JP2012071042A - Ultrasonic image diagnostic apparatus, ultrasonic image forming method, and program - Google Patents

Abstract

An ultrasonic diagnostic imaging apparatus, an ultrasonic image generation method, and a program for obtaining various property information and diagnostic information of each tissue are provided.
A region of interest is divided into two or more divided regions based on a local sound velocity value and feature information that is a characteristic of a sound velocity unique to a tissue set in advance, and information on the divided region of interest is used as region information. By having the area dividing unit to be generated, the above-described problem is solved.
[Selection] Figure 1

Description

  The present invention relates to an ultrasonic diagnostic imaging apparatus, an ultrasonic image generation method, and a program for transmitting an ultrasonic wave to a subject, receiving a reflected wave, and displaying an image, and more specifically, features of a sound speed value and a sound speed unique to a tissue. The present invention relates to an ultrasonic diagnostic imaging apparatus, an ultrasonic image generation method, and a program that divide into a plurality of regions based on the above, and obtain and display tissue property information for each divided region.

Conventionally, as one of the morphological images of the ultrasonic image, a B-mode image representing the shape (an image in which the amplitude of the ultrasonic echo is represented by the luminance of a point) has been used. However, there is a desire to use information other than the shape for diagnosis, and one of them is the speed of sound.
Since the speed of sound is effective acoustic information for diagnosing living tissues, lesions and their progress, etc., when doctors make an ultrasound diagnosis, it is proposed to measure the sound speed of a subject using various measurement methods. Has been. Attempts have also been made to measure sound velocity values (hereinafter referred to as local sound velocity values) in a part of the subject.

  For example, in Patent Document 1, by using a plurality of transmitting and receiving ultrasonic transducers and changing their angles and intervals, the intersecting region (region of interest) of the ultrasonic beam is set in the depth direction in the living body. It has been proposed to obtain a two-dimensional distribution of local sound velocity values in a living body by moving the intersection region in the direction along the body surface of the living body and obtaining a local sound velocity value.

  In Patent Document 2, based on the virtual sound velocity distribution, the sound ray path is set by changing the irradiation angle and the incident angle for each of the transmitting transducer and the receiving transducer, and the measured actual elapsed time, It has been proposed to obtain error data with respect to the set time required for the sound ray path, correct the sound ray distribution so as to minimize the error data, and obtain the sound speed from the corrected sound ray distribution.

  Patent Document 3 uses the Huygens principle to determine lattice points set in a region shallower than the region of interest in the subject and the optimum sound speed value in the region of interest, and based on the optimum sound speed value in the region of interest. Each grid obtained from the optimum sound speed value at each grid point based on the assumed sound speed by calculating the received wave received from the target area when the ultrasonic wave is transmitted to the target area and assuming the assumed sound speed in the target area An ultrasonic diagnostic apparatus is disclosed in which a received wave from a point is synthesized to obtain a synthesized received wave, and a local sound velocity value in a region of interest is determined based on the received wave and the synthesized received wave.

JP 62-254740 A Japanese Patent Laid-Open No. 5-95946 JP 2010-99452 A

  However, in Patent Documents 1 to 3, although the local sound speed distribution information of the subject can be obtained, how the obtained sound speed distribution information is presented as information that can be used for diagnosis so that a doctor can easily see it. Is not disclosed.

  An object of the present invention is to divide a region of interest based on a local sound velocity value and feature information that is a characteristic of a sound velocity unique to a tissue set in advance, obtain a tissue type of each divided region, By obtaining tissue property information that represents the characteristics of the distribution of sound velocity values, it provides a doctor with various property information of each tissue that cannot be obtained only by local sound velocity values, and an ultrasound diagnostic imaging device that contributes to the diagnosis. An object is to provide an image generation method and a program.

  In order to solve the above problems, the present invention has an ultrasonic probe that transmits an ultrasonic wave to a subject, receives a reflected wave, and outputs an ultrasonic detection signal, and obtains a local sound velocity value of a region of interest. In the ultrasonic diagnostic imaging apparatus, the region of interest is divided into two or more divided regions based on the local sound velocity value and feature information that is a characteristic of the sound velocity inherent to the tissue, and the divided region There is provided an ultrasonic diagnostic imaging apparatus having a region dividing unit that generates information on a region of interest as region information.

  Moreover, it is preferable that the said area | region division part divides | segments the said attention area | region into two or more division areas based on the said local sound speed value and the said characteristic information, and determines the structure | tissue to which each said division area corresponds.

Furthermore, it is preferable to have a tissue property information generating unit that generates tissue property information representing characteristics of the distribution of the local sound velocity values for one or more of the divided regions based on the region information and the local sound velocity values.
Furthermore, it is preferable to have a diagnostic information generation unit that generates diagnostic information including one or more of the type of lesion and the degree of lesion in each of the divided regions based on the tissue property information.

Moreover, it is preferable that one of the tissue property information in the divided region is information reflecting the other tissue property information.
Further, it is preferable that the tissue property information is information reflecting information set by a user.

Further, it is preferable that the tissue property information is further generated by reflecting the information on the tissue in the divided region.
Further, it is preferable that the tissue property information is generated again reflecting the diagnostic information.

  In order to solve the above problem, the present invention provides an ultrasonic image generation method for obtaining a local sound speed value of a region of interest by transmitting an ultrasonic wave to a subject and receiving a reflected wave, wherein the local sound speed value is obtained. A region dividing step of dividing the region of interest into two or more divided regions on the basis of feature information that is a characteristic of the speed of sound unique to the tissue set in advance, and generating information on the divided region of interest as region information A method for generating an ultrasonic image is provided.

  Moreover, in order to solve the said subject, this invention provides the program for making a computer perform as a procedure each step of the ultrasonic image generation method described above.

  According to the present invention, not only the local sound speed value for each divided area, but also the area tissue information indicating the tissue type of each divided area and the tissue property information indicating the characteristics of the distribution of local sound speed values are obtained. Furthermore, diagnostic information that contributes to the diagnosis of the doctor such as the type of lesion and the degree of lesion can be provided.

It is a block diagram which shows an example of a structure of one Embodiment of the ultrasonic image diagnostic apparatus which implements the ultrasonic image generation method which concerns on this invention. It is explanatory drawing which shows typically the calculation process of the local sound speed value which concerns on this invention. (A), (b) is a graph which shows an example of a setting sound speed profile. It is a flowchart which shows an example of the flow of a process of the ultrasonic image generation method of one Embodiment which concerns on this invention. 5 is a flowchart showing a continuation of the flowchart shown in FIG. 4. It is a flowchart which shows an example of the flow of a process which determines an environmental sound speed value. It is a flowchart which shows an example of the calculation process of the local sound speed value which concerns on this invention. It is explanatory drawing which shows an example of the setting of an attention area. It is explanatory drawing which shows an example of area division. It is explanatory drawing which shows an example of the display by which the tissue name was superimposed and displayed on each division area of a sound speed image. It is explanatory drawing which shows an example of the display on which the tissue name and the tissue property information were superimposed and displayed on each divided area of the sound velocity image. It is explanatory drawing which shows an example of the display by which the tissue name, the tissue property information, and the diagnostic information (lesion, progress degree) were superimposed and displayed on each divided region of the sound velocity image.

  An ultrasonic diagnostic imaging apparatus according to the present invention that implements an ultrasonic image generation method according to the present invention will be described in detail below based on preferred embodiments shown in the accompanying drawings. Note that the method of specifying the region of interest is not particularly limited, but in the following description, as an example, the region of interest is specified on the B-mode image, and the local sound speed value corresponding to each pixel in the region of interest of the B-mode image. The case of calculating will be described.

FIG. 1 is a block diagram of an embodiment showing a configuration of an ultrasonic diagnostic imaging apparatus according to the present invention.
1 includes an operation unit 12, a control unit 14, an ultrasonic probe 16, a transmission / reception unit 20, a signal processing unit 22, a sound speed value calculation unit 24, a sound speed image generation unit 26, and a region division. A unit 27, a tissue property information generation unit 34, a diagnosis information generation unit 36, an image processing unit 38, a display unit 40, and an RF data recording / reproducing unit 42.

The sound speed value calculation unit 24 includes an environmental sound speed value calculation unit 44 and a local sound speed value calculation unit 46. The environmental sound speed value calculation unit 44 includes a focus index calculation unit 48, an environmental sound speed profile generation unit 50, and an environmental sound speed value determination unit 52. The local sound speed value calculation unit 46 calculates a virtual received wave / virtual synthesized received wave error. Unit 54, error profile generation unit 56, and local sound velocity value determination unit 58.
The region dividing unit 27 includes a pixel organization determining unit 28, a region of interest dividing unit 30, and a divided region organization determining unit 32.

  The operation unit 12 is for an operator to perform various operations of the ultrasonic diagnostic imaging apparatus 10 and outputs operation information. The specific mode of the operation unit 12 is not particularly limited, and various known operation devices such as a keyboard, a mouse, and a touch panel may be used.

  The control unit 14 is for controlling the operation of each unit of the ultrasonic diagnostic imaging apparatus 10. In addition, a control signal (CTL) is output to each unit so that various processes are performed according to the operation information. In addition, a set sound speed or a reception delay pattern for obtaining the environmental sound speed value is set in the transmission / reception unit 20 described later.

  The ultrasonic probe 16 is a probe used in contact with a subject, and includes a plurality of ultrasonic transducers 18 constituting a one-dimensional or two-dimensional transducer array. The ultrasonic transducer 18 transmits an ultrasonic beam to the subject based on the drive signal applied from the transmission / reception unit 20, receives an ultrasonic echo reflected from the subject, and outputs a detection signal.

  The ultrasonic transducer 18 includes a vibrator having electrodes formed on both ends of a piezoelectric material (piezoelectric body). Examples of the piezoelectric body constituting the vibrator include a piezoelectric ceramic such as PZT (lead zirconate titanate) and a polymer piezoelectric element such as PVDF (polyvinylidene difluoride). Can be used. When an electric signal is sent to the electrodes of the vibrator and a voltage is applied, the piezoelectric body expands and contracts, and ultrasonic waves are generated in each vibrator by the expansion and contraction of the piezoelectric body. For example, when a pulsed electric signal is sent to the electrode of the vibrator, a pulsed ultrasonic wave is generated, and when a continuous wave electric signal is sent to the electrode of the vibrator, a continuous wave ultrasonic wave is generated. Then, the ultrasonic waves generated in the respective vibrators are combined to form an ultrasonic beam. Further, when an ultrasonic wave is received by each vibrator, the piezoelectric body of each vibrator expands and contracts to generate an electric signal. The electrical signal generated in each transducer is output to the transmission / reception unit 20 as an ultrasonic detection signal.

  As the ultrasonic transducer 18, a plurality of types of elements having different ultrasonic conversion methods can be used. For example, a transducer constituted by the piezoelectric body may be used as an element that transmits ultrasonic waves, and an optical transducer of an optical detection type may be used as an element that receives ultrasonic waves. Here, the light detection type ultrasonic transducer converts an ultrasonic signal into an optical signal for detection, and is, for example, a Fabry-Perot resonator or a fiber Bragg grating.

The transmission / reception unit 20 includes a transmission circuit, a reception circuit, and an A / D converter.
The transmission circuit generates a drive signal in accordance with a control signal from the control unit 14 and applies the drive signal to the ultrasonic transducer 18. At this time, the transmission circuit delays the drive signal applied to each ultrasonic transducer 18 based on the transmission delay pattern selected by the control unit 14. Here, the transmission circuit adjusts (delays) the timing of applying the drive signal to each ultrasonic transducer 18 so that the ultrasonic waves transmitted from the plurality of ultrasonic transducers 18 form an ultrasonic beam. Note that the timing of applying the drive signal may be adjusted so that the ultrasonic waves transmitted from the plurality of ultrasonic transducers 18 reach the entire imaging region of the subject.

The receiving circuit receives and amplifies the ultrasonic detection signal output from each ultrasonic transducer 18. Since the distances between the ultrasonic transducers 18 and the ultrasonic wave reflection sources in the subject are different, the time for the reflected wave to reach the ultrasonic transducers 18 is different. The reception circuit includes a delay circuit, and the difference (delay in arrival time) of the reflected wave according to the reception delay pattern set based on the sound speed selected by the control unit 14 (hereinafter referred to as assumed sound speed) or the distribution of sound speed. Each detection signal is delayed by an amount corresponding to (time).
Next, the reception circuit performs reception focus processing by matching and adding the detection signals given delay times. When there is another ultrasonic reflection source at a position different from the ultrasonic reflection source X, the arrival time of the ultrasonic detection signal from the other ultrasonic reflection source is different. The phases of the ultrasonic detection signals from the ultrasonic reflection sources cancel each other. As a result, the received signal from the ultrasonic wave reflection source X becomes the largest and is focused. By this reception focus processing, a sound ray signal (hereinafter referred to as an RF signal) in which the focus of the ultrasonic echo is narrowed is formed.

  In the A / D converter, an analog RF signal output from the receiving circuit is converted into a digital RF signal (hereinafter referred to as RF data) and output. Here, the RF data includes phase information of the received wave (carrier wave).

  In the signal processing unit 22, the RF data is subjected to correction of attenuation by distance according to the depth of the ultrasonic reflection position by STC (Sensitivity Time gain Control), and then subjected to envelope detection processing. Mode image data is generated and output.

  The sound velocity value calculation unit 24 designates a region of interest for a region where a local sound velocity value is to be obtained, and outputs region-of-interest designation information. The region of interest can be specified on a B-mode image, for example, and the entire B-mode image may be automatically set by default.

  The focus index calculation unit 48 receives B-mode image data and RF data for each set sound speed, and calculates a focus index for each set sound speed necessary for obtaining an environmental sound speed value for each pixel of the B-mode image. . When the focus index is calculated for a certain set sound speed, the focus index is calculated by changing the set sound speed. That is, focus indexes are calculated and output for all set sound speeds. As the focus index, for example, the contrast or sharpness of the image is used from the B-mode image data, or the period or amplitude of the ultrasonic detection signal at each pixel, and the beam width (half-value width) is used from the RF data.

  A focus index for all set sound speeds is input to the environmental sound speed profile generation unit 50 for each pixel of the B-mode image. The input focus index is plotted on a graph with the horizontal axis indicating the set sound speed and the vertical axis indicating the focus index, and a set sound speed profile (hereinafter referred to as an environmental sound speed profile) is generated and output.

The environmental sound speed value determination unit 52 receives the environmental sound speed profile obtained for each pixel of the B-mode image. Based on the input environmental sound speed profile, the optimum sound speed value of each pixel (hereinafter referred to as the environmental sound speed value) is determined and output. Here, the optimum sound speed value (environmental sound speed value) is the sound speed value at which the contrast, sharpness is highest, and the sound speed value at which the beam width is the narrowest, and the actual sound speed value (local sound speed value) at each pixel. Does not necessarily match.
In addition, as a method for obtaining the environmental sound speed value, for example, a method of determining from the contrast of the image, the spatial frequency in the scanning direction, dispersion, and the like (for example, JP-A-8-317926) may be used.

  The virtual received wave / virtual synthesized received wave error calculation unit 54 receives the B-mode image data and the environmental sound velocity value, and for each temporary local sound velocity necessary for obtaining the local sound velocity value for each pixel of the B-mode image. The error between the virtual received wave and the virtual combined received wave is calculated. That is, the error between the virtual received wave and the virtual synthesized received wave is calculated and output for all temporary local sound velocities.

  The error profile generation unit 56 receives an error between the virtual received wave and the virtual synthesized received wave for all temporary local sound velocities for each pixel of the B-mode image. The error between the input virtual received wave and the virtual synthesized received wave is plotted in a graph with the horizontal axis representing the tentative local sound velocity and the vertical axis representing the error between the virtual received wave and the virtual synthesized received wave to generate an error profile. Is output.

  The local sound speed value determination unit 58 receives an error profile obtained for each pixel of the B-mode image. Based on the input error profile, a local sound velocity value for each pixel is determined and output.

Here, the local sound speed value calculation processing will be described.
FIG. 2 is a diagram schematically showing a local sound speed value calculation process.

As shown in FIG. 2B, the lattice point representing the region of interest ROI in the subject OBJ is X _ROI , shallower than the lattice point X _ROI (that is, close to the ultrasonic transducer 18) in the XY direction, etc. Assume that the lattice points arranged at intervals are A1, A2,..., And at least the sound speed between the lattice point _XROI and each lattice point A1, A2,.

In this example, it is assumed that (T and delay time ΔT) of received waves from the lattice points A1, A2,... (W _A1 , W _A2 ,...) Are known, and the lattice points X _ROI and the lattice points A1, A2,. A local sound velocity value at the lattice point X _ROI is obtained from the positional relationship. Specifically, the principle of Huygens, received wave W _X and the lattice point from the lattice point X _ROI A1, A2, utilize the received wave W _SUM obtained by synthesizing the received waves from ... virtually coincide. The assumed sound speed value at which the difference between the received wave W _X and the virtual synthesized received wave W _SUM is minimized is defined as the local sound speed value at the lattice point X _ROI .

Here, the lattice points used in the calculation of the time for obtaining the local sound speed value at the lattice point X _ROI A1, A2, ... scope and number of determined in advance. Here, if the range of the lattice point used for the local sound speed value calculation is wide, the error of the local sound speed value becomes large, and if it is narrow, the error with the virtual received wave becomes large. Therefore, the range of the lattice point is determined based on these factors.

  The interval in the X direction between the lattice points A1, A2,... Is determined by the balance between the resolution and the processing time. The distance between the lattice points A1, A2,... In the X direction is, for example, 1 mm to 1 cm.

  If the distance between the grid points A1, A2,... In the Y direction is narrow, the error in the error calculation increases, and if it is wide, the error in the local sound speed value increases. The interval in the Y direction between the lattice points A1, A2,... Is determined based on the setting of the image resolution of the ultrasonic image. An interval in the Y direction between the lattice points A1, A2,... Is 1 cm as an example.

  Note that when the intervals between the lattice points A1, A2,... Are wide, it is difficult to calculate the composite wave, and fine lattice points may be generated by interpolation.

  The sound velocity image generation unit 26 receives a local sound velocity value obtained for each pixel of the region of interest (B mode image) and tissue property information described later. In the sound velocity image generation unit 26, a difference (difference sound velocity image) between a value corresponding to the local sound velocity value, for example, a sound velocity value (normal sound velocity image) of each pixel, an average value or a minimum value of sound velocity of the entire region of interest or the divided region ) And a sound speed value (dispersed sound speed image) normalized by dispersion is assigned to each pixel of the B-mode image to generate a sound speed image, which is output as sound speed image data. The diagnosis information is input to the sound speed image generation unit 26, and a difference from the average value of the sound speed based on the diagnosis information may be used, or the value corresponding to the local sound speed value is adjusted again so that the gradation can be easily expressed. You may go. Further, an image of a distribution of a difference from an average value of local sound speed values in a separately set reference region, an average value of local sound speed values set by an operator, or an average value of local sound speed values based on diagnostic information (difference sound speed image ).

  A local sound speed value of the entire region of interest is input to the pixel organization determination unit 28. In the pixel organization determination unit 28, the organization belonging to each pixel for the entire region of interest is determined based on the local sound velocity value and the feature information that is a characteristic of the sound velocity inherent to the tissue, and is output as pixel organization information. . For example, a feature amount (for example, an average value of local sound speed values) is obtained from a distribution of local sound speed values of pixels included in a predetermined range centered on a certain target pixel, and the feature amount is compared with feature information. The organization to which the target pixel belongs is determined. Note that the feature information can be obtained by previously obtaining a feature value of the sound speed distribution by a statistical method or the like and expressing it in a table or the like.

  Here, the feature amount of the target pixel is not limited to one type, and a plurality of feature amounts may be used. For example, one index may be calculated from a plurality of feature quantities by a multiple regression equation, and the organization to which the target pixel belongs may be determined based on the index. Examples of the plurality of feature amounts include an average value of local sound velocity values, a variance, a degree of concentration on the average value, a skewness or kurtosis of a histogram, an average of spatial frequencies, and a variance or band of spatial frequencies. . In addition, texture feature quantities such as co-occurrence matrices, such as uniformity, contrast, correlation, and entropy may be used. Note that the feature information may use the same feature amount.

In addition, if the target region and the scanning method are determined, the standard arrangement of each tissue is also determined, so not only the feature amount of the pixel of interest but also the probability of belonging to each tissue is determined by the position of the pixel of interest, The organization to which the target pixel belongs may be determined reflecting the probability.
Further, when the tissue to which the pixel of interest belongs is different from the tissue to which the surrounding pixels belong, it is possible to prevent the occurrence of an enclave by determining the tissue having the closest feature. Or, if it is only necessary to be able to determine the rough boundary of each area, it may be inconspicuous by reducing the resolution, etc., and if a detailed image is required, it may be abnormal, so it was decided The organization may be displayed as it is.

  The attention area dividing unit 30 receives sound velocity image data, pixel organization information, and attention area designation information. Based on the pixel organization information, the region of interest division unit 30 divides the region of interest into two or more divided regions so that adjacent pixels and the same tissue belong to the same divided region. The information of the attention area including information such as the boundary line of the divided areas, the number of divisions, and the attribute indicating which division area each pixel belongs to is generated and output as the attention area information.

  The divided region organization determination unit 32 receives pixel organization information and focus region information. In the divided region organization determination unit 32, the organization of each divided region is determined based on the pixel organization information (the organization of the pixels belonging to the divided region), added as region organization information to the region of interest information, and output as region information. Is done.

The tissue property information generation unit 34 receives a local sound velocity value, region information, and diagnostic information described below for the entire region of interest. The tissue property information generation unit 34 generates tissue property information based on the local sound velocity value of each pixel and the divided region to which the pixel belongs. The tissue property information is information representing the characteristics of the distribution of local sound speed values, for example, the average value, variance, degree of concentration on the average value, skewness or kurtosis of the histogram in each divided region. , Spatial frequency average, and spatial frequency variance or band. In addition, texture feature amounts such as co-occurrence matrixes, such as uniformity, contrast, correlation, and entropy, may be used, or the pixel organization information generated above may be used. Note that the tissue property information is generated separately from the feature amount obtained by the pixel organization determination unit 28.

  Further, a difference in tissue property information may be taken in one divided region and the other divided region. At this time, the reference region may be set based on the position of the divided region, or may be set based on the tissue property information. For example, if you want to obtain the difference between the average value of the local sound speed value of the liver and the average value of the local sound speed value of the subcutaneous fat, the subcutaneous fat is directly under the skin, and the average value of the sound speed is lower than that of other tissues. Since it is low, the shallowest divided area or the divided area having the lowest average sound speed may be determined as the subcutaneous fat and set as the reference area. Alternatively, a table may be used between a plurality of other divided areas instead of taking the difference. In addition, the reference area may be set by the operator, or the reference area may be set based on the positional relationship of the areas.

  In addition, when diagnostic information is input, that is, when diagnostic information is fed back with respect to the tissue property information generated once, the tissue property information is generated again reflecting the diagnosis information. For example, there are a case where diagnostic information of one divided region is used for generation of tissue property information of the other divided region, and a case where tissue characteristic information reflecting the diagnostic information is generated.

  The tissue property information is input to the diagnostic information generation unit 36. Based on the tissue property information, the diagnosis information generation unit 36 generates and outputs information such as the type of lesion such as fatty liver and cirrhosis and the degree of progression (F0 to F4) of cirrhosis as diagnosis information.

  B-mode image data, sound velocity image data, region information, tissue property information, and diagnostic information are input to the image processing unit 38. The image processing unit 38 has a DSC (Digital Scan Converter) function and superimposition (overlay) of various image data (B-mode image data and sound velocity image data) and various information (region information, tissue property information, and diagnostic information). ) Image processing functions such as display, highlighting, and mask processing. The image processing unit 38 outputs display image data subjected to DSC and image processing. Note that B-mode image data used for superimposed display or the like is preferably data at a set sound speed that provides the best focus of the entire image.

  In the DSC function, since the B-mode image data and the sound velocity image data have a scanning method different from the normal television signal scanning method, normal image data (for example, a television set) can be displayed on the display unit 40 described later. John signal is converted (raster conversion) into scanning data (NTSC image data).

  In the image processing function, for example, B-mode image data, sound speed image data, and a superimposed display image of various information are generated. By displaying region tissue information, tissue property information, and / or diagnostic information for each divided region on a B-mode image or a sound velocity image, a display image that assists a doctor's diagnosis is generated. For example, the average value of local sound speed values and / or the names of tissues (liver, kidney, fat, etc .: area tissue information) are displayed in each divided area on the sound speed image, or the area tissue information and local sound speed values are displayed. From the diagnosis information that the average value is within the range of the sound velocity value of cirrhosis, a display image on which display such as display of symbols (F0 to F4) indicating the degree of progress of cirrhosis or coloring is performed on the divided region is performed. Generated.

  Display image data is input and displayed on the display unit 40. The display unit 40 is configured by an FPD (Flat Panel Display) such as liquid crystal, plasma, organic EL (Electro Luminescence), or a CRT (Cathode Ray Tube). As the display unit 40, it is preferable to use a display having a large display area and a large number of pixels so that a plurality of images can be displayed side by side.

  The RF data recording / reproducing unit 42 receives RF data and information about the frame rate (for example, parameters indicating the depth of the reflection position of the ultrasonic wave, the density of the scanning line, and the visual field width) and records them in the internal cine memory. The RF data recording / reproducing unit 42 has two operation modes of a cine memory recording mode and a cine memory reproducing mode, and operates as a cine memory recording mode during normal observation (live mode), and RF data is recorded.

  The cine memory playback mode is a mode for displaying, analyzing and measuring an ultrasonic diagnostic image based on RF data stored in the cine memory. In the cine memory playback mode, the RF data stored in the cine memory is output to the signal processing unit 22 in accordance with the operation of the operator, and the operator uses the B mode based on the RF data recorded in the RF data recording / playback unit 42. Images, sound speed images, regional tissue information, tissue property information, and diagnostic information can be viewed.

  Next, the operation of the ultrasonic diagnostic imaging apparatus 10 according to the present invention for realizing the ultrasonic image generation method according to the present invention will be described.

4 and 5 are flowcharts showing an example of the processing flow of the ultrasonic diagnostic imaging apparatus according to the present invention.
First, a region (target region) for which region information and tissue property information and the like are to be acquired is selected by the operator. When the target region is selected, the tissue included in the target region and the characteristics of the sound speed unique to the tissue are set as feature information (step S6). In addition, even if the scanning method is the same, the observed tissue and cross-section are different, that is, the characteristics of the specific sound speed are different. For example, scanning methods such as scanning under the right radial arch and midline longitudinal scanning are also selected. You may be made to do.

  Next, a plurality of set sound speeds for obtaining the environmental sound speed value are selected by the control unit 14 and set for the transmission / reception unit 20 (step S8). Here, as the set sound speed, a plurality of sound speeds are selected and set from the range of sound speed in the human body (generally, 1400 m / s to 1650 m / s). The number of selected sound speeds (L) should be such that when plotted on a graph with the horizontal axis as the set sound speed and the vertical axis as the focus index, the graphs shown in FIGS. 3 (a) and 3 (b) can be drawn. That's fine. The set sound speed may be set by the operator.

  Subsequently, the operator brings the ultrasonic probe 16 into contact with the subject to transmit / receive ultrasonic waves, and an ultrasonic detection signal is output from the ultrasonic probe 16 (step S10). The ultrasonic detection signal is input to the transmission / reception unit 20, and reception focus processing or transmission / reception focus processing is performed for each set sound speed based on the reception delay pattern corresponding to the selected plurality of set sound speeds, and A / D (Analog / Digital) and output as RF data for each set sound speed (step S12).

  The RF data for each set sound speed is input to the signal processing unit 22, and after the attenuation by the distance is corrected according to the depth of the reflection position of the ultrasonic wave by the STC, the envelope detection process is performed, as shown in FIG. Such B-mode image data of the B-mode image is generated and output for each set sound speed (step S14).

The B-mode image data and the RF data for every set sound speed are input to the sound speed value calculation unit 24. In the sound speed value calculation unit 24, an area for which a local sound speed value is to be obtained in the B-mode image is designated as a region of interest (step S16). As the attention area, for example, as in the attention area 60 shown in FIG. 8, the entire B-mode image may be automatically specified by default, or a part of the B-mode image is automatically noticed. It may be set as an area. Further, a part of the B-mode image may be specified by operating the operation unit 12 by the operator. The region of interest is set with, for example, start point coordinates [x _min , y _min ] and end point coordinates [x _max , y _max ]. In the flowchart of FIG. 4, x is set as n to N and y is set as m to M as an example.
When the region of interest is set, a starting pixel of interest (for example, x = n, y = m) for starting the calculation of the environmental sound speed value is set (step S18), and the environmental sound speed value of the pixel of interest is calculated ( Step S20).

Here, the details of the calculation of the environmental sound speed value of the pixel of interest will be described with reference to the flowchart of FIG.
First, the number of selected sound speeds (number of set sound speeds) for obtaining the environmental sound speed value set in step S8 is set to an initial value C _i = 1 and a maximum value C _max = L (step S202). .

Then, the focus index of the set sound velocity _{C i} is calculated and output (step S204). As the focus index value, for example, the contrast and sharpness values of the B-mode image data are calculated and output. Note that a predetermined index may be calculated from the beam width of the RF data of the pixel of interest and output as a focus index.

When the calculation of the focus index is completed for C _i = 1 (initial value), the values of C _i and C _max (maximum value) are compared (step S206). When the value of C _i is less than C _max (step S206) "N") in S206, 1 is being added together in _{C i} (step S208), returns to the calculation of the focus index of the step S204. The calculation of the focus index (step S204) is repeated until C _i = C _max, and the focus index is calculated and output for all set sound speeds of the pixel of interest.

  The focus index for all the set sound speeds of the target pixel is input to the environmental sound speed profile generation unit 50, plotted on a graph with the horizontal axis as the set sound speed and the vertical axis as the focus index, and the environmental sound speed profile is generated and output. (Step S210).

  The environmental sound speed profile is input to the environmental sound speed value determination unit 52. For example, if the environmental sound speed profile is as shown in FIG. 3A, the set sound speed value of the maximum value of the focus index is determined and output as the environmental sound speed value. (Step S212).

When the calculation of the environmental sound speed value of the pixel of interest is completed, that is, when step S20 is completed, the y coordinate value of the pixel of _interest is compared with y _max (step S22), and when the value of y is less than y _max (step S22) "N" in S22), 1 is added to y (step S24), and the process returns to the calculation of the environmental sound speed value of the pixel of interest in step S20. The calculation of the environmental sound speed value of the pixel of interest (step S20) is repeated until y = y _max .

When y = y _max (“Y” in step S22), the value of the x coordinate of the pixel of _interest is compared with x _max (step S26), and when the value of x is less than x _max (“N” in step S26) ”), 1 is added to x (step S28), the value of the y coordinate is set to y _min (y = m) (step S30), and the process returns to the calculation of the environmental sound speed value of the target pixel in step S20. That is, assuming that the y coordinate direction is a line, when the environmental sound speed value of the first line whose x coordinate is n is calculated, the x coordinate is incremented by 1 (n + 1), and the environmental sound speed value of the second line is calculated. The The calculation of the environmental sound speed value of the target pixel (step S20) is repeated for the entire target area (up to x = x _max (x = N), y = y _max (y = M)) until the environmental sound speed value is calculated. It is.
When the environmental sound velocity value is calculated for the entire region of interest, the environmental sound velocity value for the entire region of interest is output from the environmental sound velocity value calculation unit 44.

  The environmental sound speed value of the entire region of interest is input to the local sound speed value calculation unit 46. In the local sound speed value calculation unit 46, a start target pixel (for example, x = n, y = m) for starting the calculation of the local sound speed value is set (step S32), and the local sound speed value of the target pixel is calculated (step S32). Step S34).

Here, the details of the calculation of the local sound velocity value of the pixel of interest will be described with reference to the flowchart of FIG.
First, based on the environmental sound speed value at the lattice point _{X ROI,} the waveform of the virtual receiving wave _{W X} when the lattice point _{X ROI} and the reflection point is calculated (step S302).

Next, the initial value of the assumed sound speed at the lattice point X _ROI is set (step S304). Then, the assumed sound speed is changed by one step (step S306), and a virtual combined received wave _WSUM is calculated (step S308). When the local sound speed value at the lattice point _{X ROI} is assumed by V, ultrasound lattice points having propagated from the lattice point _{X ROI} A1, A2, the time to reach ... to _{X ROI A1 / V, X ROI} A2 / V, ... Here, X _ROI A1, X _ROI A2,... _Are the distances between the lattice points A1, A2 _,. Since the environmental sound velocity values at the lattice points A1, A2,... Are known up to step S26 in FIG. 4, the received waves from the lattice points A1, A2,. Therefore, the virtual composite received wave _WSUM is obtained by synthesizing the reflected waves (ultrasonic echoes) emitted from the lattice points A1, A2,... With the delays _XROI A1 / V, _XROI A2 / V _,. Can do.

Actually, since the above processing is performed on the element data (RF signal), the time (T1, T2,...) From the lattice point _XROI to the lattice points A1, A2,. It is represented by (1). Here, X _A1 , X _A2 ,... _Are distances in the scanning direction (X direction) between the lattice points A 1, A 2,. Δt is a time interval in the Y direction of the lattice points.

The T1, T2, ..., the lattice point _{X ROI} and same sound ray from the lattice point An Time to reach the grid point _{X ROI (Δt} / 2) each grid point in the delay plus A1, A2, ... from By synthesizing the received wave, a virtual synthesized received wave _WSUM can be obtained.

Here, when the lattice points are set at equal intervals (Δt) on the time axis in the Y direction, the intervals in the space are not necessarily equal. Therefore, when calculating the time until the ultrasonic wave reaches each lattice point, Δt / 2 corrected in Equation (1) instead of Δt / 2 may be used. Here, the corrected Δt / 2 is, for example, a value obtained by dividing the difference in depth (distance in the Y direction) of A1, A2,... Compared with the lattice point X _ROI and the lattice point An of the same sound line by V. A value obtained by adding / subtracting from / 2. The depth of each lattice point A1, A2,... Is obtained because the local sound velocity value is known at a lattice point shallower than that.

Further, the virtual composite received wave _WSUM is calculated from predetermined pulse waves (W _A1 , W _A2 , respectively) actually emitted from the lattice points A1, A2,... With delays X _ROI A1 / V, X _ROI A2 / V _,. , ...) are superimposed.

Next, the error of the assumed resultant received wave _{W SUM} is calculated and the virtual reception wave _{W X} (step S310). Error between the virtual receiving wave W _X assumed resultant received wave W _SUM is a method of cross-correlating with each other, the method over a delay obtained from the assumed resultant received wave W _SUM to the virtual receiving wave W _X phase matching addition or Conversely over a delay obtained assumed resultant received wave W _SUM from the virtual receiving wave W _X is calculated by the method of phase matching addition. Here, in order to obtain a delay from the virtual received wave W _X , the lattice point X _ROI is used as a reflection point, and the time at which the ultrasonic wave propagated at the sound velocity V arrives at each element may be set as the delay. Further, in order to obtain a delay from the virtual combined received wave _WSUM , an equiphase line is extracted from the phase difference of the combined received wave between adjacent elements, and the equal phase line is used as a delay, or simply, The phase difference of the maximum (peak) position of the combined received wave may be used as the delay. Further, the cross-correlation peak position of the combined received wave from each element may be set as a delay. The error at the time of phase matching addition is obtained by a method of setting the peak to peak of the waveform after the matching addition or a method of setting the maximum value of the amplitude after the envelope detection.

Next, Steps S306 to S310 are repeated, and when the calculation is completed for all assumed sound speed values (“Y” in Step S312), the local sound speed value at the lattice point X _ROI is determined (Step S314). When the Huygens principle is strictly applied, the waveform of the virtual synthesized received wave W _SUM obtained in step S308 is a virtual received wave (reflected wave) W _X when the local sound velocity value at the lattice point X _ROI is assumed to be V. It becomes equal to the waveform. At step S314, the determined value of the assumed sound speed difference between the virtual receiving wave _{W X} and the assumed resultant received wave _{W SUM} is minimized and local sound speed value at the lattice point _{X ROI.}

The above method (assumed resultant received waveform calculation, error calculation and virtual reception waveform, sound speed determination), instead of the lattice points X _ROI of ambient sound velocity value and the lattice points A1, A2, ... ambient sound velocity value as input A table that outputs sound speed values at the grid point X _ROI may be used.
Alternatively, the local sound speed value may be determined a plurality of times using different intervals and different ranges of grid points.

When the calculation of the local sound velocity value of the pixel of interest is completed, that is, when step S34 is completed, the y coordinate value of the pixel of _interest is compared with y _max (step S36), and if the value of y is less than y _max (step S36) "N" in S36), 1 is added to y (step S38), and the process returns to the calculation of the local sound speed value of the pixel of interest in step S34. The calculation of the local sound velocity value of the pixel of interest (step S34) is repeated until y = y _max .

When y = y _max (“Y” in step S36), the value of the x coordinate of the pixel of _interest is compared with x _max (step S40), and when the value of x is less than x _max (“N” in step S40) ”), 1 is added to x (step S42), the value of the y coordinate is set to y _min (y = m) (step S44), and the process returns to the calculation of the local sound speed value of the pixel of interest in step S34. That is, assuming that the y coordinate direction is a line, when the local sound speed value of the first line whose x coordinate is n is calculated, the x coordinate is incremented by 1 (n + 1), and the local sound speed value of the second line is calculated. The The calculation of the local sound velocity value of the pixel of interest (step S34) is repeated for the entire region of interest (up to x = x _max (x = N), y = y _max (y = M)) until the local sound velocity value is calculated. It is.
When the calculation of the local sound velocity value is completed for the entire region of interest, the sound velocity value calculation unit 24 outputs the local sound velocity value of the entire region of interest and the region of interest designation information.

  The local sound speed value of the entire region of interest is input to the sound speed image generation unit 26. The sound speed image generation unit 26 generates a sound speed image from the local sound speed value of the entire region of interest and outputs it as sound speed image data (step S46).

  Further, the local sound velocity value of the entire region of interest is also input to the pixel organization determination unit 28. Based on the local sound velocity value and the feature information, the pixel organization determination unit 28 determines the organization that belongs to each pixel for the entire region of interest and outputs it as pixel organization information (step S48).

  The sound speed image data, the pixel organization information, and the attention area designation information are input to the attention area dividing section 30. In the region-of-interest dividing unit 30, the region of interest is divided into two or more divided regions so that pixels having the same tissue as the adjacent pixels of the sound velocity image belong to the same divided region based on the pixel organization information. Also, information on the region of interest including information such as the boundary line of each divided region, the number of divisions, and the attribute indicating which division region each pixel belongs to is generated and output as the region of interest information. (Step S50).

  FIG. 9 shows an example of area division. FIG. 9 is a sound velocity image when the entire B-mode image is designated as the region of interest, and the organization of the pixel tissue information is different from the dotted line 66 at the substantially central portion of the sound velocity image. By this dotted line 66, the sound velocity image is divided into upper and lower parts to be divided areas 62 and 64.

  The pixel organization information and the attention area information are input to the divided area organization determining unit 32. In the divided region organization determination unit 32, the organization of each divided region is determined based on the pixel organization information, added to the region of interest information as region organization information, and output as region information (step S52). For example, in the above example, region tissue information that the divided region 62 is fat and the divided region 64 is the liver is added.

  The region information is input to the tissue property information generation unit 34 together with the local sound velocity value of the entire region of interest. In the tissue property information generation unit 34, tissue property information is generated based on the local sound velocity value of each pixel and the divided region to which the pixel belongs (step S54). For example, in the sound speed image of FIG. 9, when the average value of local sound speed values in the divided area 62 is 1450 m / sec and the average value of local sound speed values in the area 64 is 1555 m / sec, the tissue property information of the divided area 62 is obtained. Organizational property information such as “average value of local sound speed value: 1450 m / sec” and “average value of local sound speed value: 1555 m / sec” as the tissue property information of the divided region 64 is generated.

  When the tissue property information is generated, if further diagnosis information is necessary (“Y” in step S56), the tissue property information is input to the diagnosis information generation unit 36, and the diagnosis information is generated based on the tissue property information. Is output (step S58). The diagnosis information represents the type of lesion and / or the extent (progression level) of the lesion. For example, the information on the progression level of the lesion is generated by a table in which the range of local sound speed values for each progression degree of the lesion is recorded. As the degree of progression of the lesion, for example, an index such as F0 to F4 representing the degree of progression of cirrhosis can be used. In the example of the divided area 64 described above, since the local sound speed value of the divided area 64 is 1555 m / sec, for example, diagnostic information indicating that “the progression degree of cirrhosis: F0” is generated. It should be noted that the range of the local sound velocity values used in the table may be statistically obtained in advance as with the tissue name.

  The diagnosis information may be fed back to the tissue property information generation unit 34 and reflected in the tissue property information. Further, for example, when regional tissue information called liver is generated, a difference between tissue property information of the divided region and normal liver tissue property information may be taken.

  B-mode image data, sound velocity image data, region information, tissue property information, and diagnostic information are input to the image processing unit 38. In the image processing unit 38, various types of input image data are converted into normal image data, various image data are superimposed and displayed, tissue property information and / or diagnostic information is superimposed and displayed on various image data, highlighting, Then, mask processing and the like are performed, display image data is generated, and is output and displayed on the display unit 40 (step S60).

Here, an example of display image data displayed on the display unit 40 will be given. As shown in FIG. 10, only the regional tissue information may be displayed on the sound velocity image, or as shown in FIG. 11, the average value of the local sound velocity values of each divided region is displayed as the tissue property information. You may do it. In addition, as shown in FIG. 12, the type of lesion and the degree of progression (F0 in the figure) may be displayed. At this time, if the divided area is small, the organization name may be omitted and only the progress degree may be displayed.
In addition, various colors such as modulating the color (brightness, hue, saturation) of a sound speed image, displaying various images individually or side by side, displaying only necessary portions, displaying in an enlarged or reduced manner, etc. A display method may be used.

  Further, the display mode of the various display images may be arbitrarily switched by the operator via the operation unit 12.

  As described above, without using a configuration for transmitting and receiving a dedicated ultrasonic wave for measuring the local sound velocity value, not only the local sound velocity value for each divided region, but also the tissue type of each divided region is determined. The region tissue information to be represented and the tissue property information representing the characteristics of the distribution of local sound velocity values can be obtained, and further diagnostic information that contributes to the diagnosis of the doctor such as the type of lesion and the degree of lesion can be provided.

  The dimension of the region of interest may be any one of one dimension (sound ray), two dimensions (B mode image: plane), three dimensions (solid), and four dimensions (adding a time axis to the solid). Can be either as well. For example, in one dimension, there are A mode display in which a sound ray signal is displayed as it is, and profile display in which a B mode image is cut by a straight line orthogonal to the sound ray. In 3D, a B-mode image is added with information in the depth direction about the region of interest, and in 4D, a time axis is added and displayed as a moving image.

Further, the region organization information may be reflected in the tissue property information. For example, the difference between the normal tissue property information of the tissue obtained from the region tissue information may be taken as new tissue property information.
Furthermore, information set by the operator may be reflected in the tissue property information. For example, when the liver is set by the operator, a difference from the tissue property information of the normal liver may be taken. Thereby, for example, the progress of cirrhosis can be shown more easily.

In the above embodiment, a table is used to generate diagnostic information. However, when generating diagnostic information based on a plurality of tissue property information, a derived equation such as a multiple regression equation may be used. .
Further, for each divided area displayed on the display image, a selection button may be provided on the screen to display only the divided area required by the operator.
In each of the above embodiments, the sound velocity image is generated by assigning the local sound velocity value to each pixel of the B-mode image. However, the present invention is not limited to this, and the pixel of the sound velocity image is one-to-one with the pixel of the B-mode image. It does not have to correspond. For example, four pixels of the B-mode image may be used as one pixel of the sound speed image.

  In the above embodiment, the operation during normal observation (live mode) has been described. However, based on the RF data recorded in the RF data recording / reproducing unit 42, a B-mode image and a sound speed image are generated. May be.

In the present invention, each step of the above-described ultrasonic image generation method may be configured as an ultrasonic image generation program for causing a computer to execute, or the computer may be configured as each step of the ultrasonic image generation method. As each means for implementing the above, or as an ultrasonic image generation program that functions as each means constituting the above-described ultrasonic image diagnostic apparatus.
Further, the present invention may be configured as a computer-readable medium or a computer-readable memory for the above-described ultrasonic image generation program.

  The ultrasonic diagnostic imaging apparatus, the ultrasonic image generation method, and the program according to the present invention have been described in detail above. However, the present invention is not limited to the above-described embodiment, and the scope of the present invention is not deviated. Various improvements and changes may be made.

DESCRIPTION OF SYMBOLS 10 Ultrasonic image diagnostic apparatus 12 Operation part 14 Control part 16 Ultrasonic probe 18 Ultrasonic transducer 20 Transmission / reception part 22 Signal processing part 24 Sound speed value calculation part 26 Sound speed image generation part 27 Area division part 28 Pixel structure determination part 30 Attention Region division unit 32 Division region organization determination unit 34 Tissue property information generation unit 36 Diagnostic information generation unit 38 Image processing unit 40 Display unit 42 RF data recording / playback unit 44 Environmental sound speed value calculation unit 46 Local sound speed value calculation unit 48 Focus index calculation unit DESCRIPTION OF SYMBOLS 50 Environmental sound speed profile production | generation part 52 Environmental sound speed value determination part 54 Virtual reception wave / virtual synthetic | combination reception wave calculation part 56 Error profile generation part 58 Local sound speed value determination part 60 Region of interest 62, 64 Division area 66 Dotted line ( Representing dotted line)

Claims (10)

An ultrasonic diagnostic imaging apparatus that has an ultrasonic probe that transmits an ultrasonic wave to a subject, receives a reflected wave, and outputs an ultrasonic detection signal, and obtains a local sound velocity value of a region of interest,
Based on the local sound speed value and feature information that is a characteristic of the sound speed unique to the tissue set in advance, the region of interest is divided into two or more divided regions, and information on the divided region of interest is generated as region information. An ultrasonic diagnostic imaging apparatus comprising an area dividing unit that performs the above-described process.   The region dividing unit divides the region of interest into two or more divided regions based on the local sound velocity value and the feature information, and determines an organization to which each divided region corresponds. Item 2. The ultrasonic diagnostic imaging apparatus according to Item 1.   Furthermore, the system has a tissue property information generating unit that generates tissue property information for one or more of the divided regions based on the region information and the local sound velocity value. The ultrasonic diagnostic imaging apparatus according to claim 1 or 2.   The diagnostic information generation unit according to claim 3, further comprising: a diagnostic information generation unit configured to generate diagnostic information including at least one of a lesion type and a lesion degree in each of the divided regions based on the tissue property information. The ultrasonic diagnostic imaging apparatus described in 1.   5. The ultrasonic diagnostic imaging apparatus according to claim 3, wherein one tissue property information of the divided regions is information reflecting the other tissue property information. 6.   The ultrasonic image diagnostic apparatus according to claim 3, wherein the tissue property information is information reflecting information set by a user.   The ultrasonic image diagnostic apparatus according to claim 3, wherein the tissue property information is further generated by reflecting information on a tissue in the divided region.   The ultrasonic image diagnostic apparatus according to claim 3, wherein the tissue property information is generated again by reflecting the diagnostic information. An ultrasonic image generation method for transmitting an ultrasonic wave to a subject, receiving a reflected wave, and obtaining a local sound velocity value of a region of interest,
Based on the local sound speed value and feature information that is a characteristic of the sound speed unique to the tissue set in advance, the region of interest is divided into two or more divided regions, and information on the divided region of interest is generated as region information. An ultrasonic image generation method characterized by comprising an area dividing step.   The program for making a computer perform each step of the ultrasonic image generation method of Claim 9 as a procedure.