparatus according to any one of claims 1 to 9. further comprising a blood vessel of interest designation unit that analyzes the blood vessel map and designates the blood vessel of interest;
The ophthalmic device of claim 10. the plurality of cross-sectional images include a first cross-sectional image and a second cross-sectional image;
The vascular region specifying unit
detecting a first blood vessel region from the first cross-sectional image;
detecting a second blood vessel region from the second cross-sectional image;
the vascular region associating unit associates the first vascular region and the second vascular region with each other as different cross sections of the blood vessel of interest;
The hemodynamic information generating unit
generating first position information indicating a position of the first vascular region;
generating second position information indicating a position of the second vascular region;
generating Doppler angle information indicating the magnitude of the Doppler angle in the optical coherence tomography blood flow measurement for the blood vessel of interest based on the first position information and the second position information;
12. An ophthalmic apparatus according to claim 10 or 11. the hemodynamic information generating unit generates the hemodynamic information in the blood vessel of interest based on the data collected by the repeated scans and the Doppler angle information.
The ophthalmic device of claim 12. the hemodynamic information generating unit applies an evaluation process to the magnitude of the Doppler angle to generate evaluation information;
Further, a display control unit is provided to display the evaluation information on a display device.
14. An ophthalmic apparatus according to claim 12 or 13. an observation image generating unit that generates an infrared observation image of the fundus;
a movement mechanism that moves the scanning unit;
a movement control unit that controls the movement mechanism based on a displacement of the infrared observation image relative to the blood vessel map,
When the deviation becomes smaller than a preset threshold, the scan control unit executes the control of the scan unit.
The ophthalmic device according to any one of claims 10 to 14. the vascular map generating unit generates a new vascular map based on new data newly collected from the fundus by the scanning unit;
a projection image generator that applies a projection of the optical coherence tomography scan in an A-scan direction to the vascular map to generate a first projection image, and applies the projection to the new vascular map to generate a second projection image;
a movement mechanism that moves the scanning unit;
a movement control unit that controls the movement mechanism based on a deviation between the first projection image and the second projection image.
The ophthalmic device according to any one of claims 10 to 14. 1. A method for controlling an ophthalmic device having a scanning unit and a processor for performing optical coherence tomography scans, comprising:
the processor,
a scan control that controls the scan unit to apply an optical coherence tomography scan using a scan pattern without flyback to the fundus of the subject's eye to collect data;
a cross-sectional image generation process for generating a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus based on the data;
a vascular region specifying process for detecting a vascular region group from each of the plurality of cross-sectional images to specify a plurality of vascular region groups corresponding to the plurality of cross-sectional images;
a vascular region association process for associating vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a vascular map generation process for generating a vascular map showing the distribution of blood vessels based on the result of the association.
method. 1. A method for controlling an ophthalmic device having a scanning unit and a processor for performing optical coherence tomography scans, comprising:
the processor,
a scan control that controls the scanning unit to collect data by applying an optical coherence tomography scan to a three-dimensional region of the fundus of the subject's eye;
a three-dimensional image generation process for generating a three-dimensional image of the fundus based on the data;
a cross-sectional image extraction process for extracting, from the three-dimensional image, a plurality of cross-sectional images corresponding to a plurality of cross sections of the fundus, the cross-sectional images corresponding to a scan pattern without a flyback;
a vascular region specifying process for detecting a vascular region group from each of the plurality of cross-sectional images to specify a plurality of vascular region groups corresponding to the plurality of cross-sectional images;
a vascular region association process for associating vascular regions corresponding to different cross sections of the same blood vessel among the plurality of vascular region groups;
and a vascular map generation process for generating a vascular map showing the distribution of blood vessels based on the result of the association.
method. A program that causes a computer to execute the method of claim 17 or 18. A computer-readable non-transitory recording medium on which the program of claim 19 is recorded.