Ultrasonic diagnostic apparatus, ultrasonic image processing method, information processing program product, and recording medium

Abstract

The present disclosure provides an ultrasonic diagnostic apparatus, an ultrasonic image processing method, an information processing program product, and a recording medium. The ultrasonic diagnostic apparatus detects a homogeneous region (214) of liver tissue from a B-mode image (210) and measures a superficial layer thickness between a body surface and the homogeneous region (214). Next, the ultrasonic diagnostic apparatus determines an upper limit depth of a ROI, i.e., a measurement target region, according to the superficial layer thickness. The upper limit depth is calculated using a coefficient determined in a manner that multiple reflections between the body surface and a liver surface are sufficiently attenuated. The ultrasonic diagnostic apparatus sets the ROI for various measurements within the homogeneous region and at a depth range up to the calculated upper limit depth.

Description

Technical Field

[0001] This disclosure relates to an ultrasound diagnostic device, and more particularly to a process for setting up a tissue property measurement area. Background Technology

[0002] As measurement modes for diffuse liver disease in ultrasound diagnostic devices, SWE (Shear Wave Elastography) and ATT (Attenuation Imaging) are widely known. SWE is a technique for measuring tissue elasticity. In SWE, a shear wave is excited in the tissue of the patient by transmitting a burst wave, and the propagation velocity of the shear wave is measured. Then, based on the measurement result of the propagation velocity, the elastic modulus (in kPa) of each part of the tissue is calculated. ATT is a technique for measuring tissue attenuation. In ATT, the amplitude of the transmitted signal of the longitudinal wave propagating along the depth direction is measured within a specified depth range, and the attenuation rate (in dB / MHz / cm) is calculated based on the measurement result. Patent Document 1 discloses a high-performance ultrasound diagnostic device equipped with both SWE and ATT.

[0003] In order to perform these measurements properly, it is necessary to set the Region of Interest (ROI) to avoid structures such as subcutaneous tissue or blood vessels. Previously, this ROI setting was done manually by the examiner, requiring a significant amount of time and effort.

[0004] Patent Document 2 discloses a method for supporting the selection of a Region of Interest (ROI) suitable for quantification of liver fat in ultrasound diagnosis of the liver. In this method, for example, a map representing the uniformity of ultrasound images is generated, and if the user selects an ROI containing an uneven distribution of liver fat for quantification of liver fat, a visual or auditory warning is provided (e.g., paragraphs 0010-0011 and 0031-0032 of Patent Document 2).

[0005] In paragraph 0075 of patent document 3 and Figure 7 The diagram shows that in the display of the ultrasound diagnostic device, an imaging ROI is set in the B-mode image, and an elastic image is overlaid on the imaging ROI. A first measurement ROI is overlaid on the elastic image. Furthermore, the average value and standard deviation (SD value) of the shear rate within the first measurement ROI are displayed on the screen.

[0006] The ultrasound diagnostic apparatus disclosed in Patent Document 4 shows that a region of interest including the liver boundary line is set in an ultrasound image related to the liver, and an index representing the degree of concavity and convexity of the liver boundary line is calculated based on the image within the region of interest (e.g., paragraphs 0043-0048 of Patent Document 4).

[0007] Patent Document 1: Japanese Patent Application Publication No. 2024-117427

[0008] Patent Document 2: Japanese Patent Publication No. 2024-522311

[0009] Patent Document 3: Japanese Patent Application Publication No. 2020-138017

[0010] Patent Document 4: Japanese Patent Application Publication No. 2011-143062 Summary of the Invention

[0011] As a method for automatically setting the target area for organ tissue property measurement, one could consider finding a homogeneous region within the organ from ultrasound images and automatically setting the target area within that homogeneous region. However, if the target area is set only within a homogeneous region, the measurement may sometimes be adversely affected by multiple reflections of ultrasound waves generated between the body surface and the organ surface.

[0012] An ultrasound diagnostic apparatus according to one aspect of this disclosure is characterized by comprising a processor that performs the following processing: extracting a homogeneous region of an organ from an ultrasound image; determining the depth of the organ's surface relative to the body surface based on the ultrasound image; and setting an object region for tissue property measurement within the homogeneous region based on the depth.

[0013] In one embodiment, the ultrasonic diagnostic device is characterized in that, in setting the target area, the processor performs the following processing: determining the depth of influence of multiple reflections based on the depth of the surface of the organ; and setting the target area at a position deeper than the depth of influence of the multiple reflections.

[0014] Here, it can be set that the influence depth of the multiple reflections is determined based on the depth of the surface and a coefficient, wherein the coefficient is a coefficient greater than or equal to 1, and the deeper the surface, the smaller the coefficient.

[0015] Alternatively, the coefficients can be set to be calculated using an exponential function with a base greater than 0 and less than 1.

[0016] Furthermore, the coefficient can be a value between 1.5 and 2.5.

[0017] Furthermore, in one embodiment, the measurement includes shear wave elastography and attenuation imaging, and in setting the object region, the processor performs the following process: configuring the object region with respect to the shear wave elastography and the object region with respect to the attenuation imaging in a manner that overlaps with each other.

[0018] Here, the object region for the attenuation imaging can be a longitudinal region.

[0019] Furthermore, the processor may be configured to perform the following processing in setting the object region: determine the position of the object region with respect to the attenuation imaging as a position deeper than the influence depth of the multiple reflections; and set the position of the object region with respect to the shear wave elastic imaging based on the determined position of the object region with respect to the attenuation imaging.

[0020] Furthermore, the measurement may include backscatter analysis, in which the processor performs the following processing in setting the object region: the region set as the object region with respect to the attenuation imaging is also set as the object region with respect to the backscatter analysis.

[0021] Furthermore, in another embodiment, whenever an ultrasonic image is obtained through repeated ultrasonic measurements, the processor performs the following processing: extracting the homogeneous region from the obtained ultrasonic image, calculating the depth of the surface relative to the body surface, and setting the object region; performing tissue property measurements with respect to the set object region; storing data representing the results of the performed measurements in a storage device; and performing processing for selecting and displaying a preset number of data that meet a preset accuracy index from the data obtained in each of the measurements stored in the storage device.

[0022] Furthermore, in another embodiment, the tissue property measurement is at least one of shear wave elastography, attenuation imaging, and backscattering analysis.

[0023] Furthermore, the program involved in this disclosure is a program for causing a computer to perform the following processes: extracting a homogeneous region of an organ from an ultrasound image; determining the depth of the organ's surface relative to the body surface based on the ultrasound image; and setting an object region for tissue property measurement within the homogeneous region based on the depth.

[0024] -Invention Effects-

[0025] According to this disclosure, compared to setting the measurement object area solely based on the condition of a homogeneous region of an ultrasound image, it is expected to mitigate the adverse effects of multiple reflections of ultrasound waves between the body surface and organ surface during measurement. Attached Figure Description

[0026] Figure 1 This is a diagram illustrating the functional structure of an ultrasound diagnostic device according to an embodiment.

[0027] Figure 2 It is a graph used to illustrate the relationship between the B-mode image and the ROIs used for measurement.

[0028] Figure 3 This is a graph illustrating the relationship between the upper limit depth coefficient of the ROI and the shallow layer thickness.

[0029] Figure 4 This is a diagram illustrating the measurement and processing procedure.

[0030] Figure 5 This is a diagram illustrating the process of setting the ROI.

[0031] Figure 6 This is a diagram illustrating a variation of the ROI setting process.

[0032] Figure 7 This is a diagram illustrating a variation of the measurement and processing procedure.

[0033] Symbol Explanation

[0034] 10-Probe, 30-Display unit, 40-External input unit, 100-Ultrasound diagnostic device, 110-Transmit / receive control unit, 120-Signal processing unit, 130-Memory, 140-Image processing unit, 150-Image memory, 160-Measurement unit, 162-Measurement processing, 164-Homogeneous region determination processing, 166-ROI setting, 168-Statistical analysis. Detailed Implementation

[0035] Hereinafter, with reference to the accompanying drawings, a method for implementing this disclosure (hereinafter referred to as an embodiment) will be described.

[0036] Figure 1 The functional structure of the ultrasonic diagnostic apparatus according to this embodiment is illustrated below. The ultrasonic diagnostic apparatus includes a probe 10, a transceiver control unit 110, a signal processing unit 120, a memory 130, an image processing unit 140, an image memory 150, and a measurement unit 160.

[0037] The probe 10 contains multiple transducers arranged along the transducer surface. Ultrasonic waves are transmitted from each transducer within the probe 10 under the control of the transmit beamformer 112 within the transmit control unit 110, thereby forming a transmitted ultrasonic beam within the inspection object 20. Furthermore, each transducer within the probe 10 converts reflected waves from the inspection object 20 for the transmitted ultrasonic beam into an electrical received signal. The receive beamformer 114 within the transmit control unit 110 forms a received ultrasonic beam by delaying and summing the received signals output from each transducer. The receive beamformer 114 outputs a received beam signal representing the echo corresponding to each formed received ultrasonic beam. The signal processing unit 120 performs signal processing on the input received beam signal, including bandpass filtering 122, detection 124, logarithmic compression 126, and gain adjustment 128. The memory 130 is a storage device used as a working area for the processing of the signal processing unit 120. The signal output from the signal processing unit 120 is input to the image processing unit 140 and the measurement unit 160.

[0038] The image processing unit 140 generates an ultrasound image, such as a B-mode image, by performing known image processing, including image filtering, on the signal output from the signal processing unit 120. The generated ultrasound image is stored in the image memory 150 and displayed on the display unit 30.

[0039] The measurement unit 160 performs processing for tissue property measurements of organs such as SWE or ATT. The processing performed by the measurement unit 160 includes measurement processing 162, homogeneous region determination processing 164, ROI setting 166, statistical analysis 168, etc.

[0040] Measurement processing 162 performs control and data analysis for measuring ATT or SWE, etc. For example, measurement processing 162 controls the transmission and reception of the ultrasonic beam used for measurement. Furthermore, measurement processing 162 performs known data analysis for ATT or SWE on the received signals obtained through its transmission and reception.

[0041] Homogeneous Region Determination Process 164 Homogeneous regions are determined or detected from ultrasound images such as B-mode images. A homogeneous region is an area in the image whose characteristics are considered homogeneous. Regions where a speckled pattern is observed (hereinafter referred to as speckled regions) are representative examples of homogeneous regions. A speckled pattern refers to a granular pattern formed by the interference of scattered ultrasound signals caused by tiny reflectors dispersed in living tissue. For example, in the case of the liver, depending on differences in tissue state, such as the difference between a normal liver and a liver with fibrosis progression, the frequency band or intensity of scattering changes, and the speckled pattern also changes. Furthermore, homogeneous regions are not limited to speckled regions. Any area exhibiting a periodically repeating pattern with a certain fine cycle within a certain width (e.g., several centimeters square) is considered a homogeneous region.

[0042] Various methods have been proposed in the past and will be developed in the future for the determination of homogeneous regions. The homogeneous region determination process 164 can use any of these past methods or future methods. For example, the homogeneous region determination process 164 can use local feature quantities of the image to determine homogeneous regions, or it can use artificial intelligence techniques such as machine learning models.

[0043] ROI setting 166 defines an ROI for tissue property measurement within the region of the organ being measured in the ultrasound image. Here, the ROI is set within a determined homogeneous region. In this embodiment, the ROI is set based on the superficial layer thickness between the probe 10 and the organ being measured. Superficial layer thickness is the thickness of the body surface tissue between the body surface contacted by the probe 10 and the organ being measured. Therefore, superficial layer thickness can be considered the depth of the organ's surface relative to the body surface. Setting the ROI based on the superficial layer thickness is to sufficiently reduce the influence of multiple reflections of ultrasound waves between the body surface and the organ surface.

[0044] Normally, ultrasound waves transmitted from the body surface propagate through repeated scattering or reflection by tiny scatterers within the living body. However, at the boundary between the probe and surface tissues (such as fascia or collagen membrane) or the liver surface, multiple reflections of the ultrasound signal occur between the boundaries. This multiple reflection results in a virtual image in ultrasound measurements. It is known in principle that virtual images are generated at depths that are integer multiples of the depth of the boundary where multiple reflections occur. Furthermore, the ultrasound signal attenuates according to the effective propagation distance during repeated multiple reflections. The greater the thickness of the superficial layer, the longer the effective propagation distance accompanied by multiple reflections, and correspondingly, the smaller the effect of the virtual image caused by multiple reflections.

[0045] Therefore, ROI setting 166 calculates the superficial layer thickness from the ultrasound image, determines a suitable depth range for the ROI based on this superficial layer thickness and prescribed rules, and sets the ROI within this depth range. Details regarding ROI setting will be explained in detail later.

[0046] Statistical analysis 168 performs statistical analysis on the results of measurements such as ATT and SWE performed in measurement processing 162. The analysis performed in statistical analysis 168 will be explained in detail later.

[0047] Display unit 30 displays the display screen generated by ultrasonic diagnostic device 100.

[0048] The external input unit 40 accepts input from the user to the ultrasound diagnostic device 100.

[0049] Next, refer to Figure 2The handling of setting ROI to 166 will be further explained.

[0050] exist Figure 2 The figure shows a display window 200 displaying a B-mode image 210 of the liver. This B-mode image 210 is an image obtained by a convex probe 10. The upper edge 212 of the B-mode image 210 is an arc shape corresponding to the shape of the transducer surface of the probe 10, representing the body surface in contact with the transducer surface of the probe 10. The direction from top to bottom in the figure is the axis of symmetry of the annular fan-shaped B-mode image 210, in other words, the direction of the normal at the center of the aperture of the transducer surface of the probe 10. Hereinafter, this normal will be referred to as the aperture centerline. Homogeneous region 214 of the liver tissue is detected by homogeneous region determination process 164. Furthermore, the outline 220 of the liver including the homogeneous region 214 can also be detected by other analytical techniques. Structures such as blood vessels 216 within the liver are not included in the detected homogeneous region 214.

[0051] On the central line of the aperture in the B-mode image 210, the distance from the body surface to the liver surface near that body surface is the superficial layer thickness. Here, the contour of the homogeneous region 214 can simply be set as the liver surface. Alternatively, the contour 220 can also be set as the liver surface. Furthermore, the width between the upper and lower ends of the liver surface on the central line of the aperture is the liver thickness.

[0052] By setting ROI 166, ROI 230 for ATT and ROI 240 for SWE are set within the homogeneous region 214 of the liver.

[0053] In ATT (Automatic Toll Measurement), the attenuation of ultrasound waves along the depth direction is measured. Therefore, the ROI 230 for ATT requires a width of approximately 10–40 mm along the depth direction. In the following example, the width of the ROI 230 for ATT is set to 30 mm. ATT measurements theoretically require only a single acoustic ray, so there are no particular theoretical requirements regarding the lateral (in other words, scanning direction) width of the ROI 230 for ATT. However, to compensate for the accuracy of attenuation measurements, when performing measurements using multiple lateral acoustic rays, the lateral width of the ROI 230 for ATT is usually set to approximately 10–20 mm. Furthermore, when observing the two-dimensional distribution of ultrasound attenuation, the lateral width is sometimes set wider. In the following example, the lateral width of the ROI 230 for ATT is set to 10 mm. This is just one example; the dimensions of the ROI 230 for ATT are appropriately determined according to various ATT measurement conditions.

[0054] The ROI 240 for SWE needs to be limited to the range within which the excited shear wave can be detected. Therefore, the detectable range varies depending on the excitation method or the power of the ultrasound used for excitation, but under normal conditions, it is approximately ±10 mm in the depth direction and ±10 mm in the lateral direction, starting from the excitation site. Therefore, under normal conditions, the depth and lateral width of the ROI 240 for SWE are both set to approximately 20 mm or less. Hereinafter, as an example, the depth and lateral width of the ROI 240 for SWE are both set to 20 mm. Furthermore, this is only one example; the dimensions of the ROI 240 for SWE are appropriately determined according to various conditions of SWE measurement.

[0055] The conditions for the ROIs shown above assume the simplest measurement scenarios. In scenarios involving more advanced measurements, the size or shape of these ROIs may change. For example, these ROIs could be enlarged to accommodate a wider range of measurements.

[0056] When viewed from the body surface (represented by the upper edge 212 of the B-mode image 210 in the figure), ATT uses ROI 230 and SWE uses ROI 240, both set at a depth deeper than the upper limit depth calculated based on the superficial layer thickness. The upper limit depth represents the uppermost position of the ROI used for tissue measurement. The range shallower than the upper limit depth is the range where the influence of multiple reflections of ultrasound waves between the body surface and the liver surface is strong. Therefore, the upper limit depth can be considered the depth affected by multiple reflections in the sense that the influence of multiple reflections is unacceptably strong.

[0057] The starting and ending depths shown in the figure are the upper and lower depths of the ATT ROI 230. Therefore, the ATT ROI 230 is set with a starting depth of the aforementioned upper limit depth or deeper. By setting ROIs such as the ATT ROI 230 within a depth range above the upper limit depth, the influence of multiple reflections on the measurement can be controlled within acceptable limits. Furthermore, although this is only one example, the figure illustrates a case where the starting depth of the SWE ROI 240 is set at a position deeper than the starting depth of the ATT ROI 230.

[0058] exist Figure 2 In the example shown, ATT uses ROI 230 and SWE uses ROI 240, both of which are set to not contain any structures (such as structure 216) other than the homogeneous region 214.

[0059] Figure 2 The example shown is an instance where ATT uses the starting depth of ROI230 to match the upper limit depth calculated based on the shallow layer thickness.

[0060] As mentioned above, the upper limit depth of the ROI is determined based on the thickness of the shallow layer. For example, the upper limit depth is determined according to the following formula (1).

[0061] Upper limit depth = shallow layer thickness × upper limit depth coefficient……(1)

[0062] The upper limit depth coefficient is positive. Considering the property that the greater the thickness of the shallow layer, the smaller the influence of the virtual image caused by multiple reflections, the upper limit depth coefficient can be represented by a function that decreases as the thickness of the shallow layer increases. Here, since the attenuation of the intensity of the virtual image based on the thickness of the shallow layer is caused by the increase in the propagation distance of the ultrasonic wave, the function representing the upper limit depth coefficient is preferably a function similar to an exponential function with a base value x of 0 < x < 1, rather than a function that decreases linearly with the increase in the thickness of the shallow layer. Furthermore, the higher the frequency of the transmitted ultrasonic wave, the greater the attenuation of the ultrasonic wave intensity with the increase in the propagation distance, so the upper limit depth coefficient can be considered as a function that decreases as the frequency increases. Combining the above, a function represented by, for example, the following equation (2), can be considered as the upper limit depth coefficient y.

[0063] y = Aexp(-azf)……(2)

[0064] In equation (2), A and a are constant coefficients, z is the shallow layer thickness, and f is the frequency.

[0065] Figure 3 The diagram illustrates the function 300 of equation (2) when the frequency f is fixed. Although this is just one example, Figure 3 The function takes a value between 1.5 and 2.5 within the generally accepted range of superficial layer thickness. The ultrasound signal detected up to two round trips between the body surface and the liver surface becomes the virtual image signal where the effects of multiple reflections are most strongly manifested. Therefore, it can be said that the depth range multiplied by 2 represents the depth at which the effects of multiple reflections are most strongly manifested. However, as mentioned above, the greater the superficial layer thickness, the longer the ultrasound propagation distance, and the weaker the virtual image of multiple reflections becomes. Therefore, within the range of thin superficial layer thickness, considering multiple reflections exceeding two round trips, the upper limit coefficient becomes greater than 2; within the range of thick superficial layer thickness, it becomes less than 2.

[0066] Next, refer to Figure 4 An example of the processing procedure of the measuring unit 160 will be explained.

[0067] The examiner places the probe 10 against the subject and takes an image of the area including the organ being examined (e.g., liver). This operation acquires a B-mode image containing the subject organ within the field of view (S10). The measurement unit 160 awaits input of a measurement start instruction (S12). While observing the B-mode image displayed on the display unit 30, the examiner changes the position or orientation of the probe 10 to search for the desired cross-section. At the moment the desired cross-section is displayed on the display unit 30, the examiner inputs a measurement start instruction from the external input unit 40. The result of step S12 becomes "Yes". Accordingly, the B-mode image displayed on the display unit 30 is paused, and the measurement unit 160 begins measurement processing based on that image.

[0068] In the measurement process, firstly, the homogeneous region determination process 164 automatically determines the homogeneous region within the B-mode image of the object, and measures the superficial layer thickness and liver thickness (S14).

[0069] Next, ROI setting 166 involves setting ROI 230 for ATT and ROI 240 for SWE based on these homogeneous regions, superficial layer thickness, liver thickness, etc. (S16). Step S16 will be discussed later. Figure 5 Examples of detailed processing will be provided later.

[0070] Next, measurement processing 162 performs ATT measurements using ROI 230 and SWE measurements using ROI 240 (S18). In each measurement, ultrasound waves used for that measurement are transmitted and received, and measurements are performed based on the received signals. Then, measurement processing 162 outputs the measurement results obtained through these measurements (S19). This output can be, for example, a display on display unit 30 or a data entry in a patient database.

[0071] Next, refer to Figure 5 Here is an example of the detailed process of step S16. In this process, ROI setting 166 calculates the upper limit depth of ROI based on the shallow layer thickness obtained in step S14 and using a function such as the example above (2) (S20). Then, ROI setting 166 positions the candidate ROI 230 for ATT and the candidate ROI 240 for SWE at a predetermined initial position above the upper limit depth (S22).

[0072] The initial position at this point is, for example, the position from the body surface to the upper limit depth on the center line of the aperture of probe 10. The ATT (Area To T) ROI 230, which has a larger width in the depth direction, is positioned at this initial position using the center of its upper edge. In this example, the relative positional relationship between the ATT ROI 230 and the SWE ROI 240 is fixed. For example, the SWE ROI 240 is defined to have its center position in the lateral direction coincide with the center position of the ATT ROI 240, and its initial depth is a predetermined length deeper than the initial depth of the ATT ROI 230. Therefore, in this example, if the ATT ROI 230 is positioned, the position of the SWE ROI 240 is automatically determined.

[0073] Next, ROI setting 166 determines whether the two candidate regions of ATT ROI 230 and SWE ROI 240 located in step S22 contain any part other than the homogeneous region (e.g., structure 216) (S24).

[0074] Here, the measurement of tissue properties such as ATT or SWE targets homogeneous regions. Therefore, if the ROI includes portions other than homogeneous regions, accurate measurement is difficult. Thus, if the result of the determination in step S24 is "yes," ROI setting 166 offsets the positions of the two candidate ROIs, ATT ROI 230 and SWE ROI 240, within a depth range above the upper limit depth according to prescribed rules (S26). Then, ROI setting 166 repeats the determination in step S24 for the two offset candidates. The cycle of steps S24 and S26 is repeated until the determination in step S24 becomes "no," that is, until the two candidates contain only homogeneous regions.

[0075] If the determination result in step S24 is "no", ROI setting 166 sets the two candidate positions at this time as the positions of the formal ATT ROI230 and SWE ROI240 (S28).

[0076] Furthermore, in the search according to the prescribed rules in step S26, for example, firstly, while maintaining the depth direction position of the upper edge of the candidate of ATT with ROI 230 at the aforementioned upper limit depth, the determination in step S24 is repeated while changing the lateral position of the two candidates in various ways. If the determination result of step S24 is not "no" regardless of how the lateral position is changed, the two candidates are moved downward along the depth direction by only a predetermined amount. While moving the two candidates laterally in various ways at this depth direction position, the search is performed for the position where the determination result of step S24 is "no". If the determination result of step S24 is not "no" regardless of how the lateral position is changed at this depth, the two candidates are moved downward further along the depth direction by only a predetermined amount, and the same search is repeated.

[0077] pass Figure 5 The process involves setting appropriate ROI 230 for ATT and ROI 240 for SWE.

[0078] Next, refer to Figure 6 A variation of the detailed process of step S16 will be explained. Figure 5 During the process, regardless of how the positions of ROI230 used by ATT and ROI240 used by SWE were changed, it was sometimes impossible to make these ROIs solely homogeneous regions. Figure 6 During the process, even under these circumstances, it is possible to set the ROI 230 for ATT and the ROI 240 for SWE at locations where the homogeneous region widens as much as possible. Figure 6 In the middle, to and Figure 5 The same steps in the process are marked with the same symbols, and repeated descriptions are omitted.

[0079] exist Figure 6 During the process, if the determination result in step S24 is "yes", ROI setting 166 calculates the area of ​​the homogeneous region within the two candidates (or the ratio of its area to the total area of ​​the two candidates), and establishes a corresponding association between this area and the position information of the two candidates and stores it (S30). Next, ROI setting 166 determines whether the check of all possible positions of the two candidates within the depth range above the upper limit depth has been completed (S32). If the determination result is "no", then ROI setting 166 shifts the positions of the two candidates within the depth range above the upper limit depth according to the prescribed rules (S26), and repeats the determination in step S24 again.

[0080] If the determination result in step S32 is "yes", ROI setting 166 sets ROI 230 for ATT and ROI 240 for SWE at the location represented by the location information of the largest combination of area in the combination of location information stored in the previous repetition of step S30 (S34).

[0081] according to Figure 6 The process allows for the setting of two ROIs at the location with the largest area in the homogeneous region.

[0082] Figure 6 The process assumes that the inspector, while observing the ultrasound image displayed as a dynamic image, determines the cross-section of the object to be measured and then inputs a measurement start instruction. The Region of Interest (ROI) is automatically set according to the measurement start instruction, and the measurement is performed on that ROI. However, this procedure is only one example.

[0083] As another example, for ultrasound images displayed as dynamic images, the ROI setting 166 can automatically set and display the ROI used for tissue property measurement. For example, if the user instructs automatic ROI display, the ROI setting 166 automatically sets the ROI for each frame of the dynamic image. In this case, the ROI superimposed on the ultrasound image can change according to the changes in the ultrasound image as a dynamic image. While observing the dynamic image of the ultrasound image with the superimposed ROI, the examiner instructs the measurement to begin at a suitable time. Based on this instruction, the measurement unit 160 performs the measurement on the ROI displayed at the time the measurement start instruction is received. In addition, a suitable time for measurement can be considered, for example, when the subject stops breathing due to a breath-holding signal, and the displayed ultrasound image becomes approximately still.

[0084] In this example, setting the ROI to 166 allows for the execution of operations on frames of a moving image. Figure 6 The same processing procedure is used to automatically set the ROI. This automatic ROI setting can be performed on a per-frame basis for the dynamic image. Furthermore, assuming that the processor's processing power is insufficient to automatically set the ROI for all frames, it can be set to, for example, to perform automatic ROI setting every few frames.

[0085] Next, refer to Figure 7 A modified example of the processing procedure of the measuring unit 160 will be explained. Figure 7 In the middle, to and Figure 4 The steps in the process are the same, and the same symbols are used for each step.

[0086] Because ATT or SWE measurement results contain biases caused by various factors, it is necessary to repeat the measurement a certain number of times and extract highly reliable results to obtain trustworthy measurement results. Figure 7 During the process, the measurement unit 160 automatically performs this repetitive measurement.

[0087] Figure 7 The process begins when the examiner inputs a measurement start instruction into the ultrasound diagnostic device 100. During this process, if a B-mode image is acquired by transmitting and receiving ultrasound waves from the probe 10 (S10), the measurement unit 160 determines homogeneous regions, superficial layer thickness, etc., based on the B-mode image (S14), and sets an ROI 230 for ATT and an ROI 240 for SWE (S16). Next, the measurement unit 160 uses these set ROIs to perform ATT and SWE measurements (S18), and establishes a corresponding association between the measurement results and, for example, the B-mode image acquired in S10, stores them in the image memory 150 (S19).

[0088] Next, the statistical analysis 168 within the measurement unit 160 performs numerical analysis on the measurement results stored in the image memory 150 (S40). In this analysis, for example, the average of the measured values ​​within the corresponding ROI is calculated for both ATT and SWE. That is, the attenuation coefficient of the ultrasonic wave is measured at each point in ATT, but in step S40, the average value of the attenuation coefficient within ROI 230 for ATT is calculated. Similarly, the average value of the SWE measured values ​​(e.g., the measured value of the propagation velocity of the shear wave) within ROI 240 for SWE is calculated. Thus, the average values ​​of the attenuation coefficient and propagation velocity in this measurement are calculated respectively.

[0089] Next, the statistical analysis 168 determines whether the number of measurements performed since the instruction to begin measurement has reached the predetermined number (S42). If the result of this determination is "no", the measurement unit 160 returns to step S10, acquires the next B-mode image, and repeats the processing of steps S14 to S42.

[0090] When the determination result in step S42 is "yes", the measurement unit 160 searches the stored measurement results for a combination of measurement results that indicate that the statistical value of the deviation is within a predetermined allowable limit for a specified number of times (S44).

[0091] As a statistical measure of deviation, IQR / median can be used, for example. Here, IQR (Interquartile Range) is the difference (Q3-Q1) between the 3rd quartile (Q3) and the 1st quartile (Q1) of the data in the population. Quartiles, on the other hand, refer to the data points in a population arranged in ascending order, dividing them into four equal parts from a data quantity perspective. In quartiles, the ordinal numbers 1, 2, and 3 are assigned in ascending order. IQR / median is the percentage value obtained by dividing the IQR by the population median (i.e., the central value).

[0092] That is, in step S44, statistical analysis 168 from Figure 7 The process begins by selecting a predetermined number of combinations of measurements from the currently saved measurement results (hereinafter referred to as the "population") and calculating the IQR / median for the selected combinations. Next, statistical analysis 168 determines whether the calculated IQR / median is within a pre-defined tolerance limit (e.g., "10%"). This tolerance limit for the IQR / median is an example of an indicator of measurement precision. Then, if the determination is "no" (i.e., the IQR / median is greater than the tolerance limit), statistical analysis 168 selects another predetermined number of combinations of measurements from the population and repeats the same determination.

[0093] In this repetition, if no combination is found in the population where the IQR / median is below the allowable limit, the determination result of step S46 becomes "No". In this case, the measurement unit 160 returns to step S10, acquires a new B-mode image, and performs the processing of steps S14 to S44 on the B-mode image.

[0094] On the other hand, if a combination is found in the population where the IQR / median is below the allowable limit, the determination result of step S46 becomes "yes". In this case, the measurement unit 160 ends the measurement (S48) and outputs the found combination in the form of screen display or database saving (S50).

[0095] In step S50, for example, for each measurement result included in the found combination, the values ​​of the measurement results (e.g., the average value of the attenuation coefficient and the average value of the shear wave velocity) can be correlated with and displayed as thumbnails of the corresponding B-mode images. The thumbnails can include links for calling the original B-mode images.

[0096] According to Figure 7The process is explained with a specific example. In this example, the number of measurements is specified as 5. During the stage of performing the measurement from the start to the 5th measurement, an initial deviation value (e.g., IQR / median) is calculated for the combination of these 5 measurement values. This deviation value is greater than the allowable limit. In this case, a 6th measurement is performed. If the 6th measurement value is input, a new combination of 5 measurement values ​​is created by excluding the statistically most deviating measurement value from the past 5 measurement values ​​used in the previous deviation value calculation and the current 6th measurement value. Then, the deviation value for this new combination is calculated, and the combination and the deviation value are stored in memory. By repeating this process, the combination of measurement values ​​for the specified number of times is updated in the direction of decreasing deviation value. Finally, when the predetermined condition that the deviation value is within the specified allowable limit is met, the measurement automatically ends, and the result is displayed, for example, on the display unit 30.

[0097] Furthermore, in the above example, two types of measurements, ATT and SWE, are performed. Therefore, step S44 is searched and step S46 is determined for each of these two types. Then, if the determination result of step S46 for one type is "yes", the measurement for that type can be ended, and only for the other type of measurement, the process returns to step S10 and is repeated.

[0098] according to Figure 7 In this process, the inspector can automatically complete the measurement simply by placing the probe 10 in contact with the object being inspected. That is, not only is there no need to set the ROI while identifying homogeneous areas, but the inspector also does not need to statistically select data with minimal bias. Therefore, accurate and quick inspections can be expected.

[0099] In addition to ATT and SWE, BSC is another known method for measuring tissue properties using ultrasound. BSC stands for Back Scatter Coefficient. BSC is a technique for evaluating tissue inhomogeneity by measuring the intensity of ultrasound signals scattered from the tissue. Examples of BSC usage include Keith A. Wear et al., “USbackscatter for Liver Fat Quantification: An AIUMRSNA QIBA Pulse-EchoQuantitative Ultrasound Initiative”, Radiology, Volume 305, Number 3-December, pp. 526-537, 2022, radiology.rsna.org, and Kazuaki Tamura et al., “Development of an Ultra-High Precision Ultrasound Diagnostic Method Based on Scatterer Structure Analysis in Living Organisms”, Tateishi Science and Technology Foundation Granted Research Results Collection (No. 28), 2019. (Tateishi Science and Technology Foundation Granted Research Results Collection)

[0100] BSC analyzes the longitudinal wave of ultrasound, so in principle, only a one-dimensional signal from a single sound ray is needed. Therefore, the ROI of BSC can be shared with the ROI of ATT, which also uses a one-dimensional signal as its object. Therefore, in the above embodiment, the ROI of ATT can be used for further BSC measurements.

[0101] Furthermore, the measurements mentioned above, such as ATT, SWE, and BSC, are merely examples. The method of this embodiment can also be applied to other tissue property measurement methods.

[0102] In this embodiment, each process is executed by any computer. Furthermore, any computer can execute these processes via a processor as hardware, a program as software, or a combination thereof. In this case, the processor is configured to cooperate with the program to execute the various processes in this embodiment and can function as a unit or means in this embodiment. Moreover, the execution order of the processor-based processes is not limited to the order described and can be appropriately varied. Any computer can be a general-purpose computer, a special-purpose computer, a workstation, or other system capable of executing the processes.

[0103] A processor can be composed of one or more hardware components, and the type of hardware is not limited. For example, a processor can be composed of programmable logic devices such as CPUs (Central Processing Units), MPUs (Micro Processing Units), FPGAs (Field Programmable Gate Arrays), dedicated circuits for performing specific processes such as ASICs (Application Specific Integrated Circuits), GPUs (Graphics Processing Units), or NPUs (Neural Processing Units). Furthermore, the type of hardware can be a combination of different types of hardware. When multiple hardware components are configured to execute one or more processes of a certain processor, these multiple hardware components can exist in physically separate devices or in the same device. Moreover, in any embodiment, the order of the processor's processes is not limited to the above order and can be appropriately varied. Additionally, the hardware is composed of circuits, such as those combining semiconductor elements.

[0104] Furthermore, the program can be software such as firmware or microcode. And, for example, the program can be a group of program modules, each of whose functions can be implemented by a processor configured to execute those functions. The program can be program code or multiple code segments stored in one or more non-transitory computer-readable media (e.g., storage media or other storage devices). The program can be divided and stored in multiple non-transitory computer-readable media existing in physically separate devices. Program code or code segments can represent any combination of procedures, functions, subroutines, routines, subroutines, modules, software packages, classes or commands, data structures, or program statements. Program code or code segments can be connected to other code segments or hardware circuitry by sending and receiving information, data, arguments, parameters, or memory contents.

Claims

1. An ultrasonic diagnostic device, characterized in that, Equipped with a processor The processor performs the following processing: Extracting homogeneous regions of organs from ultrasound images; Based on the ultrasound image, determine the depth of the organ's surface relative to the body surface; and Within the homogeneous region, the target area for tissue property measurement is defined according to the depth.

2. The ultrasonic diagnostic device according to claim 1, characterized in that, In setting the object region, the processor performs the following processing: The depth of influence of multiple reflections is determined based on the depth of the surface of the organ; and The object region is defined at a location deeper than the depth of influence of the multiple reflections.

3. The ultrasonic diagnostic device according to claim 2, characterized in that, The depth of influence of the multiple reflections is determined based on the depth of the surface and a coefficient, wherein the coefficient is greater than or equal to 1, and the deeper the surface, the smaller the coefficient.

4. The ultrasonic diagnostic device according to claim 3, characterized in that, The coefficients are calculated using an exponential function with a base greater than 0 and less than 1.

5. The ultrasonic diagnostic device according to claim 3, characterized in that, The coefficient is a value between 1.5 and 2.

5.

6. The ultrasonic diagnostic device according to any one of claims 2 to 5, characterized in that, The measurements include shear wave elastic imaging and attenuation imaging. In setting the object region, the processor performs the following processing: The object region for the shear wave elastic imaging and the object region for the attenuation imaging are configured to overlap each other.

7. The ultrasonic diagnostic device according to claim 6, characterized in that, The object region in the attenuation imaging is a longitudinal region.

8. The ultrasonic diagnostic device according to claim 7, characterized in that, In setting the object region, the processor performs the following processing: The location of the object region with respect to the attenuation imaging is determined to be deeper than the depth of influence of the multiple reflections; and Based on the determined position of the object region with respect to the attenuation imaging, the position of the object region with respect to the shear wave elastic imaging is set.

9. The ultrasonic diagnostic device according to claim 6, characterized in that, The measurement also includes backscattering analysis. In setting the object region, the processor performs the following processing: The region defined for the object region in the attenuation imaging is also defined for the object region in the backscattering analysis.

10. The ultrasonic diagnostic device according to any one of claims 1 to 5, characterized in that, Each time an ultrasonic image is obtained through repeated ultrasonic measurements, the processor performs the following processing: The obtained ultrasonic image is processed by extracting the homogeneous region, calculating the depth of the surface relative to the body surface, and defining the object region. Perform tissue property measurements on the defined object region; The data representing the results of the performed measurement is stored in a storage device; and The process performs a predetermined number of data that meet a predetermined accuracy index from the data obtained in each of the measurements stored in the storage device.

11. The ultrasonic diagnostic device according to claim 1, characterized in that, The tissue property measurement is at least one of shear wave elastography, attenuation imaging, and backscattering analysis.

12. An ultrasonic image processing method, Extracting homogeneous regions of organs from ultrasound images; Based on the ultrasound image, determine the depth of the organ's surface relative to the body surface; and Within the homogeneous region, the target area for tissue property measurement is defined according to the depth.

13. The ultrasonic image processing method according to claim 12, characterized in that, In the setting of the object area, The depth of influence of multiple reflections is determined based on the depth of the surface of the organ; and The object region is defined at a location deeper than the depth of influence of the multiple reflections.

14. The ultrasonic image processing method according to claim 13, characterized in that, The depth of influence of the multiple reflections is determined based on the depth of the surface and a coefficient, wherein the coefficient is greater than or equal to 1, and the deeper the surface, the smaller the coefficient.

15. The ultrasonic image processing method according to claim 13 or 14, characterized in that, The measurements include shear wave elastic imaging and attenuation imaging. In the setting of the object area, The object region for the shear wave elastic imaging and the object region for the attenuation imaging are configured to overlap each other.

16. The ultrasonic image processing method according to claim 15, characterized in that, The object region in the attenuation imaging is a longitudinal region.

17. The ultrasonic image processing method according to claim 16, characterized in that, In the setting of the object area, The location of the object region with respect to the attenuation imaging is determined to be deeper than the depth of influence of the multiple reflections; and Based on the determined position of the object region with respect to the attenuation imaging, the position of the object region with respect to the shear wave elastic imaging is set.

18. The ultrasonic image processing method according to claim 15, characterized in that, The measurement also includes backscattering analysis. In the setting of the object area, The region defined for the object region in the attenuation imaging is also defined for the object region in the backscattering analysis.

19. The ultrasonic image processing method according to any one of claims 12 to 14, characterized in that, Each time an ultrasound image is obtained through repeated ultrasound measurements. The obtained ultrasonic image is processed by extracting the homogeneous region, calculating the depth of the surface relative to the body surface, and defining the object region. Perform tissue property measurements on the defined object region; The data representing the results of the performed measurement is stored in a storage device; and The process performs a predetermined number of data that meet a predetermined accuracy index from the data obtained in each of the measurements stored in the storage device.

20. An information processing program product that causes a computer to perform the method according to any one of claims 12 to 14.

21. A computer-readable recording medium storing an information processing program that causes a computer to perform the method of any one of claims 12 to 14.

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