JP2019217388A - Image generation apparatus, image generation method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To generate an appropriate motion contrast image.
A step of calculating a plurality of tomographic image data of the subject, each showing a tomographic image at substantially the same location of the subject, and a motion contrast using corresponding pixel data among the calculated plurality of tomographic image data. Calculating, and comparing the motion contrast with a threshold, and invalidating the motion contrast equal to or less than the threshold based on the result of the comparison, and after the invalidating step is performed, the Generating a motion contrast image based on the motion contrast, wherein the threshold value is variable or plural.
[Selection diagram] Fig. 1

Description

  The disclosed technology relates to an image generation device, an image generation method, and a program.

  Optical coherence tomography (hereinafter referred to as OCT) has been put to practical use as a method for acquiring a tomographic image of a measurement target such as a living body in a non-destructive and non-invasive manner. In OCT, a tomographic image of the retina at the fundus of a subject's eye is acquired particularly in an ophthalmic region, and is widely used in ophthalmic diagnosis of the retina.

  In OCT, a tomographic image is obtained by causing light reflected from a measurement target and light reflected from a reference mirror to interfere with each other and analyzing the time dependence or wave number dependence of the intensity of the interfered light. As such an optical coherence tomographic image acquisition device, a time domain OCT that obtains depth information of a measurement target by changing the position of a reference mirror is known. Also, a spectral domain OCT (SD-OCT) using a broadband light source is known. Further, a swept source optical coherence tomography (SS-OCT) device using a variable wavelength light source device capable of changing an oscillation wavelength as a light source is known. Note that SD-OCT and SS-OCT are collectively called (FD-OCT: Fourier Domain Optical Coherence Tomography).

  In recent years, a pseudo angiography using this FD-OCT has been proposed, and is called OCT angiography (OCTA).

  Fluorography, a common angiography in modern clinical medicine, requires the injection of a fluorescent dye (eg, fluorescein or indocyanine green) into the body. Although blood vessels that pass through the fluorescent dye are displayed two-dimensionally, OCT angiography enables non-invasive pseudo angiography and three-dimensionally displays a blood flow site network. Furthermore, the method has a higher resolution than fluorescence imaging, and can draw microvessels or blood flow in the fundus, and thus attracts attention.

  A plurality of OCT angiography methods have been proposed due to differences in blood flow detection methods. A method for extracting an OCT signal from a bloodstream by extracting only a signal in which time modulation has occurred from the OCT signal (Non-Patent Document 1) has been proposed. In addition, a method using non-patent document 2 using phase variation due to blood flow, a method using non-patent document 3, and a method using non-patent document 3 using intensity due to blood flow have been proposed. In this specification, a signal in which a time-modulated signal is displayed as an image from an OCT signal may be referred to as a motion contrast image, its pixel value may be referred to as motion contrast, and its data set may be referred to as motion contrast data.

US Patent Application Publication No. 2014/21827

Fingler et al. "Mobility and transverse flow visualization using phasevariance contrast with spectral domain optical coherence tomography" Optics Express. Vol. 15, No. 20. pp 12637-12653 (2007) Optics Letters Vol. 33, Iss. 13, pp. 1530-1532 (2008) "Speckle variance detection of microvasculature using swap-source optical coherence tomography" Mariampillai et al. , "Optimized speckle variance OCT imaging of microvasculature," Optics Letters 35, 1257-1259 (2010).

  However, in the above-mentioned OCT angiography, a blood flow region is not sufficiently delineated or buried in noise due to the influence of strong reflected light from the retinal pigment epithelium (RPE) and various noises. However, it has been difficult to easily obtain a motion contrast image suitable for an image.

  The disclosed technology aims to quickly and appropriately render a motion contrast image. Specifically, it is an object of the present invention to provide an image forming method and apparatus that remove unnecessary noise from a motion contrast image using structural information of a retinal part and render a motion contrast image useful for diagnosis.

  The disclosed technology has been made in view of the above-described problem, and has as one object to generate an appropriate motion contrast image.

  It is to be noted that the present invention is not limited to the above-described object, and it is an operation effect derived from each configuration shown in the embodiment for carrying out the invention described later, and it is also possible to obtain an operation effect that cannot be obtained by the conventional technology. It can be positioned as one.

  The disclosed image generation method includes a step of calculating a plurality of tomographic image data of the subject each showing a tomographic image at substantially the same location of the subject, and using corresponding pixel data between the calculated plurality of tomographic image data. Calculating the motion contrast by comparing the motion contrast with a threshold, disabling the motion contrast equal to or less than the threshold based on the result of the comparison, and performing the disabling. Generating a motion contrast image based on the motion contrast later, wherein the threshold value is variable or plural.

  According to the disclosed technology, it is possible to generate an appropriate motion contrast image.

FIG. 1 is a diagram schematically illustrating an example of an overall configuration of a device according to an embodiment. FIG. 3 is a diagram illustrating an example of a scan pattern according to the embodiment. FIG. 4 is a diagram illustrating an example of an overall processing procedure according to the embodiment. FIG. 4 is a diagram illustrating an example of an interference signal acquisition procedure according to the embodiment. FIG. 4 is a diagram illustrating an example of a signal processing procedure according to the embodiment. FIG. 9 is a diagram showing an example of a three-dimensional blood flow site information acquisition procedure in the embodiment. FIG. 4 is a diagram illustrating an example of a method of converting a motion contrast pixel value into a display pixel according to the embodiment. FIG. 4 is an exemplary view for explaining an example of a GUI according to the embodiment. FIG. 5 is a diagram illustrating an example of a motion contrast image when a threshold value is changed in the embodiment. FIG. 5 is a diagram illustrating an example of a histogram of a motion area and a non-motion area according to the embodiment. FIG. 9 is a diagram illustrating an example of a segmentation result according to the embodiment. FIG. 5 is a diagram illustrating an example of a display information generation procedure according to the embodiment. FIG. 3 is a diagram illustrating an example of a GUI according to the embodiment. FIG. 1 is a diagram schematically illustrating an example of an overall configuration of a device according to an embodiment.

  Hereinafter, an imaging device according to the present embodiment will be described with reference to the accompanying drawings. Note that the configurations shown in the following embodiments are merely examples, and the present invention is not limited to the following embodiments. In the present embodiment, the subject is a human eye (fundus), but is not limited to this, and may be used, for example, on the skin. In the present embodiment, the imaging target is the fundus of the eye, but the anterior eye may be the imaging target.

[First Embodiment]
In the present embodiment, the control unit 143 described below generates a tomographic image from a captured three-dimensional optical interference signal and calculates a motion contrast. Then, the control unit 143 adjusts the noise threshold using the structural information of the part, and shows an example of acquiring clear three-dimensional blood flow part information.

[Configuration of entire image forming apparatus]
FIG. 1 is a diagram illustrating a configuration example of an image forming apparatus using optical coherence tomography according to the present embodiment. The apparatus illustrated in FIG. 1 includes an optical coherence tomography acquisition unit 100 that acquires an optical coherence tomography signal and a control unit 143. The control unit 143 includes a signal processing unit 144, a signal acquisition control unit 145, a display unit 146, and a display control unit 149. The signal processing unit 144 further includes an image generation unit 147 and a map generation unit 148. Here, the control unit 143 is, for example, a computer, and a CPU included in the computer executes a program stored in a storage device (not shown) to execute a signal processing unit 144, a signal acquisition control unit 145, an image generation unit 147, It functions as the map generator 148 and the display controller 149.

  It should be noted that the control unit 143 may include one CPU or storage device, or may include a plurality of CPUs and storage devices. That is, at least one or more processing devices (CPU) and at least one storage device (RAM and ROM) are connected, and at least one or more processing devices execute a program stored in at least one or more storage devices. In such a case, the control unit 143 functions as each of the above units. The processing device is not limited to the CPU, but may be an FPGA or the like.

  First, the configuration of the optical coherence tomography acquisition unit 100 will be described. FIG. 1 is a diagram illustrating a configuration example of an OCT apparatus as an example of an optical coherence tomography acquisition unit according to the present embodiment. The OCT device is, for example, SD-OCT or SS-OCT. In the present embodiment, a configuration in the case where the OCT apparatus is SS-OCT is shown.

<Configuration of OCT device 100>
The configuration of the OCT apparatus 100 will be described.

  The light source 101 is a wavelength-swept (SS) light source, and emits light while sweeping at a sweep center wavelength of 1050 nm and a sweep width of 100 nm, for example. Here, the wavelength and the sweep width are mere examples, and the present invention is not limited to the above values. Similarly, in the following embodiments, the numerical values described are merely examples, and the present invention is not limited to the numerical values described.

  Light emitted from the light source 101 is guided to a beam splitter 110 via an optical fiber 102, and is split into measurement light (also referred to as OCT measurement light) and reference light (also referred to as reference light corresponding to the OCT measurement light). . The splitting ratio of the beam splitter 110 is 90 (reference light): 10 (measurement light). The split measurement light is emitted through the optical fiber 111 and is converted into a parallel light by the collimator 112. The parallel measuring light is incident on the subject's eye 118 via the galvano scanner 114, the scanning lens 115, and the focus lens 116 that scans the measuring light at the fundus Er of the subject's eye 118. Here, the galvano scanner 114 is described as a single mirror, but is actually configured by two galvano scanners (not shown), an X-axis scanner 114a and a Y-axis scanner 114b so as to raster-scan the fundus Er of the eye 118 to be inspected. are doing. The focus lens 116 is fixed on the stage 117, and can perform focus adjustment by moving in the optical axis direction. The galvano scanner 114 and the stage 117 are controlled by the signal acquisition control unit 145, and measure light in a desired range (also referred to as a tomographic image acquisition range, a tomographic image acquisition position, and a measurement light irradiation position) of the fundus Er of the subject's eye 118. Can be scanned.

  Although not described in detail in the present embodiment, it is preferable that a tracking function for detecting the movement of the fundus Er and scanning the mirror of the galvano scanner 114 by following the movement of the fundus Er is provided. The tracking method can be performed using a general technique, and can be performed in real time or by post-processing. For example, there is a method using a scanning laser ophthalmoscope (SLO). In this method, a two-dimensional image (fundus surface image) in a plane perpendicular to the optical axis is acquired with time using the SLO for the fundus Er, and characteristic portions such as blood vessel bifurcations in the image are extracted. It is possible to perform real-time tracking by calculating how the characteristic portion in the acquired two-dimensional image has moved as a movement amount of the fundus Er, and feeding back the calculated movement amount to the galvano scanner 114.

  The measurement light is incident on the subject's eye 118 by the focus lens 116 on the stage 117, and is focused on the fundus Er. The measurement light irradiating the fundus Er is reflected and scattered by each retinal layer, and returns to the beam splitter 110 through the above-described optical path. The return light of the measurement light that has entered the beam splitter 110 enters the beam splitter 128 via the optical fiber 126.

  On the other hand, the reference light split by the beam splitter 106 is emitted through the optical fiber 119a, the polarization controller 150, and the optical fiber 119b, and is converted into a parallel light by the collimator 120. The polarization controller 150 can change the polarization of the reference light to a desired polarization state. The reference light enters the optical fiber 127 via the dispersion compensating glass 122, the ND filter 123, and the collimator 124. One end of the collimator lens 124 and one end of the optical fiber 127 are fixed on the coherence gate stage 125, and the signal acquisition control unit 145 is driven so as to be driven in the optical axis direction according to the difference in the axial length of the subject. Is controlled by In the present embodiment, the optical path length of the reference light is changed, but it is sufficient that the optical path length difference between the optical path of the measurement light and the optical path of the reference light can be changed.

  The reference light that has passed through the optical fiber 127 enters the beam splitter 128. In the beam splitter 128, the return light of the reference light and the reference light are multiplexed into interference light, and then split into two. The split interference light is interference light having phases inverted to each other (hereinafter, referred to as a positive component and a negative component). The positive component of the divided interference light enters one input port of the detector 141 via the optical fiber 129. On the other hand, the negative component of the interference light enters the other detector 141 via the optical fiber 130. The detector 141 is a differential detector. When two interference lights having phases inverted by 180 ° are input, the detector 141 removes a DC component and outputs an interference signal including only the interference component.

  The interference light detected by the detector 141 is output as an electric signal (interference signal) corresponding to the light intensity, and is input to a signal processing unit 144 which is an example of a tomographic image generation unit.

<Control unit 143>
The control unit 143 for controlling the entire apparatus will be described.

  The control unit 143 includes a signal processing unit 144, a signal acquisition control unit 145, a display unit 146, and a display control unit 149. Further, the signal processing unit 144 further includes an image generation unit 147 and a map generation unit 148. The image generation unit 147 has a function of generating a luminance image and a motion contrast image from an electric signal (interference signal) sent from the detector 141, and the map generation unit 148 has a function of generating layer information (retinal segmentation) from the luminance image. Having.

  The signal acquisition control unit 145 controls each unit as described above. The signal processing unit 144 generates an image, analyzes the generated image, and generates visible information of the analysis result based on the interference signal output from the detector 141.

  The image and the analysis result generated by the signal processing unit 144 are sent to the display control unit 149, and the display control unit 149 causes the display screen of the display unit 146 to display the image and the analysis result. Here, the display unit 146 is, for example, a display such as a liquid crystal display. The image data generated by the signal processing unit 144 may be transmitted to the display control unit 149 and then transmitted to the display unit 146 by wire or wirelessly. In the present embodiment, the display unit 146 and the like are included in the control unit 143, but the present invention is not limited to this, and may be provided separately from the control unit 143. For example, an example of a device that can be carried by a user Tablet. In this case, it is preferable that the display unit has a touch panel function so that the display position of the image can be moved, enlarged / reduced, and the displayed image can be changed on the touch panel.

  The above is the description of the process of acquiring information related to a tomogram at one point of the subject 118. Acquiring information on a tomographic slice in the depth direction of the subject 118 in this manner is called A-scan. In addition, scanning is performed in a direction orthogonal to the A-scan, that is, information on a tomographic image of the subject, that is, a scanning direction for acquiring a two-dimensional image in a direction orthogonal to the B-scan and further to a tomographic image obtained by the B-scan. This is called C-scan. This is because, when two-dimensional raster scanning is performed on the fundus oculi when acquiring a three-dimensional tomographic image, the high-speed scanning direction is B-scan, and the low-speed scanning direction in which B-scans are arranged in the orthogonal direction is C-scan. Call it scan. By performing A-scan and B-scan, a two-dimensional tomographic image can be obtained. By performing A-scan, B-scan, and C-scan, a three-dimensional tomographic image can be obtained. B-scan and C-scan are performed by the galvano scanner 114 described above.

  In addition, the X-axis scanner 114a and the Y-axis scanner 114b (not shown) are configured by deflecting mirrors arranged so that their rotation axes are orthogonal to each other. The X-axis scanner 114a performs scanning in the X-axis direction, and the Y-axis scanner 114b performs scanning in the Y-axis direction. Each of the X-axis direction and the Y-axis direction is a direction perpendicular to the eye axis direction of the eyeball, and is a direction perpendicular to each other. Further, the line scanning direction such as B-scan or C-scan does not need to coincide with the X-axis direction or the Y-axis direction. For this reason, the line scanning directions of B-scan and C-scan can be appropriately determined according to a two-dimensional tomographic image or a three-dimensional tomographic image to be captured.

[Scan pattern]
Next, an example of a scan pattern according to the present embodiment will be described with reference to FIG.

  In OCT angiography, a time change of an OCT interference signal due to a blood flow is measured, so that multiple measurements are required at the same place (or substantially the same place). In the present embodiment, the OCT apparatus performs a scan that moves to n y positions while repeating the B scan at the same location m times.

  FIG. 2 shows a specific scan pattern. The B scan is repeatedly performed m times for each of n positions y1 to yn on the fundus plane.

  If m is large, the number of measurements at the same place increases, so that the accuracy of blood flow detection is improved. On the other hand, the scanning time becomes longer, and there arises a problem that motion artifacts occur in an image due to eye movements (fixation fine movement) during scanning and a problem that the burden on the subject increases. In this embodiment, m = 4 in consideration of the balance between the two. The control unit 143 may change m according to the A-scan speed of the OCT apparatus and the motion analysis of the fundus oculi surface image of the subject 118.

  In FIG. 2, p indicates the number of samples of the A scan in one B scan. That is, the plane image size is determined by p × n. If p × n is large, a wide range can be scanned with the same measurement pitch, but the scan time becomes long, and the above-described problems of motion artifact and patient burden occur. In this embodiment, n = p = 300 in consideration of the balance between the two. Note that the above n and p can be freely changed as appropriate.

  Further, Δx in FIG. 2 is an interval (x pitch) between adjacent x positions, and Δy is an interval (y pitch) between adjacent y positions. In the present embodiment, the x pitch and the y pitch are determined as の of the beam spot diameter of the irradiation light on the fundus, and are set to 10 μm. By setting the x pitch and the y pitch to の of the beam spot diameter on the fundus, an image to be generated can be formed with high definition. Even if the x pitch and the y pitch are smaller than の of the fundus beam spot diameter, the effect of further increasing the definition of the generated image is small.

  Conversely, when the x pitch and the y pitch are larger than 1/2 of the fundus beam spot diameter, the definition deteriorates, but a wide range of images can be acquired with a small data capacity. The x pitch and the y pitch may be freely changed according to clinical requirements.

  The scan range of this embodiment is p × Δx = 3 mm in the x direction and n × Δy = 3 mm in the y direction.

Next, a specific processing procedure of the image forming method according to the present embodiment will be described with reference to FIG.
In step S101, the signal acquisition control unit 145 controls the optical coherence tomographic image acquisition unit 100 to acquire an optical coherence tomographic signal. Detailed description of the processing will be described later. In step S102, the control unit 143 generates display information. Details of the processing will be described later. After performing the above steps, the processing procedure of the image forming method of the present embodiment ends.

[Interference signal acquisition procedure]
Next, a specific processing procedure for acquiring an interference signal in step S101 of the present embodiment will be described with reference to FIG. In step S109, the signal acquisition control unit 145 sets the index i of the position yi in FIG. In step S110, the OCT apparatus moves the scan position to yi. In step S119, the signal acquisition control unit 145 sets the index j of the repetitive B scan to 1. In step S120, the OCT apparatus performs a B scan.

In step S130, the detector 141 detects an interference signal for each A scan, and the interference signal is stored in the signal processing unit 144 via an A / D converter (not shown). The signal processing unit 144 obtains p samples of the interference signal of the A scan to obtain an interference signal for 1B scan.
In step S139, the signal acquisition control unit 145 repeatedly increments the index j of the B scan.

  In step S140, the signal acquisition control unit 145 determines whether j is larger than a predetermined number (m). That is, it is determined whether the B scan at the position yi has been repeated m times. If it has not been repeated, the process returns to S120, and the B-scan measurement at the same position is repeated. If it has been repeated a predetermined number of times, the flow proceeds to S149. In step S149, the signal acquisition control unit 145 increments the index i of the position yi. In step S150, the signal acquisition control unit 145 determines whether i is greater than the predetermined number of measurements (n) at the Y position, that is, whether the B scan has been performed at all n y positions. If the number of measurements at the predetermined Y position is less than the number of measurements (no), the process returns to S110, and the measurement at the next measurement position is repeated. If the number of measurements at the predetermined Y position has been completed (yes), the process proceeds to the next step S160.

  In step S160, the OCT apparatus acquires background data. The OCT apparatus measures 100 A-scans with the shutter 85 closed, and the signal acquisition control unit 145 averages and stores the 100 A-scans. Note that the number of background measurements is not limited to 100.

  By performing the above steps, the interference signal obtaining procedure in the present embodiment is completed.

[Signal processing procedure]
Next, a specific process of generating the three-dimensional blood flow site information in step S102 of the present embodiment will be described with reference to FIG.

  In the present embodiment, it is necessary to calculate a motion contrast of OCT angiography in order to generate three-dimensional blood flow region information from OCT angiography information.

  Here, the motion contrast is defined as a contrast between a flowing tissue (for example, blood) and a non-flowing tissue in the subject tissue. The feature quantity expressing the motion contrast is simply defined as motion contrast (or motion contrast feature quantity, motion contrast value). The motion contrast will be described later.

  In step S210, the signal processing unit 144 sets the index i of the position yi to 1. In step S220, the signal processing unit 144 extracts a repeated B-scan interference signal (for m times) at the position yi. In step S230, the signal processing unit 144 sets the index j of the repetitive B scan to 1. In step S240, the signal processing unit 144 extracts the j-th B scan data.

  In step S250, the signal processing unit 144 generates a luminance image of a tomographic image by performing general reconstruction processing on the interference signal of the B scan data in step S240.

  First, the image generation unit 147 removes fixed pattern noise composed of background data from the interference signal. The fixed pattern noise removal is performed by averaging the plurality of detected A-scan signals of the background data to extract fixed pattern noise, and subtracting this from the input interference signal. Next, the image generation unit 147 performs a desired window function process in order to optimize the depth resolution and the dynamic range, which have a trade-off relationship when Fourier transform is performed in a finite section. Thereafter, a luminance image of the tomographic image is generated by performing the FFT processing. In step S260, the signal processing unit 144 repeatedly increments the index j of the B scan. In step S270, the signal processing unit 144 determines whether it is larger than m. That is, it is determined whether the brightness calculation of the B scan at the position yi has been repeated m times. If no, the process returns to step S240 to repeat the brightness calculation of the repeated B scan at the same Y position. That is, the image generation unit 147 acquires a plurality of tomographic image data (tomographic images) of the subject each indicating a tomographic image at substantially the same location of the subject.

  On the other hand, if it is determined “yes” in step S270, the process proceeds to step S280. In step S280, the signal processing unit 144 positions m frames of the repeated B scan at a certain yi position. Specifically, first, the signal processing unit 144 selects an arbitrary one of the m frames as a template. For the frames to be selected as templates, the correlation may be calculated for all the combinations, the sum of the correlation coefficients may be obtained for each frame, and the frame having the maximum sum may be selected. Next, the signal processing unit 144 obtains positional deviation amounts (δX, δY, δθ) by collating each frame with the template. Specifically, the signal processing unit 144 calculates Normalized Cross-Correlation (NCC), which is an index indicating the similarity while changing the position and angle of the template image, and calculates the difference between the image positions when this value becomes the maximum. It is calculated as the amount of displacement.

  In the present invention, the index indicating the degree of similarity can be variously changed as long as it is a scale indicating the similarity between the features of the template and the image in the frame. For example, Sum of Absolute Difference (SAD), Sum of Squared Difference (SSD), and Zero-means Normalized Cross-Correlation (ZNCC) may be used. Further, Phase Only Correlation (POC), Rotation Invariant Phase Only Correlation (RIPOC), or the like may be used.

  Next, the signal processing unit 144 applies position correction to the (m-1) frames other than the template in accordance with the amount of positional deviation (δX, δY, δθ), and aligns the m frames.

  In step S290, the signal processing unit 144 averages the aligned luminance images calculated in step S280 to generate a luminance averaged image.

  In step S300, the map generation unit 148 is a step of performing segmentation of the retina (acquisition of part information) from the luminance averaged image generated in step S290 by the signal processing unit 144. In the first embodiment, this step is not used. This step is skipped. The description will be given in the second embodiment.

  In step S310, the image generation unit 147 calculates a motion contrast. In this embodiment, the variance of the signal intensity (luminance) is calculated for each pixel at the same position from the luminance image of the m-frame tomographic image output by the signal processing unit 144 in step S300, and the variance is used as the motion contrast. . That is, the image generation unit 147 calculates the motion contrast using the pixel data corresponding to the calculated plurality of tomographic image data. In addition, other than the variance value, any of the standard deviation, the difference value, the non-correlation value, and the correlation value may be used. Further, a phase may be used instead of the signal strength.

  Note that there are various methods for obtaining the motion contrast. In the present invention, the type of the feature amount of the motion contrast can be applied as long as it is an index indicating a change in the luminance value of each pixel of the plurality of B scan images at the same Y position. . As the motion contrast, it is also possible to use a variation coefficient normalized by an average value for each pixel of the same position in each frame instead of a variance value for each pixel at the same position from the luminance image of the tomographic image of m frames. In this case, the motion contrast is independent of the pixel value indicating the structure of the retina, and a more sensitive motion contrast can be obtained. However, on the other hand, in the motion contrast, noise components at low pixel values are relatively emphasized due to various factors such as a positioning error and camera noise. For this reason, for example, in a layer that does not contain many capillaries, it becomes difficult to separate the noise and the blood flow region. Therefore, the image processing method of the present invention works more effectively.

  In step S320, the signal processing unit 144 performs the first threshold processing of the motion contrast output from the signal processing unit 144. The value of the first threshold is determined by extracting an area where only random noise is displayed on the noise floor from the luminance averaged image output by the signal processing unit 144 in step S311, calculating the standard deviation σ, and calculating the average luminance of the noise floor. + 2σ. The signal processing unit 144 sets the value of the motion contrast corresponding to the area where each luminance is equal to or less than the threshold to 0.

  By the first threshold processing in S320, noise can be reduced by removing motion contrast resulting from a luminance change due to random noise.

  The smaller the value of the first threshold is, the higher the sensitivity of detecting the motion contrast is, while the noise component is also increased. Also, the larger the noise, the lower the noise, but the lower the sensitivity of motion contrast detection.

  In the present embodiment, the threshold is set as the average luminance of the noise floor + 2σ, but the threshold is not limited to this.

  In step S330, the signal processing unit 144 increments the index i of the position yi.

  In step S340, the signal processing unit 144 determines whether i is greater than n. That is, it is determined whether positioning has been performed at all of the n y-positions, luminance image averaging calculation, motion contrast calculation, and threshold processing have been performed. If no, the process returns to S220. If yes, the process proceeds to the next step S350.

  When S340 is completed, three-dimensional data of the luminance average image and the motion contrast of each pixel of the B scan image (Z depth vs. X direction data) at all Y positions are obtained. Note that B-scan images at a plurality of Y positions correspond to three-dimensional tomographic image data.

  In step S350, the signal processing unit 144 performs a display information generation process using the three-dimensional data of the motion contrast. FIG. 6 shows details of step S350.

  In step S351, the signal processing unit 144 acquires the three-dimensional data of the motion contrast obtained earlier.

In step S352, the signal processing unit 144 performs a smoothing process on the motion contrast three-dimensional data in order to remove noise while leaving the blood flow site information.
Although the optimum smoothing process differs depending on the nature of the motion contrast, for example, the following can be considered.

  A smoothing method for outputting the maximum value of motion contrast from nx × ny × nz voxels in the vicinity of a target pixel. Alternatively, a smoothing method for outputting the average value of the motion contrast of nx × ny × nz voxels in the vicinity of the target pixel. Alternatively, a smoothing method for outputting the median of the motion contrast of nx × ny × nz voxels near the pixel of interest. Alternatively, a smoothing method in which the motion contrast of nx × ny × nz voxels near the target pixel is weighted by distance. Alternatively, a smoothing method in which the motion contrast of nx × ny × nz voxels near the target pixel is weighted according to the difference between the weight based on the distance and the pixel value of the target pixel. Alternatively, a smoothing method that outputs a value using a weight according to the similarity between the motion contrast pattern of the small area around the target pixel and the motion contrast pattern of the small area around the peripheral pixel.

  A method of performing smoothing while leaving other blood flow site information may be used.

  In step S353, the signal processing unit 144 obtains, from the display control unit 149, a threshold value for determining a pixel to be displayed in step S353 and an initial value of a range in the depth direction to be displayed. The initial value of the display range is usually about 1/4 of the depth direction, and is set to a position substantially including the range of the retinal surface layer. The reason why the initial value of the display range is not set to the entire range in the depth direction is that the main blood vessel / capillary network in the surface layer portion should be displayed in an easy-to-read manner. That is, if the surface layer including the main blood vessel / capillary network and the RPE layer having no blood vessel and having a large noise are displayed at the same time, it is difficult to determine the main blood vessel / capillary network in the surface layer. The method for determining the initial value of the display threshold will be described later.

  Next, at step 354, display threshold processing for displaying pixels exceeding the smoothed three-dimensional data using the initial value of the display threshold is performed. FIG. 7 shows an example of conversion from a motion contrast pixel value to a display pixel value by this processing. FIG. 7A shows an example in which a pixel value equal to or less than the display threshold is assigned to zero, and a display pixel value proportional to a pixel from the pixel value above the threshold to the maximum intensity is assigned. FIG. Is an example in which a display value is assigned by multiplying by 0 and pixel values higher than 0 are assigned. In any case, when the motion contrast is equal to or less than the display threshold, the motion contrast is invalidated, and the region having the motion contrast having the displayed connection is displayed in a separated form. That is, the value of the motion contrast is controlled according to the comparison result between the motion contrast and the threshold. The processing in step S354 corresponds to an example of a step of comparing the motion contrast with the threshold and an example of a step of invalidating the motion contrast equal to or less than the threshold based on the result of the comparison.

  In step S355, the display control unit 149 causes the display unit 146 to display the motion contrast image subjected to the display threshold processing shown in FIG. That is, the process in step S355 corresponds to an example of a process of generating a motion contrast image based on the motion contrast after the invalidation process is performed. For example, the display step 355 is designed to display the GUI and the three-dimensional motion contrast image shown in FIG. 8B, and displays them on the display unit 146. Reference numeral 400 denotes a parallelogram area prepared on the display unit 146, and is a display area frame for projecting and displaying the calculated three-dimensional motion contrast image. A slider 407 for adjusting the range in the depth direction for displaying the three-dimensional motion contrast image to be displayed is displayed on the side. The examiner can specify the range in the depth direction of the three-dimensional motion contrast image displayed on the display unit 149 by dragging, for example, the operation unit ends 401 and 402 of the slider 407 with a mouse. Further, by dragging, for example, the center of the operation unit of the slider 407, the displayed depth position can be changed without changing the width of the displayed depth range. FIG. 8A also shows one tomographic image of a three-dimensional motion contrast image for explaining the corresponding depth. The bright lines 403 and 404 on the tomographic image are positions on the tomographic image corresponding to the slider ends 401 and 402. In the display step, only the motion contrast image of the area 405 sandwiched between the two bright lines is displayed in the display area frame 401. For example, the display control unit 149 may cause the display unit 149 to display all the images shown in FIGS. 8A and 8B, or display only the image shown in FIG. 8B. Good.

  Further, another slider 406 is provided below the display area frame 400 to adjust a threshold value for determining a pixel to be displayed. If the examiner drags this slider with, for example, a mouse, the display threshold is changed in step S356 in FIG. 6, and the process returns to step S354 to update the three-dimensional motion contrast image to be displayed. The process of step S356 corresponds to an example of a process of changing the threshold. Repeating steps S354 and S355 corresponds to repeatedly executing the step of generating a motion contrast image and the step of displaying the motion contrast image in accordance with the change in the threshold value.

  At this time, if the adjustment of the threshold value is set so that it can be changed by a relative value with respect to the initial value, an equivalent effect can be obtained even with respect to different data such as different eyes or parts to be examined. With the above configuration, the examiner can arbitrarily change the depth range to be displayed, and can set an optimal display threshold value for the selected depth range. Similarly, when the examiner drags the slider operation unit ends 401 and 402 with the mouse in order to change the display range in the depth direction, the range to be displayed is changed in step S357. Then, the process returns to step S354 to update the three-dimensional motion contrast image to be displayed. That is, the motion contrast image displayed according to the change of the display range is updated. Here, the process of step S357 corresponds to an example of a process of setting a display range in the depth direction of the motion contrast image. Further, the execution of step S355 after the execution of step S357 corresponds to an example of a process of displaying a motion contrast image based on the set display range.

  In the above description, the tomographic image shown in FIG. 8A is used only for description, but if this tomographic image is displayed simultaneously in the display step, the depth range to be displayed by the examiner can be easily set. It is possible to do so, which is more preferable. Further, the tomographic image is desirably provided on the side of the display area frame 400 in order to clearly indicate the depth direction. Further, it is desirable to display a position corresponding to the tomographic image to be displayed so as to overlap the three-dimensional motion contrast image. For example, the table display control unit 149 may display a line corresponding to a tomographic image so as to be superimposed on a three-dimensional motion contrast image.

  FIG. 9 is a diagram showing an example of a two-dimensional motion contrast image generated by projecting or integrating each pixel value of the three-dimensional motion contrast image in the selected depth range in the depth direction.

  In the above embodiment, a three-dimensional motion contrast image is displayed as shown in FIG. 8B, but the present invention is not limited to this, and a two-dimensional motion contrast image may be displayed. For example, a two-dimensional motion contrast image may be displayed instead of a three-dimensional motion contrast image, or both may be displayed simultaneously.

  In order to generate a two-dimensional motion contrast image, a motion contrast value of a corresponding pixel may be integrated, or a representative value such as a maximum value, a minimum value, and a median value may be extracted and projected. Here, an example of a two-dimensional motion contrast image in the case of integration is shown in FIG. Of course, the display threshold can be similarly changed by the examiner operating the slider 406 shown in FIG. FIG. 9B shows the case where the threshold value is considered to be optimal empirically, FIG. 9A shows the case where the threshold value is lower than that of FIG. 9B, and FIG. 9C shows the case where the threshold value is higher than that of FIG. Equivalent to. In (a), noise appears and is not suitable for grasping the structure of the blood flow region, but (b) is suitable for grasping the structure of the minute blood flow region, and when comparing with a conventional fluorescence fundus photograph, An image like (c) would be preferred.

  Here, a method of automatically determining the threshold will be described with reference to FIG. FIG. 10A shows a histogram of a motion contrast in a certain depth range when the depth is selected. The noise peak N1 is on the low luminance side, and the signal of the blood flow region is on the high luminance side. A peak is observed. In the display threshold step, Th1 corresponding to the intersection of these two peaks is programmed to be the initial value of the display threshold. Of course, it is also possible to give a certain ratio or a certain amount of shift empirically. FIGS. 10B and 10C show changes in the histogram when the examiner changes the range displayed in the depth direction. (B) shows a case where a range with a small blood flow is selected, and moves as shown in (c) when a range with a large blood flow is selected, and the noise peaks S2 and S3 of the noise N2, N3, and blood flow regions respectively move. Then, appropriate display threshold initial values Th2 and Th3 are set. That is, the display threshold is automatically changed in conjunction with the display range of the motion contrast image. As described above, according to the present embodiment, the motion region and the non-motion region can be estimated from the motion contrast histogram of the predetermined region, and the threshold can be determined from the motion region histogram and the non-motion region histogram.

  The method of determining a uniform threshold value for the target region using the histogram of the motion contrast in the display range in the depth direction, which is the target region, has been described above, but the present invention is not limited to this. For example, it is also possible to use a local determination method such as determining a threshold based on the average and variance of the motion contrast for a predetermined area of the display area without uniformly setting a threshold value for the same area.

  Of course, when the examiner operates the slider 406 as described above, the value can be stored and used as a threshold value for subsequent display, and a switch for returning to the initial setting can be additionally provided. is there.

  According to the above-described embodiment, the noise in the motion contrast calculation is removed by making the appropriate display threshold variable or plural for the motion contrast data constituting the OCT angiography, and the blood flow region information that is more easily viewable is quickly obtained. Can be provided.

  Further, in the step of calculating the motion contrast, a step of normalizing the motion contrast using an average value of the corresponding pixel data of the plurality of tomographic image data used in the calculation is included. Noise can be effectively removed.

  Furthermore, by setting the display range in the depth direction when displaying the calculated motion contrast image, the display range can be easily changed and an appropriate display threshold can be set.

  Further, by limiting the display setting range to a predetermined width in the depth direction of the tomographic image, unnecessary overlapping portions of the motion contrast image can be removed, so that an image that is easy to understand can be taught. That is, in the present embodiment, the settable display range can be limited to a predetermined width in the depth direction.

  In this case, by further providing a step of detecting the layer structure of the tomographic image of the eye from the three-dimensional tomographic image data, it is possible to select and limit the display range in the depth direction according to the structure of the retina of the eye to be inspected. Display processing according to the anatomical structure of the optometry becomes possible, which is more effective.

  Further, if a two-dimensional motion contrast image is generated by projecting and integrating the three-dimensional motion contrast according to the selection of the display range, a motion contrast image which is more intuitive and easy to understand can be provided.

  In addition, if the display means selects or generates a tomographic image at a position corresponding to the position designated by the motion contrast image from the three-dimensional motion contrast and displays the tomographic image, it is more intuitive to identify which layer is currently displaying information about which layer. Can be performed. That is, in the present embodiment, in the step of displaying the motion contrast image, the tomographic image at the position corresponding to the position specified on the motion contrast image is selected or generated from the three-dimensional motion contrast and displayed.

  Furthermore, the threshold value of the predetermined area can be adaptively determined based on the motion contrast value of the peripheral pixels of each pixel of the motion contrast image to which the threshold value is applied. For example, a motion area and a non-motion area can be estimated from a motion contrast histogram of a predetermined area, and a threshold can be adaptively determined from the histogram of each area. Alternatively, the threshold value can be locally determined based on the average value and the variance of the motion contrast in a predetermined area. Therefore, it is possible to provide a motion contrast image that is easier to see and understand.

[Second embodiment]
In the above-described first embodiment, the mode in which the inspector directly selects the display range in the depth direction has been described. However, the fundus of the subject's eye to be imaged generally has a layer structure as shown in FIG. Are known. In consideration of the fact that the blood vessel density differs for each retinal layer in the depth direction, it is preferable to make the threshold for detecting the blood flow site variable for each layer. The step S300 in FIG. 5, which is not used in the first embodiment, is a step of segmenting this layer structure. In this embodiment, six layers can be detected. That is, the process in step S300 corresponds to an example of a process of detecting a layer from tomographic image data. The number of layers to be detected is not limited to six. Here, the breakdown of the six layers is (1) the nerve fiber layer (NFL), (2) the layer obtained by combining the ganglion cell layer (GCL) and the inner plexiform layer (IPL), and (3) the inner granular layer (INL). (4) outer granular layer (ONL) + outer limiting membrane (ELM) combined layer, (5) Ellipsoid Zone (EZ) + Interdigestion Zone (IZ) + retinal pigment The combined layers of epithelium (RPE), (6) Choroid.

  The specific processing of generating the three-dimensional blood flow region information in step S102 in the present embodiment is substantially the same as that in the first embodiment shown in FIG. 5, and thus detailed description is omitted. Here, the segmentation of the retina in the characteristic step S300 will be described below.

  The map generator 148 creates an image by applying a median filter and a Sobel filter to a tomographic image to be subjected to processing extracted from the luminance averaged image (hereinafter, also referred to as a median image and a Sobel image, respectively). . Next, a profile is created for each A-scan from the created median image and Sobel image. The median image has a brightness value profile, and the Sobel image has a gradient profile. Then, a peak in the profile created from the Sobel image is detected. The boundary of each region of the retinal layer is extracted by referring to the profile of the median image before and after the detected peak and between the peaks. The segmentation result obtained in step S300 is once held here, and after the processing is performed in the same manner as in the first embodiment described below, the display information generation step in step 350 is performed.

  The display information generation step of step 350 in the second embodiment will be described with reference to FIG. The second embodiment is characterized in that the setting of the display range in the depth direction of the motion contrast image is performed by selecting a layer based on the result of the segmentation of the retina in step S300. That is, the display range can be selected based on the detected layer.

  FIG. 12 shows details of step S350. However, the basics are the same as in the first embodiment. That is, in step S351, three-dimensional data of motion contrast is obtained, and in step S352, smoothing processing is performed on the three-dimensional motion contrast data in order to remove noise while leaving blood flow site information.

  Next, in step S353, the signal processing unit 144 obtains a display threshold value for determining a pixel to be displayed in step S353 and an initial value of a layer to be displayed. The method of determining the initial value of the display threshold is the same as that of the first embodiment, but the initial value of the display range is, for example, four layers from the surface layer, that is, the nerve fiber layer (NFL) and the ganglion cell layer (GCL). , An inner plexiform layer (IPL) and an inner granular layer (INL). Note that at least three layers may be selected from four layers from the surface layer as initial values. However, when a plurality of layers are selected as initial values, it is desirable that the layers be continuous. In the case of a layer that cannot be separated by retinal layer segmentation, a layer described as a composite layer thereof is desirable. The reason why the initial value of the display range is not set to the entire retinal layer is that the main blood vessel / capillary network in the surface layer portion should be displayed in an easy-to-read manner. That is, if the surface layer including the main blood vessel / capillary network and the RPE layer having no blood vessel and having a large noise are displayed at the same time, it is difficult to determine the main blood vessel / capillary network in the surface layer.

  Next, in step S354, display threshold processing for displaying pixels exceeding the three-dimensional data that has been smoothed using the initial values is performed. Thereafter, in step S355, a step of displaying a motion contrast image subjected to the display threshold processing as shown in FIG. 13 is performed. For example, as shown in FIG. 13, a two-dimensional motion contrast image 71, and a tomographic image 72 at the position of the marker AA ′ shown on the two-dimensional motion contrast image 71 and other GUIs 73 are displayed by the display control unit 149 beside the two-dimensional motion contrast image 71. It is displayed in the section 146.

  Another GUI 73 is provided beside the tomographic image 72. From the right, the name of the retinal layer used for displaying the two-dimensional motion contrast image, a check box for selecting it, and a slider for adjusting the threshold value for determining each display pixel for the selected layer are provided from the right. ing. When the examiner drags this slider with the mouse, the display threshold is changed in step S356 in FIG. 12, and the process returns to step S354 to update the two-dimensional motion contrast image to be displayed. That is, as shown in the GUI 73, in the present embodiment, the threshold is set for each detected layer.

  When the examiner changes the check of the check box in order to change the selection of the layer (corresponding to the change of the display range in the depth direction in the first embodiment), in step S357, the range in which the motion contrast image is displayed. Is changed, and the process returns to step S354 to update the two-dimensional motion contrast image to be displayed.

  At this time, the number of layers to be selected is limited to, for example, five layers, and when the upper retina layer is selected (for example, nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL)) At least one of an inner granular layer (INL), an outer plexiform layer (OPL), an outer granular layer (ONL), and an outer limiting membrane (ELM)). One is unselectable. Alternatively, when the lower retinal layer is selected (for example, inner nuclear layer (INL), outer plexiform layer (OPL), outer granular layer (ONL), outer limiting membrane (ELM), Ellipsoid Zone (EZ), Interdigestion Zone (IZ)) Retinal pigment epithelium (RPE) layer, choroid) at least nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner granular layer (INL), outer plexiform layer (OPL) The control for making one of the outer granular layer (ONL) and the outer limiting membrane (ELM) unselectable is effective in maintaining the diagnostic value of the displayed motion contrast image. As described above, in the present embodiment, in setting the display range, an arbitrary layer can be selected based on the detected layer, and the number of selectable layers can be limited.

  It is desirable that the boundary of each layer is further displayed on the tomographic image as a result of the segmentation, and that marking is performed so that the selected layer can be easily recognized. A radio button 74 of Layer / Border at the bottom of the other GUI 73 is a radio button for selecting a method of generating a two-dimensional motion contrast image. When the layer is selected, a two-dimensional motion contrast image is generated based on information of each pixel value of the selected three-dimensional motion contrast image of the entire layer. However, when Border is selected, the selectable check boxes are controlled so that two adjacent ones are restricted, and each of the three-dimensional motion contrast images of a predetermined depth sandwiching the boundary between the two selected layers is controlled. A two-dimensional motion contrast image is generated based on the pixel value information.

  Note that the first embodiment and the second embodiment may be combined. For example, the slider 406 shown in FIG. 8B may be displayed on the screen in FIG.

  According to the present embodiment, it is possible to easily set the display range of the motion contrast image using the segmentation result.

[Third embodiment]
In the second embodiment, an example has been described in which the segmentation result calculated based on the luminance information is used as the part structure information in order to clarify the three-dimensional blood flow part information. On the other hand, in the present embodiment, an example of acquiring part structure information using polarization information of an optical coherence tomography as part structure information will be described.

  FIG. 14 is a diagram illustrating a configuration example of an image forming method and apparatus using optical coherence tomography according to the present embodiment. The image forming method and apparatus include an optical coherence tomography acquisition unit 800 that acquires an optical coherence tomography signal and a control unit 143. The control unit 143 further includes a signal processing unit 144, a signal acquisition control unit 145, a display control unit 149, and a display unit 146. The signal processing unit 144 further includes an image generation unit and a map generation unit.

  First, the configuration of the optical coherence tomographic acquisition unit 800 will be described. In the present embodiment, a polarization OCT device using SS (Swept Source) -OCT will be described. Note that the present invention can be applied to a polarization OCT apparatus using SD-OCT.

<Configuration of polarization OCT apparatus 800>
The configuration of the polarization OCT device 800 will be described.

  The light source 801 is a wavelength-swept (SS) light source, and emits light while sweeping at a sweep center wavelength of 1050 nm and a sweep width of 100 nm, for example.

  Light emitted from the light source 801 includes a single mode fiber (hereinafter referred to as SM fiber) 802, a polarization controller 803 connector 804, an SM fiber 805, a polarizer 806, and a polarization maintaining (PM) fiber (hereinafter referred to as a PM fiber). Description) 807, a connector 808, and a PM fiber 809, the light is guided to a beam splitter 810, and split into measurement light (also referred to as OCT measurement light) and reference light (also referred to as reference light corresponding to the OCT measurement light). The split ratio of the beam splitter 810 is 90 (reference light): 10 (measurement light). The polarization controller 103 can change the polarization of light emitted from the light source 101 to a desired polarization state. On the other hand, the polarizer 806 is an optical element having a characteristic of passing only a specific linearly polarized light component. Normally, light emitted from the light source 801 has a high degree of polarization, and light having a specific polarization direction is dominant, but includes light having no specific polarization direction, called a random polarization component. It is known that the random polarization component deteriorates the image quality of the polarized OCT image, and the random polarization component is cut by a polarizer. Since only light in a specific linear polarization state can pass through the polarizer 806, the polarization state is adjusted by the polarization controller 803 so that a desired amount of light is incident on the subject's eye 118.

  The branched measurement light is emitted through the PM fiber 811 and is converted into a parallel light by the collimator 812. The parallel measuring light is transmitted through a 波長 wavelength plate 813 and then enters the eye 818 via a galvano scanner 814, a scan lens 815, and a focus lens 816 that scans the measuring light at the fundus Er of the eye 818. I do. Here, the galvano scanner 814 is described as a single mirror, but is actually configured by two galvano scanners so as to raster-scan the fundus Er of the subject's eye 118. Further, the focus lens 816 is fixed on the stage 817, and the focus can be adjusted by moving in the optical axis direction. The galvano scanner 814 and the stage 817 are controlled by the signal acquisition control unit 145, and measure light in a desired range (also referred to as a tomographic image acquisition range, a tomographic image acquisition position, and a measurement light irradiation position) of the fundus Er of the subject's eye 118. Can be scanned. The 波長 wavelength plate 813 is an optical element having a characteristic of delaying the phase between the optical axis of the 波長 wavelength plate and an axis orthogonal to the optical axis by 波長 wavelength. In this embodiment, the optical axis of the 波長 wavelength plate is rotated by 45 ° with respect to the direction of the linearly polarized light of the measurement light emitted from the PM fiber 811 using the optical axis as the rotation axis, and the light incident on the subject's eye 118 is circular. Polarized light. Although not described in detail in the present embodiment, it is preferable that a tracking function for detecting the movement of the fundus Er and scanning the mirror of the galvano scanner 114 so as to follow the movement of the fundus Er is provided. The tracking method can be performed using a general technique, and can be performed in real time or by post-processing. For example, there is a method using a scanning laser ophthalmoscope (SLO). In this method, a two-dimensional image in a plane perpendicular to the optical axis is acquired with time using the SLO with respect to the fundus Er, and a characteristic portion such as a blood vessel branch in the image is extracted. It is possible to perform real-time tracking by calculating how the characteristic portion in the acquired two-dimensional image has moved as a movement amount of the fundus Er, and feeding back the calculated movement amount to the galvano scanner 814.

  The measurement light is incident on the subject's eye 118 by the focus lens 816 on the stage 817, and is focused on the fundus Er. The measurement light irradiated to the fundus Er is reflected and scattered by each retinal layer, and returns to the beam splitter 810 through the above-described optical path. Return light of the measurement light that has entered the beam splitter 810 passes through the PM fiber 826 and enters the beam splitter 828.

  On the other hand, the reference light split by the beam splitter 806 is emitted through the PM fiber 819 and is converted into a parallel light by the collimator 820. The reference light enters the PM fiber 827 via the half-wave plate 821, the dispersion compensation glass 822, the ND filter 823, and the collimator 824. One end of the collimator lens 824 and one end of the PM fiber 827 are fixed on the coherence gate stage 825, and the signal acquisition control unit 145 is driven in the optical axis direction according to the difference in the eye axis length of the subject. Is controlled by The half-wave plate 821 is an optical element having a characteristic of delaying the phase between the optical axis of the half-wave plate and an axis orthogonal to the optical axis by a half wavelength. In the present embodiment, the adjustment is performed so that the linearly polarized light of the reference light emitted from the PM fiber 819 becomes a polarized state in which the major axis of the PM fiber 827 is inclined by 45 °. In the present embodiment, the optical path length of the reference light is changed, but it is sufficient that the optical path length difference between the optical path of the measurement light and the optical path of the reference light can be changed.

  The reference light having passed through the PM fiber 827 enters the beam splitter 828. In the beam splitter 828, the return light of the reference light and the reference light are multiplexed to form interference light, and then split into two. The split interference light is interference light having phases inverted to each other (hereinafter, referred to as a positive component and a negative component). The positive component of the split interference light enters the polarization beam splitter 835 via the PM fiber 829, the connector 831 and the PM fiber 833. On the other hand, the negative polarization component of the interference light enters the polarization beam splitter 836 via the PM fiber 830, the connector 832, and the PM fiber 834.

In the polarization beam splitters 835 and 836, the interference light is split in accordance with two orthogonal polarization axes, and a vertical (Vertical) polarization component (hereinafter, V polarization component) and a horizontal (Horizontal) polarization component (hereinafter, H polarization component). Is divided into two lights. The positive interference light incident on the polarization beam splitter 835 is split by the polarization beam splitter 835 into two interference lights of a positive V polarization component and a positive H polarization component. The split positive V-polarized component enters the detector 841 via the PM fiber 837, and the positive H-polarized component enters the detector 842 via the PM fiber 838. On the other hand, the negative interference light incident on the polarization beam splitter 836 is split by the polarization beam splitter 836 into a negative V polarization component and a negative H polarization component. The negative V polarization component enters the detector 841 via the PM fiber 839, and the negative H polarization component enters the detector 142 via the PM fiber 840.
Each of the detectors 841 and 842 is a differential detector. When two interference signals whose phases are inverted by 180 ° are input, the DC components are removed and only the interference components are output.

  The V-polarized component of the interference signal detected by the detector 841 and the H-polarized component of the interference signal detected by the detector 842 are output as electric signals corresponding to the light intensities, respectively, and a signal processing unit which is an example of a tomographic image generation unit 144.

<Control unit 143>
The control unit 143 for controlling the entire apparatus will be described.

  The control unit 143 includes a signal processing unit 144, a signal acquisition control unit 145, a display unit 146, and a display control unit 149. Further, the signal processing unit 144 further includes an image generation unit 147 and a map generation unit 148. The image generation unit 147 has a function of generating a luminance image and a polarization characteristic image from the electric signal sent to the signal processing unit 144, and the map generation unit 148 has a function of detecting nerve fiber bundles and retinal pigment epithelium.

  The signal acquisition control unit 145 controls each unit as described above. The signal processing unit 144 generates an image, analyzes the generated image, and generates visualization information of the analysis result based on the signals output from the detectors 841 and 842.

  Since the display unit 146 and the display control unit 149 are substantially the same as those shown in the first embodiment, detailed description will be omitted.

[Image processing]
Next, image generation in the signal processing unit 144 will be described. The signal processing unit 144 performs general reconstruction processing in the image generation unit 147 on the interference signals output from the detectors 841 and 842. By this processing, the signal processing unit 144 generates a tomographic image corresponding to the H-polarized component and a tomographic image corresponding to the V-polarized component, which are two tomographic images based on the respective polarized components.

  First, the image generation unit 147 removes fixed pattern noise from the interference signal. The fixed pattern noise removal is performed by averaging a plurality of detected A-scan signals to extract fixed pattern noise, and subtracting this from the input interference signal. Next, the image generation unit 147 performs a desired window function process in order to optimize the depth resolution and the dynamic range, which have a trade-off relationship when Fourier transform is performed in a finite section. Then, a tomographic signal is generated by performing FFT processing.

  By performing the above processing on the interference signal of the two polarization components, two tomographic images are generated. A luminance image and a polarization characteristic image are generated based on these tomographic signals and tomographic images. The polarization characteristic image is an image of the polarization characteristic of the subject's eye, and includes, for example, an image based on retardation information, an image based on orientation information, and an image based on birefringence information.

<Generation of luminance image>
The image generator 147 generates a luminance image from the two tomographic signals described above. The luminance image is basically the same as the tomographic image in the conventional OCT (similar to step S250 of the first embodiment), and its pixel value r is the tomographic signals A _H and V of the H polarization component obtained from the detectors 141 and 142. It is calculated by equation 1 from the tomographic signal a _V polarization components.

  Further, by performing raster scan by the galvano scanner 814, the B-scan images of the fundus Er of the subject's eye 818 are arranged in the sub-scanning direction, and three-dimensional data of a luminance image is generated.

  When the processing described in the first embodiment is applied, the fundus Er is photographed with a scan pattern for OCT angiography, and OCT angiography is acquired from the luminance image calculated above.

  Since the retinal pigment epithelium (RPE) has a property of depolarizing, the signal processing unit 144 detects the RPE based on the property.

[RPE segmentation]
<DOPU image generation>
The image generation unit 147 calculates the Stokes vector S for each pixel from the acquired tomographic signals A _{H and} A _V and the phase difference ΔΦ between them using Equation 2.

<DOPU image generation>
The image generation unit 147 calculates the Stokes vector S for each pixel from the acquired tomographic signals A _{H and} A _V and the phase difference ΔΦ between them using Equation 2.

However, .DELTA..PHI is calculated from the phase [Phi _H and [Phi _V of each signal obtained in calculating the two tomographic images as ΔΦ = Φ _V -Φ _H.

  Next, the image generation unit 147 sets a window having a size of about 70 μm in the main scanning direction of the measurement light and a size of about 18 μm in the depth direction for each B-scan image, and is calculated for each pixel by Expression 2 in each window. The elements of the Stokes vector are averaged, and the DOPU (Degree Of Polarization Uniformity) within the window is calculated by Equation 3.

Here, Q _m , U _m , and V _m are values obtained by averaging the elements Q, U, and V of the Stokes vector in each window. By performing this processing for all windows in the B-scan image, a DOPU image (also referred to as a tomographic image indicating the degree of uniformity of polarization) is generated.

  DOPU is a numerical value representing the uniformity of polarized light, and is a numerical value close to 1 at a position where polarized light is maintained, and is a numerical value smaller than 1 at a position where polarized light is not maintained. In the structure in the retina, since the RPE has a property of canceling the polarization state, the value of the portion corresponding to the RPE in the DOPU image is smaller than that of other regions. In the DOPU image, since a layer for depolarizing RPE or the like is imaged, even when the RPE is deformed due to a disease or the like, the RPE can be imaged more reliably than a change in luminance.

  The segmentation information of the RPE is obtained from the DOPU image.

  By this processing, it is determined whether or not each position is an RPE from the captured interference signal (three-dimensional data).

[Processing operation]
Next, a specific processing procedure of the image forming method according to the present embodiment will be described. The basic processing flow in the present embodiment is the same as the processing flow in the first embodiment, and thus a brief description is omitted. However, since the detailed processes of steps S250, S300, and S320 are different, the corresponding steps S250A, S300A, and S320A of the present embodiment will be described in detail below.

In step S250A, the signal processing unit 144 generates a tomographic image _{A H} and the tomographic image _{A V,} to generate a luminance image. Further, a DOPU image is generated.

  In step S300A, the map generator 148 performs RPE segmentation using the luminance image and the DOPU image.

  In step S320A, the signal processing unit 144 corrects OCT angiography information (here, motion contrast) using the site information (retinal segmentation information) acquired in step S300A. Here, the noise threshold (first threshold) of the motion contrast in the RPE is increased using DOPU information (information that is an RPE) of the pixel obtained from the retinal segmentation information. For example, the threshold value for the RPE is set higher than the threshold value for the region above the RPE. Alternatively, the motion contrast is reduced so as not to be a blood flow site. By doing so, the threshold processing performed in step S320A can be performed more accurately. The noise at a deep position may be reduced by increasing the threshold value of a portion deeper than the RPE as compared with other regions.

  By using the polarization OCT apparatus described above, RPE segmentation can be obtained, noise can be more accurately reduced from three-dimensional data of motion contrast, and clear three-dimensional blood flow site information can be obtained. Can be. Further, it is possible to prevent an uncertain blood flow site from being displayed.

  The display threshold in step S354 may be controlled like the above-described noise threshold. For example, the noise at a deep position may be reduced by increasing the display threshold at a portion deeper than the RPE as compared with other regions. Further, the display threshold value related to the RPE may be set higher than the display threshold value of the region above the RPE.

[Fourth embodiment]
In the third embodiment, the example of acquiring the structure information of the RPE using the polarization information of the optical coherence tomography as the part structure information has been described. In the present embodiment, an example of acquiring the structure information of the RNFL will be described.

  An example of the configuration of the image forming method and apparatus according to the present embodiment is the same as that of FIG. 14 of the third embodiment, and a description thereof will not be repeated.

  The layer having birefringence is the retinal nerve fiber layer (RNFL), and the signal processing unit 144 of the present embodiment detects the RNFL based on the property.

<Generation of retardation image>
The image generation unit 147 generates a retardation image from the tomographic images of the polarization components orthogonal to each other.

The value δ of each pixel of the retardation image is obtained by quantifying the phase difference between the vertical polarization component and the horizontal polarization component at the position of each pixel constituting the tomographic image, and the respective tomographic signals A _H and A _V Is calculated according to Equation 4.

  By generating a retardation image, a birefringent layer such as a retinal nerve fiber layer (RNFL) is grasped.

  The signal processing unit 144 detects a retinal nerve fiber layer (RNFL) from retardation images obtained for a plurality of B-scan images.

<Generation of retardation map>
The signal processing unit 144 generates a retardation map from retardation images obtained for a plurality of B-scan images.

  First, the signal processing unit 144 detects a retinal pigment epithelium (RPE) in each B-scan image. Since the RPE has the property of depolarizing, each A-scan is examined along the depth direction from the inner limiting membrane (ILM) to the distribution of retardation in a range not including the RPE, and the maximum value is determined in the A-scan. This is a representative value of retardation.

  The map generation unit 148 generates a retardation map by performing the above processing on all the retardation images.

[RNFL segmentation]
<Generation of birefringence map>
The image generation unit 147 linearly approximates the value of the retardation δ in the range from the ILM to the retinal nerve fiber layer (RNFL) in each of the A-scan images of the previously generated retardation image, and determines the slope of the A-scan image. Is determined as the birefringence at the position on the retina. By performing this process on all the acquired retardation images, a map representing birefringence is generated. Then, the map generator 148 performs RNFL segmentation using the birefringence value.

[Processing operation]
Next, a specific processing procedure of the image forming method according to the present embodiment will be described. The basic processing flow in the present embodiment is the same as the processing flow in the second embodiment, and thus a brief description is omitted. However, since the detailed processes of Step S250A, Step S300A, and Step S320A are different, Step S250B, Step S300B, and Step S320B of the present embodiment corresponding to each will be described in detail below.

In step S250B, the signal processing unit 144 generates a tomographic image _{A H} and the tomographic image _{A V,} to generate a luminance image. Further, a retardation image is generated.

  In step S300B, the map generation unit 148 generates a retardation map and performs RNFL segmentation using the luminance image and the retardation image.

  In step S320B, the signal processing unit 144 corrects OCT angiography information (here, motion contrast) using the site information (retinal segmentation information) acquired in step S300B. Here, the noise threshold (first threshold) of the RNFL motion contrast is raised using the retardation information of the pixel (information that is RNFL) obtained from the retinal segmentation information. Alternatively, the motion contrast is reduced so as not to be a blood flow site. By doing so, the threshold processing performed in step S320B can be performed more accurately.

  As described above, by using the polarization OCT apparatus described above, RNFL segmentation can be obtained, noise can be more accurately reduced from three-dimensional data of motion contrast, and clear three-dimensional blood flow site information can be obtained. Can be.

  The display threshold in step S354 may be controlled like the above-described noise threshold.

  Above, RPE and RNFL were segmented using the polarization OCT information, and a method for acquiring clearer three-dimensional blood flow site information was described. However, the present embodiment is not limited to RPE and RNFL, and other You may apply also to a site | part.

  Furthermore, the blood vessel can be specified using the polarization characteristics of the blood vessel wall, and the reliability of the result of the combination with the motion contrast information can be improved.

[Other Examples]
Although the embodiments have been described in detail, the present invention can take embodiments as a system, an apparatus, a method, a program, a recording medium (storage medium), or the like. Specifically, the present invention may be applied to a system including a plurality of devices (for example, a host computer, an interface device, an imaging device, a web application, and the like), or may be applied to a device including a single device. good.

  Needless to say, the purpose of the disclosed technology is achieved by the following. That is, a recording medium (or a storage medium) in which a program code (computer program) of software for realizing the functions of the above-described embodiments is supplied to a system or an apparatus. Needless to say, such a storage medium is a computer-readable storage medium. Then, the computer (or CPU or MPU) of the system or the apparatus reads out and executes the program code stored in the recording medium. In this case, the program code itself read from the recording medium implements the functions of the above-described embodiment, and the recording medium on which the program code is recorded constitutes the present invention.

143 control unit 144 signal processing unit 145 signal acquisition control unit 146 display unit 147 image generation unit 148 map generation unit 149 display control unit

One of the disclosed image generation methods is:
A step of calculating a motion contrast value using corresponding pixel data between a plurality of tomographic image data of the eye to be inspected obtained by scanning substantially the same position of the eye to be inspected a plurality of times with measurement light,
Based on a comparison result obtained by comparing the motion contrast value and a threshold, a step of invalidating a motion contrast value equal to or less than the threshold,
A step of performing alignment of the plurality of tomographic image data before the motion contrast value is calculated,
A step of detecting a plurality of layer boundaries by performing a segmentation process using at least one tomographic image data of the plurality of tomographic image data,
After the invalidation is performed, a motion contrast front image of the subject's eye is determined based on at least one of the plurality of layers classified based on the detected plurality of layer boundaries and the motion contrast value. Generating a;
A step of changing the threshold from an initial value in accordance with an instruction from an examiner,
Based on at least one of the plurality of layers determined according to an instruction from an examiner and a comparison result obtained by comparing again using a threshold obtained by the change, Generating a motion contrast front image of the optometry again.

Claims (16)

A step of acquiring a plurality of tomographic image data of the subject each showing a tomogram at substantially the same location of the subject,
Calculating a motion contrast using the pixel data corresponding to the calculated plurality of tomographic image data,
Comparing the motion contrast with a threshold,
A step of invalidating the motion contrast equal to or less than the threshold based on the result of the comparison,
After the invalidating step is performed, a step of generating a motion contrast image based on the motion contrast,
An image generation method, wherein the threshold value is variable or plural.   2. The method according to claim 1, wherein the step of calculating the motion contrast further includes a step of normalizing the motion contrast using an average value of corresponding pixel data of the plurality of tomographic image data used for the calculation. Image generation method. Setting a display range in the depth direction of the motion contrast image,
Displaying the motion contrast image based on the set display range, further comprising:
3. The image generation method according to claim 1, wherein the motion contrast image displayed according to the change of the display range is updated.   4. The image generating method according to claim 3, wherein in the step of setting the display range, the settable display range can be limited to a predetermined width in a depth direction. Further comprising a step of detecting a layer from the tomographic image data,
The image generation method according to claim 3, wherein the step of setting the display range is selectable based on the detected layer.   6. The image generation method according to claim 5, wherein in the step of setting the display range, an arbitrary layer can be selected based on the detected layer, and the number of selectable layers can be limited. . The subject is a fundus,
In the step of setting the display range, the upper layer of the retina can be selected, and the nerve fiber layer (NFL), the ganglion cell layer (GCL), the inner plexiform layer (IPL), the inner granular layer (INL), and the outer layer When any of the reticular layer (OPL), outer granular layer (ONL), and outer limiting membrane (ELM) is selected, at least one of the Ellipsoid Zone (EZ), the Interdigitation Zone (IZ), the RPE layer, and the choroid cannot be selected. 7. The image generation method according to claim 6, wherein: The subject is a fundus,
In the step of setting the display range, the lower layer of the retina can be selected, and the inner granular layer (INL), the outer plexiform layer (OPL), the outer granular layer (ONL), the outer limiting membrane (ELM), and the Ellipsoid Zone can be selected. (EZ), Interdigestion Zone (IZ), the retinal pigment epithelium (RPE) layer, and when any of the choroid is selected, at least nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), 7. The image generating method according to claim 6, wherein one of an inner granular layer (INL), an outer plexiform layer (OPL), an outer granular layer (ONL) and an outer limiting membrane (ELM) is made unselectable. The tomographic image data is three-dimensional tomographic image data,
In the step of calculating the motion contrast, a three-dimensional motion contrast is calculated,
In the step of generating the motion contrast image, the three-dimensional motion contrast is projected or integrated in the depth direction in the display range to generate a two-dimensional motion contrast image,
9. The image generation method according to claim 3, wherein in the step of displaying the motion contrast image, a two-dimensional motion contrast image is displayed.   10. The image generation method according to claim 9, wherein in the step of displaying the motion contrast image, a tomographic image at a position corresponding to a position specified on the motion contrast image is selected or generated from three-dimensional motion contrast and displayed. Further comprising the step of changing the threshold,
The method according to any one of claims 3 to 10, wherein a step of generating a motion contrast image and a step of displaying the motion contrast image are repeatedly executed according to the change of the threshold value. .   The image generation method according to claim 5, wherein the threshold is set for each of the detected layers.   The method according to claim 1, wherein the threshold is determined based on a motion contrast of a peripheral pixel of an image corresponding to the motion contrast to be compared with the threshold.   The image according to any one of claims 1 to 13, wherein a motion area and a non-motion area are estimated from a motion contrast histogram of a predetermined area, and the threshold is determined from the motion area histogram and the non-motion area histogram. Generation method. Acquisition means for acquiring a plurality of tomographic image data of the subject, each showing a tomogram at substantially the same location of the subject,
Calculating means for calculating a motion contrast using pixel data corresponding to the acquired plurality of tomographic image data;
Comparing means for comparing the motion contrast with a threshold,
Invalidation means for invalidating the motion contrast equal to or less than the threshold based on the result of the comparison,
After the invalidation, generating means for generating a motion contrast image based on the motion contrast,
An image generating apparatus comprising: a changing unit configured to change the threshold value.   A program for causing a computer to execute the image generation method according to claim 1.