Ultrasound diagnostic equipment

Abstract

The objective is to improve inspection efficiency and accuracy in PWD mode. [Solution] The ultrasound diagnostic apparatus according to the embodiment includes: a sample gate setting unit that sets a sample gate including a region for acquiring blood flow information of a subject on an ultrasound image of the subject; an acquisition unit that acquires a plurality of blood vessel width candidates for the blood vessel at the position where the sample gate is set, based on at least one of the ultrasound reception information and examination information of the subject; and an adjustment unit that adjusts the region included in the sample gate based on the plurality of blood vessel width candidates.

Description

Technical Field

[0001] The embodiments disclosed in this specification and the drawings relate to an ultrasonic diagnostic apparatus.

Background Art

[0002] Conventionally, in ultrasonic examinations using an ultrasonic diagnostic apparatus, a Doppler spectrum (Doppler waveform) representing blood flow information is displayed using Doppler information (Doppler signal) including a blood flow signal extracted from a reflected wave of ultrasonic waves. The Doppler waveform is a waveform obtained by plotting the blood flow velocity at a position set by an operator as an observation site over time. For example, one method of collecting this Doppler waveform is the pulsed wave Doppler (PWD) method. In the PWD mode (PWD scan) for collecting the Doppler waveform using this PWD method, the user sets a sample gate including a region (sample volume) for acquiring the blood flow information of the subject in an ultrasonic image (B-mode image and color Doppler image), and it is necessary to manually set the sample volume according to the blood vessel width of the blood vessel at the position where the sample gate is set. By appropriately setting the sample volume by the user according to the blood vessel width of the blood vessel at the position where the sample gate is set, the accuracy of comparison of blood flow waveforms, measurement of maximum blood flow, and blood flow volume is improved. For example, the size of an appropriate sample volume according to the blood vessel may be described in detail by an examination guideline.

[0003] However, since the widths and shapes of blood vessels vary, when manually setting the sample volume for each blood vessel, the examination time may become long. Also, when blooming where the blood flow signal protrudes from the blood vessel and is displayed occurs in the color Doppler image superimposed on the B-mode image, the B-mode image of the part where blooming occurs cannot be observed, so it is difficult for the user to manually or subjectively adjust the sample volume, and when such manual or subjective adjustment is performed, the accuracy of adjusting the sample volume may decrease.

[0004] In recent years, there has been technology that recognizes blood flow areas based on color Doppler images superimposed on B-mode images and automatically adjusts the depth and width of the sample volume to match the blood flow areas. However, if blooming occurs in the color Doppler image superimposed on the B-mode image, the sample volume may not be properly adjusted because the blooming area is recognized as a blood flow area. This can reduce the accuracy of sample volume adjustment, similar to manual or subjective adjustments. Furthermore, when blooming occurs, the B-mode image becomes difficult to observe, making it difficult for the user to manually adjust the sample volume after the depth and width have been automatically adjusted to match the blood flow areas. In addition, if the color gain and scale are not properly adjusted, the color Doppler image may not extend to the vicinity of the blood vessel wall, making it difficult to accurately adjust the sample volume in such cases as well. For these reasons, it is desirable to improve the efficiency and accuracy of examinations in PWD mode by appropriately adjusting the area from which to acquire blood flow information of the subject. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Patent No. 7345624 [Overview of the project] [Problems that the invention aims to solve]

[0006] One of the problems that the embodiments disclosed herein and in the drawings aim to solve is to improve inspection efficiency and inspection accuracy in PWD mode. However, the problems that the embodiments disclosed herein and in the drawings aim to solve are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described later can also be positioned as other problems. [Means for solving the problem]

[0007] The ultrasound diagnostic apparatus according to the embodiment includes: a sample gate setting unit that sets a sample gate on an ultrasound image of a subject that includes a region for acquiring blood flow information of the subject; an acquisition unit that acquires a plurality of blood vessel width candidates for the blood vessel at the position where the sample gate is set, based on at least one of the ultrasound reception information and examination information of the subject; and an adjustment unit that adjusts the region included in the sample gate based on the plurality of blood vessel width candidates. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing an example of the configuration of an ultrasound diagnostic device according to the first embodiment. [Figure 2] This figure shows an example of a sample gate set up on an ultrasound image. [Figure 3] This flowchart explains the process of acquiring candidate blood vessel widths based on B-mode information, which is performed within the device itself. [Figure 4] This figure shows an example of an ultrasound image within a certain range from the center of the sample volume. [Figure 5] This figure shows an example of the distribution of luminance values ​​within a certain range from the center position of the sample volume. [Figure 6] This figure shows the distribution of brightness values ​​when blood vessels are included within a certain range from the center of the sample volume, and when uniform tissue is included within a certain range from the center of the sample volume. [Figure 7] This figure shows an example of the distribution of brightness values ​​on a raster. [Figure 8] This diagram illustrates the brightness values ​​of blood vessels, tissues, and blood vessel walls. [Figure 9] This figure shows an example of a threshold obtained based on the distribution of brightness values ​​of B-mode images within a certain range from the center position of the sample volume. [Figure 10] This figure shows an example of the distribution of luminance values ​​on a raster with a set threshold. [Figure 11] This is a diagram illustrating an example of a search method. [Figure 12] This figure shows an example of how to adjust the sample volume. [Figure 13] This is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic apparatus according to the first embodiment. [Figure 14] This figure shows an example of an ultrasound image with a sample gate set. [Figure 15] Figure 14 shows an example of the distribution of brightness values ​​within a certain range from the center position of the sample volume obtained in the ultrasound image. [Figure 16] Figure 14 shows an example of the distribution of brightness values ​​on a raster obtained in an ultrasound image. [Figure 17] (a) is a diagram showing an example of an ultrasound image with a sample gate set, including the sample volume before adjustment. (b) is a diagram showing an example of an ultrasound image with a sample gate set, including the adjusted sample volume. [Figure 18] This block diagram shows an example of the configuration of an ultrasound diagnostic device according to the second embodiment. [Figure 19] This flowchart explains the process of acquiring candidate blood vessel widths based on power information, which is performed within the device itself. [Figure 20] This figure shows an example of how to obtain power values. [Figure 21] This is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic apparatus according to the second embodiment. [Figure 22] This figure shows an example of the distribution of brightness values ​​within a certain range from the center position of the sample volume acquired in an ultrasound image. [Figure 23] Figure 22 shows an example of the distribution of brightness values ​​on a raster obtained in an ultrasound image. [Figure 24] This figure shows an example of the distribution of power values ​​on a raster. [Figure 25](a) is a diagram showing an example of an ultrasound image with a sample gate set, including the sample volume before adjustment. (b) is a diagram showing an example of an ultrasound image with a sample gate set, including the sample volume before and after adjustment. [Figure 26] This block diagram shows an example of the configuration of an ultrasound diagnostic device according to the third embodiment. [Figure 27] This is a flowchart illustrating the process of acquiring candidate blood vessel widths based on velocity information, which is performed within the device itself. [Figure 28] This is a flowchart illustrating the process of acquiring candidate blood vessel widths based on distributed information, which is performed within the device itself. [Figure 29] This is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic apparatus according to the third embodiment. [Figure 30] This figure shows an example of an ultrasound image with a sample gate set. [Figure 31] Figure 30 shows an example of the distribution of brightness values ​​on a raster obtained in an ultrasound image. [Figure 32] (a) is a diagram showing an example of an ultrasound image with a sample gate set, including the sample volume before adjustment. (b) is a diagram showing an example of an ultrasound image with a sample gate set, including the sample volume before and after adjustment. [Figure 33] This is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic apparatus according to the third embodiment. [Figure 34] This figure shows an example of an ultrasound image (IM) with a sample gate set. [Figure 35] Figure 34 shows an example of the power value distribution in an ultrasound image. [Figure 36] Figure 34 shows an example of the distribution of velocity values ​​in an ultrasound image. [Figure 37] Figure 35 shows an example of the distribution of power values ​​on a raster, and Figure 36 shows an example of the distribution of velocity values ​​on a raster. [Figure 38] Figure 37 shows the normalized distributions of power and velocity values. [Modes for carrying out the invention]

[0009] The embodiments of the ultrasound diagnostic apparatus will be described below with reference to the drawings. In the following description, components having substantially the same function and configuration will be denoted by the same reference numeral, and redundant explanations will be given only when necessary.

[0010] [First Embodiment] Figure 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to the first embodiment. As shown in Figure 1, the ultrasound diagnostic apparatus 1 comprises an ultrasound probe 10, a main body 30, an input device 50, and a display 70.

[0011] The ultrasonic probe 10 has, for example, a plurality of piezoelectric transducers. These plurality of piezoelectric transducers generate ultrasound based on a drive signal supplied from a transmission circuit 31 in the main body of the device 30, which will be described later. The ultrasonic probe 10 also receives reflected waves from the subject P and converts them into electrical signals. The ultrasonic probe 10 also has, for example, a matching layer provided on the piezoelectric transducer and a backing material that prevents the propagation of ultrasound backward from the piezoelectric transducer.

[0012] When ultrasound is transmitted from the ultrasound probe 10 to the subject P, the transmitted ultrasound is reflected one after another by discontinuities in acoustic impedance within the subject P's internal tissues, and the reflected wave signals are received by multiple piezoelectric transducers on the ultrasound probe 10. The amplitude of the received reflected wave signals depends on the difference in acoustic impedance at the discontinuities where the ultrasound is reflected. Furthermore, when the transmitted ultrasound pulse is reflected by a moving blood flow or the surface of the heart wall, the reflected wave signal undergoes a frequency shift due to the Doppler effect, depending on the velocity component of the moving object relative to the ultrasound transmission direction. This reflected wave signal corresponds to the received signal in this embodiment.

[0013] The ultrasonic probe 10 is detachably connected to the main unit 30 of the device. When scanning a two-dimensional area within the subject P (two-dimensional scanning), the user connects a 1D array probe, for example, in which multiple piezoelectric transducers are arranged in a row, to the main unit 30 as the ultrasonic probe 10. 1D array probes include linear ultrasonic probes, convex ultrasonic probes, sector ultrasonic probes, etc. When scanning a three-dimensional area within the subject P (three-dimensional scanning), the user connects a mechanical 4D probe or a 2D array probe to the main unit 30 as the ultrasonic probe 10. A mechanical 4D probe can perform two-dimensional scanning using multiple piezoelectric transducers arranged in a row, similar to a 1D array probe, and can also perform three-dimensional scanning by oscillating the multiple piezoelectric transducers at a predetermined angle (oscillation angle). A 2D array probe can perform three-dimensional scanning using multiple piezoelectric transducers arranged in a matrix, and can also perform two-dimensional scanning by focusing and transmitting ultrasound. Furthermore, 2D array probes can simultaneously perform 2D scanning of multiple cross-sections.

[0014] Furthermore, the ultrasound diagnostic device 1 according to this embodiment acquires Doppler waveforms using the PWD method. Therefore, in this embodiment, the ultrasound probe 10 connected to the device body 30 is an ultrasound probe capable of performing both ultrasound transmission and reception for acquiring two-dimensional ultrasound images and ultrasound transmission and reception for acquiring Doppler waveforms using the PWD method.

[0015] The device body 30 generates an ultrasound image based on the reflected wave signal received by the ultrasound probe 10. Specifically, the device body 30 can generate a two-dimensional ultrasound image based on the reflected wave signal corresponding to the two-dimensional region of the subject P received by the ultrasound probe 10. Furthermore, the device body 30 can generate a three-dimensional ultrasound image based on the reflected wave signal corresponding to the three-dimensional region of the subject P received by the ultrasound probe 10. As shown in Figure 1, the device body 30 includes a transmission circuit 31, a reception circuit 32, a B-mode processing circuit 33, a Doppler processing circuit 34, an image generation circuit 35, an image memory 36, a storage circuit 37, and a processing circuit 38.

[0016] The transmitting circuit 31 includes a pulse generator, a transmission delay unit, a pulser, etc., and supplies a drive signal to the ultrasonic probe 10. The pulse generator repeatedly generates rate pulses at a predetermined rate frequency to form the transmitted ultrasonic waves. The transmission delay unit provides a delay time for each piezoelectric transducer necessary to focus the ultrasonic waves generated from the ultrasonic probe 10 into a beam and determine the transmission directivity, to each rate pulse generated by the pulse generator. The pulser applies a drive signal (drive pulse) to the ultrasonic probe 10 at a timing based on the rate pulse. In other words, the transmission delay unit arbitrarily adjusts the transmission direction of the ultrasonic waves transmitted from the piezoelectric transducer surface by changing the delay time provided to each rate pulse.

[0017] Furthermore, the transmitting circuit 31 has the function of instantaneously changing the transmitting frequency, transmitting drive voltage, etc., in order to execute a predetermined scan sequence based on instructions from the processing circuit 38, which will be described later. In particular, the change in the transmitting drive voltage is achieved by a linear amplifier type oscillator circuit that can switch its value instantaneously, or by a mechanism that electrically switches multiple power supply units.

[0018] The receiving circuit 32 includes a preamplifier, an A / D (Analog / Digital) converter, a receiving delay unit, an adder, etc., and performs various processing on the reflected wave signal received by the ultrasonic probe 10 to generate reflected wave data. The preamplifier amplifies the reflected wave signal for each channel and performs gain adjustment (gain correction). The A / D converter converts the gain-corrected reflected wave signal into a digital signal by A / D conversion. The receiving delay unit provides the delay time necessary to determine the receiving directivity. The adder generates reflected wave data by summing the reflected wave signals processed by the receiving delay unit. The adder then outputs the generated reflected wave data to the B-mode processing circuit 33 and the Doppler processing circuit 34.

[0019] When scanning the subject P in two dimensions, the transmitting circuit 31 causes the ultrasonic probe 10 to transmit a two-dimensional ultrasonic beam. The receiving circuit 32 then generates two-dimensional reflected wave data from the two-dimensional reflected wave signal received by the ultrasonic probe 10. In this embodiment, when scanning the subject P in three dimensions, the transmitting circuit 31 causes the ultrasonic probe 10 to transmit a three-dimensional ultrasonic beam. The receiving circuit 32 then generates three-dimensional reflected wave data from the three-dimensional reflected wave signal received by the ultrasonic probe 10.

[0020] The B-mode processing circuit 33 receives reflected wave data from the receiving circuit 32 and performs logarithmic amplification, envelope detection, etc., to generate data (B-mode data) in which the signal strength is expressed as brightness.

[0021] The Doppler processing circuit 34 performs frequency analysis on the reflected wave data received from the receiving circuit 32, extracts blood flow, tissue, and contrast agent echo components due to the Doppler effect within the ROI (Region of Interest) set in the scan area, and generates data (Doppler data) in which moving object information such as velocity, dispersion, and power is extracted for multiple points. Specifically, the Doppler processing circuit 34 generates Doppler data in which velocity values, dispersion values, power values, etc., are estimated for each of multiple sample points as motion information of moving objects. Here, moving objects include, for example, blood flow, tissue of organs that move periodically, such as the heart wall, and contrast agents. The Doppler processing circuit 34 outputs the generated Doppler data to the image generation circuit 35 and image memory 36.

[0022] Furthermore, the Doppler processing circuit 34 is capable of performing the color Doppler method, also known as the color flow mapping (CFM) method. In the color flow mapping method, ultrasound is transmitted and received multiple times on multiple rasters. Then, in the color flow mapping method, an MTI (Moving Target Indicator) filter is applied to the data sequence at the same location to suppress signals originating from stationary or slow-moving tissue (clutter signals) and extract blood flow signals, which are signals originating from blood flow. Then, in the color flow mapping method, blood flow information such as blood flow velocity, blood flow dispersion, and blood flow power is estimated from this blood flow signal. The Doppler processing circuit 34 outputs color Doppler data showing the blood flow information estimated by the color flow mapping method to the image generation circuit 35 and image memory 36. Note that the color Doppler data is an example of Doppler data.

[0023] An MTI filter uses a filter matrix to output a data sequence in which clutter components are suppressed and the blood flow signal is extracted from a data sequence of consecutive reflected wave data at the same location (same sample point). Applicable MTI filters include, for example, filters with fixed coefficients such as Butterworth-type IIR (Infinite Impulse Response) filters and polynomial regression filters, or adaptive filters that change coefficients according to the input signal using eigenvectors, etc.

[0024] The B-mode processing circuit 33 and the Doppler processing circuit 34 are capable of processing both two-dimensional and three-dimensional reflected wave data. Specifically, the B-mode processing circuit 33 generates two-dimensional B-mode data from two-dimensional reflected wave data and three-dimensional B-mode data from three-dimensional reflected wave data. Similarly, the Doppler processing circuit 34 generates two-dimensional Doppler data from two-dimensional reflected wave data and three-dimensional Doppler data from three-dimensional reflected wave data.

[0025] The image generation circuit 35 generates an ultrasonic image represented within a predetermined brightness range based on the reflected wave signal received by the ultrasonic probe 10. For example, the image generation circuit 35 generates a two-dimensional B-mode image as an ultrasonic image, representing the intensity of the reflected wave in brightness from the two-dimensional B-mode data generated by the B-mode processing circuit 33. The image generation circuit 35 also generates a two-dimensional color Doppler image as an ultrasonic image, representing moving object information, such as a velocity image, dispersion image, power image, or a combination thereof, from the two-dimensional Doppler data generated by the Doppler processing circuit 34.

[0026] Here, the image generation circuit 35 generally converts the scan line signal sequence of the ultrasonic scan into a scan line signal sequence of a video format, such as that used in televisions, to generate an ultrasonic image for display. For example, the image generation circuit 35 generates an ultrasonic image for display by performing a coordinate transformation according to the ultrasonic scanning pattern of the ultrasonic probe 10. In addition to scan conversion, the image generation circuit 35 also performs various other image processing tasks, such as image processing that regenerates an average brightness image using multiple image frames after scan conversion (smoothing process), or image processing that uses a differential filter within the image (edge ​​enhancement process).

[0027] In other words, B-mode data and Doppler data are data before scan conversion processing, while the data generated by the image generation circuit 35 is the ultrasound image for display after scan conversion processing. The B-mode data and Doppler data, which are data before scan conversion processing, are also called raw data. The image generation circuit 35 generates two-dimensional ultrasound images, specifically two-dimensional B-mode images and two-dimensional color Doppler images, from the two-dimensional B-mode data and two-dimensional Doppler data, which are raw data before scan conversion processing. The image generation circuit 35 can also generate superimposed images, for example, by superimposing a color Doppler image onto a two-dimensional B-mode image. Furthermore, the image generation circuit 35 can also generate three-dimensional B-mode images and three-dimensional color Doppler images by performing coordinate transformations on the three-dimensional B-mode data generated by the B-mode processing circuit 33 and the three-dimensional Doppler data generated by the Doppler processing circuit 34, which are raw data before scan conversion processing.

[0028] Furthermore, for example, the image generation circuit 35 generates an M-mode image from the time-series data of B-mode data on one scan line generated by the B-mode processing circuit 33. The image generation circuit 35 also generates a Doppler waveform plotting blood flow and tissue velocity information over time from the Doppler data generated by the Doppler processing circuit 34.

[0029] The image memory 36 is a memory that stores various images generated by the image generation circuit 35. The image memory 36 also stores data generated by the B-mode processing circuit 33 and the Doppler processing circuit 34. The B-mode data and Doppler data stored in the image memory 36 can be retrieved by the operator after a diagnosis, for example, and when routed through the image generation circuit 35, they become ultrasound images for display. The image memory 36 also stores reflected wave data output by the receiving circuit 32. For example, the image memory 36 can be implemented using semiconductor memory elements such as RAM (Random Access Memory), flash memory, a hard disk, or an optical disk.

[0030] The memory circuit 37 stores control programs for ultrasound transmission and reception, image processing, and display processing, as well as various data such as diagnostic information (e.g., patient ID, physician's findings, etc.), diagnostic protocols, and various body marks. The memory circuit 37 also stores a first association table linking examination information with blood vessel diameter. Furthermore, the memory circuit 37 stores information related to the sample gate settings. This sample gate setting information includes, for example, the width of the sample volume contained in the sample gate before adjustment and the angle of the scan lines (raster). The memory circuit 37 is also used, as needed, to store data stored in the image memory 36. For example, the memory circuit 37 can be implemented using semiconductor memory elements such as flash memory, a hard disk, or an optical disk.

[0031] The processing circuit 38 performs various data processing functions. The processing circuit 38 has a system control function 381, a display control function 382, ​​a sample gate setting function 383, an acquisition function 384, and an adjustment function 385. Here, for example, the processing functions of the system control function 381, display control function 382, ​​sample gate setting function 383, acquisition function 384, and adjustment function 385, which are components of the processing circuit 38 shown in Figure 1, are recorded in the storage circuit 37 in the form of a program that can be executed by a computer. The processing circuit 38 reads each program from the storage circuit 37 and realizes the function corresponding to each program by executing each read program. In other words, the processing circuit 38 in the state in which each program has been read has the functions shown in the processing circuit 38 of Figure 1. The processing circuit 38 is realized by a processor, for example. The system control function 381 is an example of a control unit. The display control function 382 is an example of a display control unit. The sample gate setting function 383 is an example of a sample gate setting unit. The acquisition function 384 is an example of an acquisition unit. The adjustment function 385 is an example of an adjustment unit.

[0032] The system control function 381 is a function that comprehensively controls the operation of the entire ultrasound diagnostic device 1. For example, the system control function 381 controls the transmitting circuit 31 and the receiving circuit 32 based on parameters related to the transmission and reception of ultrasound according to various modes. These various modes include, for example, B mode, color Doppler mode, PWD mode, CWD mode, etc. Note that PWD mode is also called PW mode, and CWD mode is also called CW mode.

[0033] B-mode is a mode for generating B-mode images through B-mode scanning. Color Doppler mode is a mode for generating color Doppler images through color Doppler scanning, in which colors are assigned to blood flow information measured, for example, using pulse waves. Color Doppler scanning includes B-mode scanning. In color Doppler mode, for example, both B-mode images and color Doppler images are generated, and the color Doppler image is superimposed on the B-mode image.

[0034] PWD mode is a mode for acquiring Doppler waveforms related to a specific measurement site by PWD mode scanning (PWD method scanning), which involves transmitting pulse waves to a log-r raster on the subject and receiving the reflected waves. In PWD mode, it is common for the ultrasound probe 10 to perform a PWD mode scan on one raster, but it is also possible to perform a PWD mode scan on multiple rasters. In that case, the ultrasound probe 10 transmits pulse waves to multiple rasters sequentially and receives the reflected waves. When performing PWD mode, in order to observe blood flow with good image quality, only the Doppler waveform may be updated, meaning that B-mode scanning may not be used in combination. Alternatively, in order to compare with B-mode images, both the B-mode image and the Doppler waveform may be updated, meaning that B-mode scanning may be used in combination.

[0035] The CWD mode is a mode for measuring Doppler waveforms on a single raster using a CWD mode scan (a scan using the CWD method) that transmits a continuous wave while receiving reflected waves. In CWD mode, it is necessary to keep the continuous wave focused on the target, so B-mode scanning cannot be used in conjunction with it.

[0036] The display control function 382 controls the display 70 to display various ultrasound images and Doppler waveforms generated by the image generation circuit 35. For example, the display control function 382 controls the display 70 to display B-mode images, color Doppler images, or images containing both, and Doppler waveforms generated by the image generation circuit 35. Specifically, the display control function 382 displays B-mode images, color Doppler images, or images containing both on the display 70 in real time, or displays Doppler waveforms on the display 70 in real time.

[0037] The sample gate setting function 383 sets a sample gate on the ultrasound image of a subject that includes a region for acquiring blood flow information of the subject. Specifically, the sample gate setting function 383 sets a sample gate on the ultrasound image of a subject, which is a B-mode image or a color Doppler image superimposed on a B-mode image, in response to user input, which includes a region for acquiring blood flow information of the subject. The sample gate setting function 383 also sets a sample gate on an ultrasound image of a blood vessel acquired from one imaging direction. This region for acquiring blood flow information is, for example, the sample volume. In the following description, the embodiment will be described assuming that the region for acquiring blood flow information is the sample volume.

[0038] Furthermore, the sample gate setting function 383 acquires the center position of the region included in the sample gate. Specifically, the sample gate setting function 383 acquires the center position of the sample volume included in the sample gate. Figure 2 is a diagram showing an example of a sample gate set on an ultrasound image. The ultrasound image IM shown in Figure 2 is a B-mode image IM1. As shown in Figure 2, the sample gate setting function 383 sets a sample gate SG containing the sample volume SV on the ultrasound image IM. Specifically, in the example shown in Figure 2, the sample gate setting function 383 sets the sample gate SG on the B-mode image IM1, which is an ultrasound image IM in which a long-axis view of the vessel BV is captured, as an ultrasound image IM in which the vessel BV is captured from one imaging direction. Also, in the example shown in Figure 2, the sample volume SV included in this sample gate SG is set on the vessel BV depicted in the ultrasound image IM. The sample gate setting function 383 acquires the coordinates (X) of the center position of the sample volume SV included in this sample gate SG. C ,Y C ) obtain.

[0039] Furthermore, the sample gate setting function 383 accepts a first input operation from the user regarding the adjustment of the sample volume. This first input operation regarding the adjustment of the sample volume is an input operation to start the adjustment of the sample volume, and is, for example, the operation of pressing the sample volume width adjustment button included in the input device 50.

[0040] The acquisition function 384 acquires multiple vessel width candidates for the vessel at the location where the sample gate SG is set, based on at least one of the subject's ultrasound reception information and examination information. Specifically, the acquisition function 384 acquires multiple vessel width candidates for the vessel BV in the ultrasound image IM, which is an ultrasound image IM in which the vessel BV is imaged from one imaging direction, based on at least one of the subject's ultrasound reception information and examination information. For example, in the example shown in Figure 2, the acquisition function 384 acquires multiple vessel width candidates for the vessel BV in the B-mode image IM1, which is an ultrasound image IM in which the longitudinal axis image of the vessel BV is imaged, based on at least one of the subject's ultrasound reception information and examination information, as the vessel BV in the ultrasound image IM in which the vessel BV is imaged from one imaging direction.

[0041] Ultrasound reception information refers to information about the reflected wave signal received by the ultrasound probe 10. Ultrasound reception information includes raw data such as B-mode data and Doppler data before scan conversion processing, and ultrasound images for display after scan conversion processing. Specifically, ultrasound reception information includes, for example, power information related to the power of blood flow based on the reflected wave signal, dispersion information related to the dispersion of blood flow based on the reflected wave signal, velocity information related to the velocity of blood flow based on the reflected wave signal, and B-mode information related to the B-mode based on the reflected wave signal. Power information includes, for example, information about power values ​​in Doppler data, blood flow power in color Doppler data, power images, etc. Dispersion information includes, for example, information about dispersion values ​​in Doppler data, blood flow dispersion in color Doppler data, dispersion images, etc. Velocity information includes, for example, information about velocity values ​​in Doppler data, blood flow velocity values ​​in color Doppler data, velocity images, etc. B-mode information includes, for example, information about the distribution of brightness values ​​in B-mode data and B-mode images. Examination information refers to information related to the ultrasound examination. The examination information includes, for example, the settings of the examination mode, the depth (field of view), and the depth and size of the region of interest (ROI). The settings of the examination mode include information about the examination site, such as the carotid artery, abdomen, and lower extremity blood vessels.

[0042] Therefore, the acquisition function 384 acquires multiple vessel width candidates based on at least two of the following pieces of information: power information, dispersion information, velocity information, B-mode information, and examination information, based on at least two pieces of information. In the following description, the acquisition function 384 according to this embodiment acquires two vessel width candidates based on the examination information and the B-mode information, which is one of the ultrasound reception information.

[0043] First, let's explain an example of how to obtain candidate vessel widths based on examination information. The acquisition function 384 acquires examination information from the memory circuit 37. If the examination information includes the carotid artery as a setting for the examination mode, the acquisition function 384 acquires the diameter of the carotid artery as a candidate vessel width from the first association table stored in the memory circuit 37, based on the examination information. In the example described above, the case where the examination information includes the carotid artery was explained, but the examination site is not limited to the carotid artery. That is, the examination site is arbitrary, and for example, the examination information may include the abdomen. Even if the examination information includes the abdomen, the acquisition function 384 acquires the diameter of the vessel corresponding to the examination site as a candidate vessel width from the first association table. If it is not possible to obtain a candidate vessel width based on the examination information, an error value may be stored in the candidate vessel width based on the examination information.

[0044] Next, Figure 3 will be used to explain how to obtain candidate vessel widths based on B-mode information. Figure 3 is a flowchart for explaining the process of obtaining candidate vessel widths based on B-mode information performed in the main unit 30 of the device. In the process of obtaining candidate vessel widths based on B-mode information shown in Figure 3, the B-mode image IM1 is used to obtain the distribution of brightness values ​​within a certain range, to determine whether or not a vessel has been detected, to obtain the distribution of brightness values ​​on the raster, to obtain a threshold, to search for max(X,Y) and min(X,Y), and to obtain candidate vessel widths based on B-mode information.

[0045] As shown in Figure 3, first, the acquisition function 384 in the processing circuit 38 of the main unit 30 acquires the distribution of brightness values ​​of the B-mode image IM1 within a certain range from the center position of the sample volume SV (step S101). Specifically, the acquisition function 384 acquires the distribution of brightness values ​​within a certain range from the center position of the sample volume SV acquired by the sample gate setting function 383 in the B-mode image IM1, which is an ultrasound image IM.

[0046] Figure 4 shows an example of an ultrasound image IM within a certain range from the center of the sample volume SV. In the example shown in Figure 4, the ultrasound image IM is a B-mode image IM1. In the example shown in Figure 4, the B-mode image IM1, which is the ultrasound image IM, depicts the blood vessel BV, the blood vessel wall BVW, and the tissue OR.

[0047] Figure 5 shows an example of the distribution of luminance values ​​within a certain range from the center position of the sample volume SV. As shown in Figure 5, the acquisition function 384 acquires the luminance value for each pixel in the B-mode image IM1, which is an ultrasound image IM within a certain range from the center position of the sample volume SV, as the distribution of luminance values ​​within a certain range from the center position of the sample volume SV, and acquires a graph G1 with the luminance value on the X axis and the number of pixels on the Y axis.

[0048] Next, as shown in Figure 3, the acquisition function 384 determines whether or not a blood vessel BV can be detected (step S103). Specifically, the acquisition function 384 determines whether or not a blood vessel BV can be detected from the distribution of brightness values ​​acquired in step S101.

[0049] The method for determining blood vessel detection will be explained using Figure 6. Figure 6 shows the distribution of brightness values ​​when blood vessels BV are included within a certain range from the center of the sample volume SV, and when uniform tissue is included within a certain range from the center of the sample volume SV. Graph G1 in Figure 6 shows the distribution of brightness values ​​when blood vessels BV such as carotid arteries are included, and graph G2 in Figure 6 shows the distribution of brightness values ​​when uniform tissue such as the abdomen is included. When the mean and median values ​​of graphs G1 and G2 are calculated, the difference between the median and mean is large in graph G1, while the difference between the median and mean is small in graph G2. In other words, when blood vessels BV are included within a certain range from the center of the sample volume SV, the difference between the mean and median in the brightness value distribution is large. Therefore, the acquisition function 384, as a method for determining blood vessel detection, calculates the mean and median values ​​of the brightness value distribution acquired in step S101, and determines whether blood vessels BV can be detected by determining whether the difference between the mean and median is greater than or equal to a predetermined threshold.

[0050] Furthermore, the acquisition function 384 may determine whether the difference between the mean and median is greater than or equal to a predetermined threshold, and even if it determines that the difference between the mean and median is greater than or equal to a predetermined threshold, it may further determine whether or not blood vessel BV can be detected by comparing the mean of the luminance value distribution with the luminance value at the center of the sample volume. In this case, when the acquisition function 384 determines that the difference between the mean and median is greater than or equal to a predetermined threshold, it compares the mean of the luminance value distribution with the luminance value at the center of the sample volume SV, and determines that blood vessel BV can be detected if the luminance value at the center of the sample volume SV is lower than the mean of the luminance value distribution, and determines that blood vessel BV cannot be detected if the luminance value at the center of the sample volume SV is higher than the mean of the luminance value distribution.

[0051] Then, in step S103, if the blood vessel BV cannot be detected (step S103: No), the acquisition function 384 stores the error values ​​in max(X, Y) and min(X, Y) (step S105).

[0052] On the other hand, if blood vessel BV can be detected in step S103 (step S103: Yes), the acquisition function 384 acquires the distribution of brightness values ​​on the raster RA (step S107). Specifically, the acquisition function 384 acquires the distribution of brightness values ​​on the raster RA at the sample gate SG based on the ultrasound image IM in which the sample gate SG is set.

[0053] Figure 7 shows an example of the distribution of luminance values ​​on a raster RA. In the example shown in Figure 7, the acquisition function 384 acquires a graph G3 with the x-axis representing Depth and the y-axis representing luminance value as the distribution of luminance values ​​on the raster RA. As shown in Figure 5, the luminance value in graph G3 becomes smaller for Depth corresponding to blood vessel BV and larger for Depth corresponding to blood vessel wall BVW.

[0054] Next, as shown in Figure 3, the acquisition function 384 acquires a threshold (step S109). Specifically, the acquisition function 384 acquires a threshold for brightness values ​​based on the distribution of brightness values ​​of the B-mode image IM1 within a certain range from the center position of the sample volume SV acquired in step S101.

[0055] The method for obtaining this threshold will be explained using Figures 8 and 9. Figure 8 is a diagram illustrating the brightness values ​​of blood vessels, tissue, and blood vessel walls. Figure 9 is a diagram showing an example of a threshold obtained based on the distribution of brightness values ​​of the B-mode image IM1 within a certain range from the center position of the sample volume SV. In the graph shown in Figure 8, where the x-axis is brightness value and the y-axis is the number of pixels, the region R1 with a small brightness value can be inferred to be a blood vessel, the region R2 with a high brightness value can be inferred to be a blood vessel wall, and the region R3 between R1 and R2 can be inferred to be tissue. From this, as shown in Figure 9, the acquisition function 384 infers the brightness value representing the blood vessel wall BVW in the brightness value distribution based on graph G1, which is the distribution of brightness values ​​within a certain range from the center position of the sample volume SV, and acquires the inferred brightness value representing the blood vessel wall BVW as the threshold TH.

[0056] Furthermore, since the distribution of luminance values ​​within a certain range from the center position of the sample volume SV varies according to the device settings such as gain, the threshold TH acquired in step S109 also varies according to the device settings such as gain. In other words, the acquisition function 384 may acquire the setting information and acquire the threshold TH based on the setting information and the distribution of luminance values ​​of the B-mode image IM1 within a certain range from the center position of the sample volume SV.

[0057] Next, as shown in Figure 3, the acquisition function 384 searches for max(X, Y) (step S111). Specifically, the acquisition function 384 sets the threshold acquired in step S109 to the distribution of brightness values ​​on the raster RA acquired in step S107, moves the points along the raster RA in the direction of increasing Depth from the center position of the sample volume SV, and searches for the position where the brightness value of the points at each position is greater than or equal to the threshold TH, thereby searching for max(X, Y).

[0058] The method for finding max(X, Y) will be explained using Figures 10 and 11. Figure 10 is a diagram showing an example of the distribution of luminance values ​​on a raster RA with a threshold TH set. Figure 11 is a diagram illustrating an example of the search method. As shown in Figure 10, the acquisition function 384 sets the threshold acquired in step S109 to the distribution of luminance values ​​on the raster RA acquired in step S107. Then, as shown in Figure 11, the acquisition function 384 sets the coordinates (X) of the center position of the sample volume. C ,Y C Move the point along the raster RA in the direction of increasing depth, that is, in the positive Y-axis direction shown in Figure 11, and adjust the coordinates (X',Y C The brightness value of point +1) is obtained. Then, the acquisition function 384 repeatedly moves the point along the raster RA in the positive direction of the Y axis as shown in Figure 11, and by obtaining the brightness value of each point, it searches for a point where the brightness value is greater than or equal to the threshold TH. Note that in the example shown in Figure 11, the graph G3 shown in Figure 10 is superimposed on the ultrasound image IM, but it is not necessary to superimpose the graph G3 on the ultrasound image IM.

[0059] Next, as shown in Figure 3, the acquisition function 384 determines whether or not there are any points with a brightness value equal to or greater than the threshold TH (step S113). Specifically, the acquisition function 384 determines whether or not there are any points with a brightness value equal to or greater than the threshold TH based on the search results in step S111. More specifically, for example, the acquisition function 384 determines whether or not there are any points with a brightness value equal to or greater than the threshold TH by checking whether or not there are consecutive points with a brightness value equal to or greater than the threshold TH. Then, in step S113, if there are no points with a brightness value equal to or greater than the threshold TH (step S113: No), the acquisition function 384 in the processing circuit 38 of the main unit 30 stores an error value in max(X, Y) (step S115).

[0060] The acquisition function 384 determines whether there are points with a brightness value equal to or greater than the threshold TH by determining whether there are points where the brightness value is equal to or greater than the threshold TH in a single consecutive instance. However, it is not limited to this method. In other words, the method for determining whether there are points with a brightness value equal to or greater than the threshold TH is arbitrary. For example, the acquisition function 384 may determine whether there are points with a brightness value equal to or greater than the threshold TH by determining whether there are points where the brightness value is equal to or greater than the threshold TH in a double or triple consecutive instance, or it may determine whether there are points with a brightness value equal to or greater than the threshold TH by determining whether a point where the brightness value is equal to or greater than the threshold TH has been searched for at least once.

[0061] On the other hand, in step S113, if there is a point whose brightness value is greater than or equal to the threshold TH (step S113: Yes), the acquisition function 384 stores max(X, Y) (step S117). Specifically, the acquisition function 384 stores the coordinates of the point obtained by moving back a predetermined amount in the negative direction of the y-axis from the point whose brightness value is greater than or equal to the threshold TH as max(X, Y). More specifically, for example, if there are consecutive points along the raster RA whose brightness value is greater than or equal to the threshold TH, the acquisition function 384 stores the coordinates of the point obtained by moving back 1 in the y-coordinate from the coordinates of the first point whose brightness value is greater than or equal to the threshold TH as max(X, Y). For example, in the example shown in Figure 11, the acquisition function 384 stores (X, Y) as max(X, Y) because the brightness value of the point at coordinate (X'', Y+1) and the brightness value of the point at coordinate (X''', Y+2) consecutively exceed the threshold TH. This is done by moving the y coordinate back by 1 from the coordinate (X'', Y+1) of the first point where the brightness value exceeded the threshold TH along the raster RA.

[0062] The acquisition function 384 is configured to store the coordinates of a point obtained by moving the y-coordinate back by 1 from the coordinates of a point whose brightness value is equal to or greater than the threshold TH as max(X, Y), but is not limited to this. That is, the coordinates that the acquisition function 384 stores as max(X, Y) are arbitrary. For example, based on the search result in step S11, the acquisition function 384 may store the coordinates of one or more points prior to a point whose brightness value is equal to or greater than the threshold TH as max(X, Y), or it may store the coordinates of a point moved by a predetermined value from a point whose brightness value is equal to or greater than the threshold TH as max(X, Y).

[0063] Next, as shown in Figure 3, the acquisition function 384 in the processing circuit 38 of the main body of the device 30 searches for min(X, Y) (step S119). Specifically, the acquisition function 384 sets the threshold TH acquired in step S109 to the distribution of brightness values ​​on the raster RA acquired in step S107, moves the points along the raster RA in the direction of decreasing depth from the center position of the sample volume SV, and searches for a position where the brightness value of the points at each position is greater than or equal to the threshold TH, thereby searching for min(X, Y).

[0064] The method for finding min(X, Y) will be explained using Figures 10 and 11. As shown in Figure 10, the acquisition function 384 sets the threshold acquired in step S109 to the distribution of brightness values ​​on the raster RA acquired in step S107. Then, as shown in Figure 11, the acquisition function 384 uses the coordinates (X) of the center position of the sample volume. C ,Y CThe point is moved along the raster RA in the direction of decreasing depth, that is, in the negative y-axis direction shown in Figure 11, which is the opposite direction to the direction in which max(X, Y) was searched, and the brightness value of the point after the move is obtained. The acquisition function 384 then repeatedly moves the point along the raster RA in the negative y-axis direction shown in Figure 11 and obtains the brightness value of each point to search for a point whose brightness value is greater than or equal to TH. Note that the processing in step S121 is equivalent to the processing in step S113 described above, so the explanation is omitted. If there is no point in step S121 that is greater than or equal to the threshold TH (step S121: No), the acquisition function 384 in the processing circuit 38 of the device body 30 stores an error value in min(X, Y) (step S123).

[0065] On the other hand, if there is a point in step S121 where the brightness value is greater than or equal to the threshold TH (step S121: Yes), the acquisition function 384 in the processing circuit 38 of the main unit 30 stores min(X, Y) (step S125). Specifically, the acquisition function 384 stores the coordinates of the point obtained by moving back a predetermined amount in the positive direction of the y-axis from the point where the brightness value is greater than or equal to the threshold TH as min(X, Y). More specifically, for example, the acquisition function 384 stores the coordinates of the point obtained by moving back 1 unit in the y-coordinate from the coordinates of the first point along the raster RA where the brightness value is greater than or equal to the threshold TH as min(X, Y).

[0066] The acquisition function 384 is configured to store the coordinates of a point obtained by moving the y-coordinate back by 1 from the coordinates of a point whose brightness value is equal to or greater than the threshold TH as min(X, Y), but is not limited to this. That is, the coordinates that the acquisition function 384 stores as min(X, Y) are arbitrary. For example, based on the search result in step S11, the acquisition function 384 may store the coordinates of a point one or more positions prior to the point whose brightness value is equal to or greater than the threshold TH as min(X, Y), or it may store the coordinates of a point moved by a predetermined value from the point whose brightness value is equal to or greater than the threshold TH as min(X, Y).

[0067] Next, as shown in Figure 3, the acquisition function 384 acquires a candidate vessel width based on B-mode information (step S127). Specifically, the acquisition function 384 acquires a candidate vessel width based on B-mode information based on max(X, Y) and min(X, Y). More specifically, if no error values ​​are stored in either max(X, Y) or min(X, Y), the acquisition function 384 acquires, for example, the absolute value of the difference between the respective Y coordinates of max(X, Y) and min(X, Y) as a candidate vessel width. Also, if an error value is stored in at least one of max(X, Y) or min(X, Y), the acquisition function 384 acquires, for example, the error value as a candidate vessel width.

[0068] Then, in step S127, the process of acquiring candidate vessel widths based on B-mode information is terminated by obtaining candidate vessel widths based on B-mode information.

[0069] Returning to Figure 1, the adjustment function 385 adjusts the region included in the sample gate SG based on multiple vessel width candidates. For example, the adjustment function 385 adjusts the sample volume SV based on multiple vessel width candidates. In this embodiment, the adjustment function 385 adjusts the width of the sample volume SV based on multiple vessel width candidates.

[0070] Figure 12 shows an example of how to adjust the sample volume SV. In the example shown in Figure 12, the adjustment function 385 adjusts the width of the sample volume SV by moving the lower end SV1 of the sample volume SV to the max(X, Y) position and the upper end of the sample volume SV to the min(X, Y) position, based on multiple candidate vessel widths. As shown in Figure 12, the adjusted sample volume SV' is adjusted to a width corresponding to the vessel width of vessel BV, with the lower end SV1' and the upper end SV2' of the sample volume SV' positioned near the lower and upper ends of vessel BV, respectively.

[0071] The input device 50 includes a mouse, keyboard, buttons, panel switches, touch command screen, wheel, dial, foot switch, trackball, joystick, etc., and receives various setting requests from the user of the ultrasound diagnostic device 1 and transmits the received setting requests to the device body 30. The input device 50 has, for example, a sample volume width adjustment button for initiating the adjustment of the sample volume SV.

[0072] The display 70 displays a GUI (Graphical User Interface) for the user of the ultrasound diagnostic device 1 to input various setting requests using the input device 50, and also displays ultrasound images (IM) and Doppler waveforms generated by the device body 30. The display 70 also displays various messages to notify the user of the processing status of the device body 30. The display 70 also has a speaker and can output sound. For example, the speaker of the display 70 outputs predetermined sounds such as beeps to notify the user of the processing status of the device body 30. This display 70 corresponds to the display unit in this embodiment.

[0073] Figure 13 is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic device 1 according to the first embodiment. The sample volume width adjustment process shown in Figure 13 involves setting the sample gate SG, obtaining the center position of the sample volume SV, obtaining vessel width candidates based on examination information, obtaining vessel width candidates based on B-mode information, comparing vessel width candidates, determining the likelihood of the vessel width, and adjusting the width of the sample volume SV. For example, the sample volume width adjustment process is performed when PWD mode is activated.

[0074] As shown in Figure 13, first, the sample gate setting function 383 in the processing circuit 38 of the main unit 30 sets the sample gate SG (step S11). Specifically, the sample gate setting function 383 sets the sample gate SG, which includes the sample volume SV, in the B-mode image IM1, which is an ultrasound image IM in which a long-axis view of the blood vessel BV is captured. More specifically, for example, the sample gate setting function 383 receives an input operation from the user to set the sample gate SG, and based on the received input operation to set the sample gate SG, it sets the sample volume SV included in the sample gate SG at the position of the blood vessel BV depicted in the B-mode image IM1.

[0075] Figure 14 shows an example of an ultrasound image IM with a sample gate SG set. As shown in Figure 14, a sample gate SG is set in the B-mode image IM1, which is an ultrasound image IM in which a long-axis view of the blood vessel BV is acquired. In the example shown in Figure 14, the sample volume SV included in this sample gate SG is set on the blood vessel BV depicted in the B-mode image IM1. Also, in the example shown in Figure 14, a region of interest (ROI) is set in the B-mode image IM1, which is an ultrasound image IM.

[0076] Next, as shown in Figure 13, the sample gate setting function 383 determines whether the automatic sample volume width adjustment trigger has been turned ON (step S13). Specifically, the sample gate setting function 383 determines whether the automatic sample volume width adjustment trigger has been turned ON by determining whether or not it has received a first input operation from the user regarding the adjustment of the width of the sample volume SV. More specifically, during the execution of a PWD mode scan, the sample gate setting function 383 determines whether or not the automatic sample volume width adjustment trigger has been turned ON by determining whether or not it has received confirmation that the sample volume width adjustment button, which is the first input operation regarding the adjustment of the width of the received sample volume SV, has been pressed. Then, in step S13, if the automatic sample volume width adjustment trigger is not turned ON (step S13: No), the process in step S13 is repeated and the function waits until the automatic sample volume width adjustment trigger is turned ON.

[0077] On the other hand, in step S13, if the automatic sample volume width adjustment trigger is ON, that is, if the first input operation is received after setting the sample gate SG to the ultrasound image IM while performing a PWD mode scan (step S13: Yes), the sample gate setting function 383 acquires the center position of the sample volume SV (step S15). Specifically, the sample gate setting function 383 acquires the coordinates of the center position of the sample volume SV in the ultrasound image IM. In this embodiment, as shown in Figure 13, if a region of interest (ROI) is set, the sample gate setting function 383 acquires the coordinates of the center position of the sample volume SV in the region of interest (ROI).

[0078] Next, as shown in Figure 13, the acquisition function 384 in the processing circuit 38 of the device body 30 acquires a candidate for the vessel width based on the examination information as the first candidate for the vessel width (step S17). Specifically, the acquisition function 384 acquires the examination information and acquires a candidate for the vessel width based on the examination information, thereby acquiring a candidate for the vessel width based on the examination information as the first candidate for the vessel width. In this embodiment, the acquisition function 384 acquires the carotid artery as the setting of the examination mode included in the examination information, and acquires 5.4 ± 1.0 mm as the vessel diameter of the carotid artery from the first association table stored in the memory circuit 37. This candidate for the vessel width based on the examination information is set as the maximum search range.

[0079] Next, as shown in Figure 13, the acquisition function 384 acquires a second vessel width candidate based on B-mode information (step S19). Specifically, the acquisition function 384 acquires a second vessel width candidate based on B-mode information by executing the above-described process for acquiring a vessel width candidate based on B-mode information.

[0080] Figure 15 is an example of the distribution of luminance values ​​within a certain range from the center position of the sample volume SV, acquired in the ultrasound image IM shown in Figure 14, and corresponds to Figure 5. In the example shown in Figure 15, the acquisition function 384 acquires graph G1, which shows the distribution of luminance values ​​within the region of interest (ROI) shown in Figure 14, as the distribution of luminance values ​​within a certain range from the center position of the sample volume SV. Furthermore, the acquisition function 384 acquires a threshold TH based on the distribution of luminance values ​​in the region of interest (ROI) shown in Figure 15.

[0081] Figure 16 is an example of the distribution of brightness values ​​on the raster RA acquired in the ultrasound image IM shown in Figure 14, and corresponds to Figure 7. In the example shown in Figure 16, the acquisition function 384 acquires a graph G4 with Depth on the x-axis and brightness value on the y-axis as the distribution of brightness values ​​on the raster RA at the sample gate SG of the ultrasound image IM shown in Figure 14. Then, as shown in Figure 16, the acquisition function 384 sets a threshold TH obtained from the distribution of brightness values ​​within a certain range from the center position of the sample volume SV shown in Figure 15 to graph G4, searches for max(X, Y) and min(X, Y), and stores max(X, Y) and min(X, Y). In the example shown in Figure 16, the acquisition function 384 acquires 5.2 mm as a candidate vessel width based on B-mode information.

[0082] Next, as shown in Figure 13, the adjustment function 385 in the processing circuit 38 of the main body of the device 30 compares the first vessel width candidate with the second vessel width candidate (step S21). Specifically, the adjustment function 385 compares multiple vessel width candidates based on multiple vessel width candidates. More specifically, the adjustment function 385 compares the vessel width candidate based on the examination information acquired as the first vessel width candidate in step S17 with the vessel width candidate based on the B-mode information acquired as the second vessel width candidate in step S19. For example, the adjustment function 385 compares whether the vessel width candidate based on the B-mode information is within the range of the vessel width candidate based on the examination information.

[0083] Next, as shown in Figure 13, the adjustment function 385 determines whether the vessel width candidate is likely or not (step S23). Specifically, the adjustment function 385 determines whether the vessel width candidate is likely or not based on the comparison result, which is the result of comparing multiple vessel width candidates. More specifically, the adjustment function 385 determines whether the vessel width candidate based on B-mode information is likely or not based on the comparison result between the vessel width candidate based on the examination information acquired as the first vessel width candidate and the vessel width candidate based on B-mode information acquired as the second vessel width candidate. For example, the adjustment function 385 determines that the vessel width candidate is unlikely if at least one of the first vessel width candidate and the second vessel width candidate is an error value. Also, for example, the adjustment function 385 determines that the vessel width candidate is unlikely if the vessel width candidate based on B-mode information acquired as the second vessel width candidate is not within the range of the vessel width candidate based on the examination information acquired as the first vessel width candidate. On the other hand, the adjustment function 385 determines that a candidate vessel width is likely if, for example, the candidate vessel width based on B-mode information falls within the range of candidate vessel widths based on the examination information. In this embodiment, if the range of candidate vessel widths based on the examination information acquired in step S17 is 5.4 ± 1.0 mm, and the candidate vessel width based on B-mode information acquired in step S19 is 5.2 mm, the adjustment function 385 determines that the candidate vessel width is likely because the candidate vessel width based on B-mode information falls within the range of candidate vessel widths based on the examination information.

[0084] Then, in step S23, if the candidate vessel width is determined to be likely (step S23: Yes), the adjustment function 385 adjusts the width of the sample volume SV (step S25). Specifically, if the adjustment function 385 determines that the candidate vessel width is likely, it adjusts the width of the sample volume SV based on the candidate vessel width determined to be likely. More specifically, if the adjustment function 385 determines that the candidate vessel width based on the B-mode information is likely, it adjusts the width of the sample volume SV based on the candidate vessel width based on the B-mode information.

[0085] In this embodiment, for example, based on max(X, Y) and min(X, Y) in the blood vessel width candidates according to the B-mode information obtained in step S19, the width of the pre-adjustment sample volume SV included in the sample gate SG set in step S11, and the center position of the sample volume SV obtained in step S15, the adjustment function 385 adjusts the width of the sample volume SV by using the following formulas (1) and (2).

Number

Number

[0086] The adjustment function 385 adjusts the upper end SV2 of the sample volume SV by moving the position of the upper end SV2 of the sample volume SV along the raster RA so as to extend the distance in the y-axis direction from the center position of the sample volume SV to the upper end SV2 of the sample volume SV according to the extension rate of the upper end SV2 of the sample volume SV calculated from the above formula (1). Further, the adjustment function 385 adjusts the lower end SV1 of the sample volume SV by moving the position of the lower end SV1 of the sample volume SV along the raster RA so as to extend the distance in the y-axis direction from the center position of the sample volume SV to the lower end SV1 of the sample volume SV according to the extension rate of the lower end SV1 of the sample volume SV calculated from the above formula (2). Then, by adjusting each of the upper end SV2 and the lower end SV1 of the sample volume SV, the width of the sample volume SV is adjusted.

[0087] Figure 17 shows an example of an ultrasound image IM with a sample gate SG, including the sample volume SV, set before and after adjustment. As shown in Figure 17(a), before adjustment by the adjustment function 385, the sample volume SV is not of an appropriate width relative to the vessel width. On the other hand, as shown in Figure 17(b), after adjustment by the adjustment function 385, the sample volume SV' is of an appropriate width relative to the vessel width. Also, as shown in Figure 17(b), at the lower end of the sample volume SV', an overhang region PR1 of the vessel BV is generated in the color Doppler image IM2 superimposed on the B-mode image IM1, but the lower end SV1' of the sample volume is adjusted without being affected by the overhang region PR1.

[0088] In step S23, if the candidate vessel width is not likely (step S23: No), or in step S25, the sample volume width adjustment process is terminated by adjusting the width of the sample volume SV.

[0089] As described above, in the ultrasound diagnostic device 1, a sample gate SG containing the sample volume SV is set to the B-mode image IM1, which is the ultrasound image IM. For the blood vessel at the position where the sample gate SG is set, multiple blood vessel width candidates are acquired, including a blood vessel width candidate based on examination information and a blood vessel width candidate based on B-mode information. Based on the blood vessel width candidates based on examination information and the blood vessel width candidates based on B-mode information, the sample volume SV included in the sample gate SG is adjusted. This eliminates the need to manually adjust the sample volume SV for each blood vessel, and allows for appropriate adjustment of the sample volume SV according to the blood vessel width, thereby improving the examination efficiency and accuracy in PWD mode.

[0090] Furthermore, in the ultrasound diagnostic device 1, the sample volume SV included in the sample gate SG is adjusted based on the candidate vessel width based on the examination information and the candidate vessel width based on the B-mode information. By adjusting the sample volume SV using high-resolution B-mode information, it is possible to determine the vessel width with high accuracy.

[0091] [Second Embodiment] In the ultrasound diagnostic apparatus 1 according to the first embodiment described above, the adjustment function 385 compares a first blood vessel width candidate with a second blood vessel width candidate to determine the likelihood of the blood vessel width, and if it is determined that the blood vessel width candidate is unlikely, it does not adjust the sample volume SV, but it is not limited to this. In the second embodiment, an ultrasound diagnostic apparatus 1 that acquires a third blood vessel width candidate when it is determined that the blood vessel width candidate is unlikely will be described.

[0092] Figure 18 is a block diagram showing an example of the configuration of the ultrasound diagnostic apparatus 1 according to the second embodiment, and corresponds to Figure 1. As shown in Figure 18, in the ultrasound diagnostic apparatus 1 according to the second embodiment, the acquisition function of the processing circuit 38 differs from that of the first embodiment described above, and is therefore referred to as the acquisition function 384a. Note that the configuration and functions other than the acquisition function 384a are the same as those in Figure 1, so their explanation is omitted.

[0093] The acquisition function 384a acquires a third vessel width candidate when the first vessel width candidate is deemed unlikely. Specifically, the acquisition function 384a acquires a third vessel width candidate based on power information. This vessel width candidate acquired based on power information is, for example, a vessel width candidate acquired based on power values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion processing, or a power image for display after scan conversion processing. In particular, the vessel width candidate acquired based on power values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion processing is a vessel width candidate acquired based on data before it is converted to brightness values ​​by scan conversion by the image generation circuit 35. Therefore, by acquiring a vessel width candidate acquired based on power values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion processing, the acquisition function 384a can acquire a more accurate vessel width candidate. Note that the vessel width candidate acquired based on power information may also be a vessel width candidate acquired based on power information in the Doppler data before the MTI filter is applied. In the following explanation, we will describe the case where the candidate vessel width obtained based on power information is obtained based on power information that includes power values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion processing.

[0094] Figure 19 is a flowchart illustrating the process of acquiring candidate vessel widths based on power information, which is performed in the main unit 30 of the device. In this process of acquiring candidate vessel widths based on power information, the power information is used to acquire the power value at the center position of the sample volume SV, to acquire the power value on the raster RA, to determine whether the power value is less than a predetermined value, to store max(X,Y) and min(X,Y), and to acquire candidate vessel widths based on the power information.

[0095] As shown in Figure 19, first, the acquisition function 384a in the processing circuit 38 of the main unit 30 acquires the power value at the center position of the sample volume SV (step S201). Specifically, the acquisition function 384a uses color Doppler mode to acquire the power value of the blood flow at the center position of the sample volume SV included in the sample gate SG set in the color Doppler image IM2.

[0096] Next, as shown in Figure 19, the acquisition function 384a determines whether the power value is above a threshold (step S203). Specifically, the acquisition function 384a determines whether the power value of the blood flow at the center of the sample volume SV acquired in step S201 is above a threshold. The threshold in step S203 is, for example, the threshold used when suppressing clutter signals in the MTI filter.

[0097] Then, in step S203, if the power value is not above the threshold, that is, if the power value is below the threshold (step S203: No), the acquisition function 384a determines whether a certain period of time has elapsed (step S205). Specifically, the acquisition function 384a determines whether a certain period of time has elapsed since the start of the process of acquiring candidate blood vessel widths based on power information. This certain period is a period set by the user, for example, 1 second for 60 heartbeats.

[0098] Then, in step S205, if a certain period of time has not elapsed (step S205: No), the process from steps S201 to S205 is repeated until the power value exceeds the threshold or a certain period of time has elapsed. In other words, if the power value is below the threshold, the system recognizes that the blood flow is pulsatile and waits for a phase in which a blood flow power value above the threshold occurs.

[0099] On the other hand, if a certain period of time has elapsed in step S205 (step S205: No), the acquisition function 384 stores the error values ​​in max(X, Y) and min(X, Y) (step S207).

[0100] On the other hand, in step S203, if the power value is greater than or equal to the threshold (step S203: Yes), the acquisition function 384a acquires the power value at the y-coordinate plus 1 (step S209). Specifically, the acquisition function 384a acquires the power value of blood flow at the position of the y-coordinate plus 1 along the raster RA. Note that in step S209, the acquisition function 384a acquires the power value of blood flow at the position of the y-coordinate plus 1, but the value added to the y-coordinate is not limited to 1. That is, the value added to the y-coordinate is arbitrary, and may be between 0 and 1, or greater than 1.

[0101] Figure 20 shows an example of a method for acquiring power values. In the example shown in Figure 20, the ultrasound image IM is a color Doppler image IM2 superimposed on a B-mode image IM1. A sample gate SG is set on the color Doppler image IM2, which is superimposed on the B-mode image IM1 (ultrasound image IM), and the sample volume SV included in the sample gate SG is the coordinate (X) of the center position. C ,Y C It is located at ). In the example shown in Figure 20, the acquisition function 384a acquires the coordinates (X) of the center position along the raster RA in step S209. C ,Y C The coordinate obtained by adding 1 to the y-coordinate of (X',Y C Get the blood flow power value at position +1).

[0102] Next, as shown in Figure 19, the acquisition function 384a determines whether the power value is below a threshold and stores the result (step S211). Specifically, the acquisition function 384a determines whether the power value of the blood flow acquired in step S209 is below a threshold, associates the coordinates of the location where the blood flow power value was acquired with the determination result, and stores it in the memory circuit 37.

[0103] Next, as shown in Figure 19, the acquisition function 384a acquires the y coordinate Y C It is determined whether or not +n has been reached (step S213). Specifically, the acquisition function 384a determines whether the y coordinate when the power value was acquired in step S209 is YC Determine whether or not +n has been reached. The value of n is, for example, if the value of n is set to 9, then Y C +9 indicates that the acquisition of the blood flow power value at a coordinate obtained by adding 1 to the y coordinate is repeated 9 times. The accuracy of blood vessel detection increases as the value of n increases; in other words, the accuracy of blood vessel detection depends on the value of n. This value of n can be set arbitrarily by the user or a fixed value may be set. Note that in step S213, the acquisition function 384a is performed when the y coordinate is Y C The system is designed to determine whether or not it has reached +n, but it is not limited to this. For example, the acquisition function 384a may determine whether or not the y coordinate has reached a value arbitrarily set by the user, or it may determine whether or not the y coordinate has reached the lower end of the scan range in the ultrasound image IM.

[0104] Then, in step S213, the y coordinate is Y C If +n has not been reached (step S213: No), the acquisition function 384a returns to step S209 and performs the process of acquiring the power value (step S209), the process of determining whether the power value is less than the threshold and storing the result (step S211), and the y coordinate is Y C The process of determining whether or not +n has been reached (step S213) is repeated until the y coordinate is Y C Wait until +n is reached.

[0105] On the other hand, in step S213, the y coordinate is Y C If +n is reached (step S213: Yes), the acquisition function 384a determines whether the power value is less than the threshold (step S215). Specifically, the acquisition function 384a determines whether the power value is less than the threshold based on the determination result stored in step S211. Then, in step S215, if the power value is not less than the threshold (step S215: No), the acquisition function 384a stores the error value in max(X, Y) (step S217).

[0106] On the other hand, in step S215, if the power value is less than the threshold (step S215: Yes), the acquisition function 384a stores max(X, Y) (step S219). Specifically, the acquisition function 384a stores max(X, Y) the coordinates obtained by moving back a predetermined amount in the negative direction of the y axis from the coordinate with the smallest y-coordinate value of the position where the judgment result in which the power value of the blood flow corresponding to the judgment result in which the power value of the power value of the blood flow was acquired, among the judgment results in which the power value of the power value of the power value of the blood flow corresponding to the judgment result in which the power value of the power value of the blood flow was acquired, among the judgment results in which the power value of the power value of the blood flow corresponding to the judgment result in which the power value of the power value of the blood flow was acquired, among the judgment results in which the power value of the power value of the blood flow was acquired, along the raster RA. For example, in the example shown in Figure 20, the acquisition function 384a determines that the smallest y-coordinate value of the position where the power value of the blood flow corresponding to the judgment result where the power value is less than the threshold was acquired was (X'',Y+1). Therefore, it stores (X',Y), which is obtained by moving the y-coordinate back by 1 from (X'',Y+1) along the raster RA, as max(X,Y).

[0107] After processing in steps S217 and S219, as shown in Figure 19, the acquisition function 384a acquires the power value at a coordinate obtained by subtracting 1 from the y-coordinate (step S221). Specifically, the acquisition function 384a acquires the power value of blood flow at a position obtained by subtracting 1 from the y-coordinate along the raster RA. More specifically, for example, in the example shown in Figure 20, in step S221, the acquisition function 384a acquires the power value of blood flow at a position obtained by subtracting 1 from the y-coordinate along the raster RA. C ,Y C The coordinate obtained by subtracting 1 from the y-coordinate of (X',Y C The power value of the blood flow at position -1) is obtained. Note that in step S209, the acquisition function 384a obtains the power value of the blood flow at the position of the y coordinate minus 1, but the value subtracted from the y coordinate is not limited to 1. That is, the value subtracted from the y coordinate is arbitrary and may be between 0 and 1, or greater than 1.

[0108] Next, as shown in Figure 19, the acquisition function 384a in the processing circuit 38 of the main body of the device 30 determines whether the power value is less than a threshold and stores the result (step S223). Specifically, the acquisition function 384a determines whether the power value of the blood flow acquired in step S221 is less than a threshold, associates the coordinates of the location where the blood flow power value was acquired with the determination result, and stores it in the storage circuit 37.

[0109] Next, as shown in Figure 19, the acquisition function 384a acquires the y coordinate Y C It is determined whether -n has been reached (step S225). Specifically, the acquisition function 384a determines whether the y coordinate at the time the power value was acquired in step S221 is Y C Determine whether -n has been reached. The value of n is, for example, if the value of n is set to 9, then Y C -9 indicates that the acquisition of the blood flow power value at a coordinate obtained by subtracting 1 from the y-coordinate is repeated 9 times. The accuracy of blood vessel detection increases as the value of n increases; in other words, the accuracy of blood vessel detection depends on the value of n. This value of n can be set arbitrarily by the user or a fixed value may be set. Note that in step S221, the acquisition function 384a is performed when the y-coordinate is Y C The function is designed to determine whether or not -n has been reached, but it is not limited to this. For example, the acquisition function 384a may determine whether or not the y coordinate has reached a value arbitrarily set by the user, or it may determine whether or not the y coordinate has reached the upper end of the scan range in the ultrasound image IM.

[0110] Then, in step S225, the y coordinate is Y C If -n has not been reached (step S225: No), the acquisition function 384a returns to step S221 and performs the process of acquiring the power value (step S221), the process of determining whether the power value is less than the threshold and storing the result (step S223), and the y coordinate is Y C The process of determining whether or not -n has been reached (step S225) is repeated until the y coordinate is Y C Wait until -n is reached.

[0111] On the other hand, in step S225, the y coordinate is Y C If -n is reached (step S225: Yes), the acquisition function 384a determines whether the power value is less than the threshold (step S227). Specifically, the acquisition function 384a determines whether the power value is less than the threshold based on the determination result stored in step S223. Then, in step S227, if the power value is not less than the threshold (step S227: No), the acquisition function 384a stores the error value in min(X, Y) (step S229).

[0112] On the other hand, in step S227, if the power value is less than the threshold (step S227: Yes), the acquisition function 384a stores min(X, Y) (step S231). Specifically, the acquisition function 384a stores min(X, Y) as the coordinates obtained by moving back a predetermined amount in the positive direction of the y axis from the coordinate with the largest y-coordinate value of the position where the power value of the blood flow corresponding to the judgment result in which the power value was less than the threshold was first obtained, among the judgment results in which the power value was less than the threshold stored in step S223. More specifically, the acquisition function 384a stores min(X, Y) as the coordinates obtained by moving back 1 unit in the positive direction of the y axis from the coordinate with the largest y-coordinate value of the position where the power value of the blood flow corresponding to the judgment result in which the power value was less than the threshold was obtained, along the raster RA.

[0113] Next, as shown in Figure 19, the acquisition function 384a acquires a candidate vessel width based on power information (step S233). Specifically, the acquisition function 384a acquires a candidate vessel width based on power information based on max(X, Y) and min(X, Y). More specifically, if no error values ​​are stored in either max(X, Y) or min(X, Y), the acquisition function 384a acquires, for example, the absolute value of the difference between the y coordinates of max(X, Y) and min(X, Y) as a candidate vessel width. Also, if an error value is stored in at least one of max(X, Y) or min(X, Y), the acquisition function 384a acquires, for example, the error value as a candidate vessel width.

[0114] Then, in step S233, the process of obtaining candidate vessel widths based on power information is terminated by obtaining candidate vessel widths based on power information.

[0115] Figure 21 is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic apparatus 1 according to the second embodiment, and corresponds to Figure 13. In the sample volume width adjustment process shown in Figure 21, if the candidate vessel width is not likely, a candidate vessel width based on power information is obtained, the candidate vessel width based on examination information is compared with the candidate vessel width based on power information, the likelihood of the vessel width is determined, and the width of the sample volume SV is adjusted. For example, the sample volume width adjustment process is performed when the PWD mode is activated. Note that the processes in steps S11 to S17 shown in Figure 21 are equivalent to those in Figure 13, so their explanation is omitted.

[0116] Next, as shown in Figure 21, the acquisition function 384a in the processing circuit 38 of the device body 30 acquires a second vessel width candidate based on B-mode information (step S19a). Specifically, the acquisition function 384a acquires a second vessel width candidate based on B-mode information by executing the vessel width candidate acquisition process based on B-mode information described above.

[0117] Figure 22 is an example of the distribution of brightness values ​​within a certain range from the center position of the sample volume SV acquired in the ultrasound image IM, and corresponds to Figure 15. In the example shown in Figure 22, the acquisition function 384a acquires graph G5, which shows the distribution of brightness values ​​within the region of interest (ROI) set on the ultrasound image IM, as the distribution of brightness values ​​within a certain range from the center position of the sample volume SV. Furthermore, the acquisition function 384a acquires a threshold TH2 based on the distribution of brightness values ​​in the region of interest (ROI) shown in Figure 22.

[0118] Figure 23 shows an example of the distribution of brightness values ​​on the raster RA acquired in the ultrasound image IM shown in Figure 22, and corresponds to Figure 16. In the example shown in Figure 23, the acquisition function 384a acquires a graph G6 with the x-axis as Depth and the y-axis as Brightness Value, representing the distribution of brightness values ​​on the raster RA at the sample gate SG of the ultrasound image IM. Then, as shown in Figure 23, the acquisition function 384a sets a threshold TH2, obtained from the distribution of brightness values ​​within a certain range from the center position of the sample volume SV in Figure 22, to graph G6, searches for max(X, Y) and min(X, Y), and stores max(X, Y) and min(X, Y). In the example shown in Figure 23, the acquisition function 384a acquires 3.1 mm as a candidate vessel width based on B-mode information. Note that the processing in step S21 is equivalent to that in Figure 13, so the explanation is omitted.

[0119] Next, as shown in Figure 21, the adjustment function 385 in the processing circuit 38 of the device body 30 determines whether the vessel width candidate is likely or not (step S23a). In this embodiment, if the range of the vessel width candidate based on the examination information acquired in step S17 is 5.4 ± 1.0 mm, while the vessel width candidate based on the B-mode information acquired in step S19a is 3.1 mm, the adjustment function 385 determines that the vessel width candidate is unlikely because the vessel width candidate based on the B-mode information is not within the range of the vessel width candidate based on the examination information. Note that the explanation of step S23a other than that described above is the same as the explanation of step S23 in Figure 13, so the explanation is omitted.

[0120] Then, in step S23a, if it is determined that the vessel width candidate is unlikely (step S23a: No), the acquisition function 384a acquires a third vessel width candidate based on power information (step S31). Specifically, the acquisition function 384a acquires a third vessel width candidate based on power information by executing the process for acquiring a vessel width candidate based on power information described above.

[0121] Figure 24 shows an example of the distribution of power values ​​on the raster RA. In the example shown in Figure 24, the acquisition function 384a acquires a graph G7 with the x-axis representing Depth and the y-axis representing Power Value as the distribution of power values ​​on the raster RA. This graph G7 is acquired by executing the processes from steps S209 to S213 and steps S221 to S225 in the process of acquiring candidate vessel widths based on power information. Also, as shown in Figure 24, the distribution of power values ​​on the raster RA is set to the threshold TH3 used in steps S211 and S223 of the process of acquiring candidate vessel widths based on power information. In the example shown in Figure 24, the acquisition function 384a acquires 6.2 mm as a candidate vessel width based on power information.

[0122] Next, as shown in Figure 21, the adjustment function 385 compares the first vessel width candidate with the third vessel width candidate (step S33). Specifically, the adjustment function 385 compares multiple vessel width candidates based on multiple vessel width candidates. More specifically, the adjustment function 385 compares the vessel width candidate based on the examination information acquired as the first vessel width candidate in step S17 with the vessel width candidate based on the power information acquired as the third vessel width candidate in step S31. For example, the adjustment function 385 compares whether the vessel width candidate based on the power information falls within the range of the vessel width candidate based on the examination information.

[0123] Next, as shown in Figure 21, the adjustment function 385 determines whether the vessel width candidate is likely or not (step S35). Specifically, the adjustment function 385 determines whether the vessel width candidate is likely or not based on the comparison result, which is the result of comparing multiple vessel width candidates. More specifically, the adjustment function 385 determines whether the vessel width candidate based on power information is likely or not based on the comparison result between the vessel width candidate based on examination information acquired as the first vessel width candidate and the vessel width candidate based on power information acquired as the third vessel width candidate. For example, if at least one of the first vessel width candidate and the third vessel width candidate is an error value, the adjustment function 385 determines that the vessel width candidate is not likely. Also, for example, if the vessel width candidate based on power information is not within the range of the vessel width candidate based on examination information, the adjustment function 385 determines that it is not likely. On the other hand, for example, if the vessel width candidate based on power information is within the range of the vessel width candidate based on examination information, the adjustment function 385 determines that the vessel width candidate is likely. In this embodiment, for example, if the range of candidate vessel widths based on the inspection information acquired in step S17 is 5.4 ± 1.0 mm, and the range of candidate vessel widths based on the power information acquired in step S31 is 6.2 mm, the adjustment function 385 determines that the candidate vessel width is likely because the candidate vessel width based on the power information is within the range of the candidate vessel widths based on the inspection information.

[0124] Then, in step S35, if the candidate vessel width is determined to be likely (step S35: Yes), the adjustment function 385 adjusts the width of the sample volume SV (step S25a). Specifically, the adjustment function 385 adjusts the width of the sample volume SV based on the candidate vessel width based on power information, which was determined to be within the range of candidate vessel widths based on the examination information in step S23a.

[0125] Figure 25 shows an example of an ultrasound image IM with a sample gate SG, including the sample volume SV, set before and after adjustment of the width of the sample volume SV. As shown in Figure 25(a), before adjustment by the adjustment function 385, the sample volume SV is not of an appropriate width for the vessel width. On the other hand, as shown in Figure 25(b), after adjustment by the adjustment function 385, the sample volume SV' is of an appropriate width for the vessel width.

[0126] In step S35, if the candidate vessel width is not likely (step S35: No), or if the sample volume width adjustment process is terminated by adjusting the width of the sample volume SV in step S25a.

[0127] As described above, in the ultrasound diagnostic device 1, a sample gate SG containing the sample volume SV is set to the B-mode image IM1, which is the ultrasound image IM. For the blood vessel at the position where the sample gate SG is set, multiple blood vessel width candidates are acquired, including a blood vessel width candidate based on examination information and a blood vessel width candidate based on B-mode information. If the blood vessel width candidate is not reliable, a blood vessel width candidate based on power information is acquired. Based on the blood vessel width candidate based on examination information and the blood vessel width candidate based on power information, the sample volume SV included in the sample gate SG is adjusted. This eliminates the need to manually adjust the sample volume SV for each blood vessel, and allows for appropriate adjustment of the sample volume SV according to the blood vessel width, thereby improving the examination efficiency and accuracy in PWD mode.

[0128] [Third Embodiment] In the ultrasound diagnostic apparatus 1 according to the first and second embodiments described above, if the vessel width candidate acquired by the acquisition function is deemed unlikely when comparing it with other vessel width candidates acquired by the acquisition function, the width of the sample volume is not adjusted. However, the method of adjusting the width of the sample volume is not limited to this. In the third embodiment, even if the vessel width candidate acquired by the acquisition function is deemed unlikely when comparing it with other vessel width candidates acquired by the acquisition function, the width of the sample volume SV may be adjusted based on one of max(X, Y) and min(X, Y) in the vessel width candidate based on B-mode information and the vessel width candidate based on the examination information. The third embodiment will describe the case where this modification is applied to the second embodiment described above, and the differences from the second embodiment will be explained below. In the following, the case where this modification is applied to the first embodiment will be described, but this modification is also applicable to the first embodiment described above.

[0129] Figure 26 is a block diagram showing an example of the configuration of the ultrasound diagnostic apparatus 1 according to the third embodiment, and corresponds to Figure 1. As shown in Figure 26, in the ultrasound diagnostic apparatus 1 according to the third embodiment, the acquisition function of the processing circuit 38 differs from that of the first embodiment described above, and is therefore referred to as the acquisition function 384b. Note that the configuration and functions other than the acquisition function 384b are the same as those in Figure 1, so their explanation is omitted.

[0130] The acquisition function 384b acquires a fourth vessel width candidate based on velocity information. Furthermore, the acquisition function 384b acquires a fifth vessel width candidate based on dispersion information. The vessel width candidates acquired based on velocity information are, for example, vessel width candidates acquired based on velocity values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion processing, or on velocity images for display after scan conversion processing. Similarly, the vessel width candidates acquired based on dispersion information are, for example, vessel width candidates acquired based on variance values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion processing, or on velocity images for display after scan conversion processing. In particular, the vessel width candidates acquired based on velocity values ​​or variance values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion are vessel width candidates acquired based on data before it is converted to brightness values ​​by scan conversion by the image generation circuit 35. Therefore, the acquisition function 384b can acquire more accurate vessel width candidates by acquiring vessel width candidates acquired based on velocity values ​​or variance values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion. Note that the vessel width candidates acquired based on velocity information or variance information may also be vessel width candidates acquired based on velocity information or variance information in the Doppler data before the MTI filter is applied. In the following explanation, we will describe the case in which the vessel width candidates acquired based on velocity information are vessel width candidates acquired based on velocity information or variance information including velocity values ​​or variance values ​​estimated at each of multiple sample points in the raw Doppler data before scan conversion.

[0131] Figure 27 is a flowchart illustrating the process of acquiring candidate vessel widths based on velocity information, which is performed in the main unit 30 of the device. In this process of acquiring candidate vessel widths based on velocity information, the velocity information is used to acquire the velocity value at the center position of the sample volume SV, to acquire the velocity value on the raster RA, to determine whether the velocity value is less than a predetermined value, to store max(X,Y) and min(X,Y), and to acquire candidate vessel widths based on the velocity information.

[0132] As shown in Figure 27, first, the acquisition function 384b in the processing circuit 38 of the main unit 30 acquires the velocity value at the center position of the sample volume SV (step S301). Specifically, the acquisition function 384b uses color Doppler mode to acquire the blood flow velocity value at the center position of the sample volume SV included in the sample gate SG set in the color Doppler image IM2.

[0133] Next, as shown in Figure 27, the acquisition function 384b determines whether the velocity value is above a threshold (step S303). Specifically, the acquisition function 384b determines whether the blood flow velocity value at the center of the sample volume SV acquired in step S301 is above a threshold. The threshold in step S303 is, for example, the threshold used when suppressing clutter signals in an MTI filter.

[0134] Then, in step S303, if the velocity value is not above the threshold, that is, if the velocity value is below the threshold (step S303: No), the acquisition function 384b determines whether a certain period of time has elapsed (step S305). Specifically, the acquisition function 384b determines whether a certain period of time has elapsed since the start of the process of acquiring candidate blood vessel widths based on velocity information. This certain period is a period set by the user, for example, 1 second for 60 heartbeats.

[0135] Then, in step S305, if a certain period of time has not elapsed (step S305: No), the process from steps S301 to S305 is repeated until the velocity value exceeds the threshold or a certain period of time has elapsed. In other words, if the velocity value is below the threshold, the system recognizes that the blood flow is pulsatile and waits for a phase in which a blood flow velocity value above the threshold occurs.

[0136] On the other hand, if a certain period of time has elapsed in step S305 (step S305: No), the acquisition function 384 stores the error values ​​in max(X, Y) and min(X, Y) (step S307).

[0137] On the other hand, in step S303, if the velocity value is above the threshold (step S303: Yes), the acquisition function 384b acquires the velocity value at the coordinate obtained by adding 1 to the y coordinate (step S309). Specifically, the acquisition function 384b acquires the blood flow velocity value at the position obtained by adding 1 to the y coordinate along the raster RA. More specifically, for example, in the example shown in Figure 20, in step S309, the acquisition function 384b acquires the velocity value at the coordinate of the center position (X) along the raster RA. C ,Y C The coordinate obtained by adding 1 to the y-coordinate of (X',Y C The blood flow velocity value is obtained at the position +1). Note that in step S309, the acquisition function 384b obtains the blood flow velocity value at the position of the y coordinate +1, but the value added to the y coordinate is not limited to 1. That is, the value added to the y coordinate is arbitrary, and may be between 0 and 1, or greater than 1.

[0138] Next, as shown in Figure 27, the acquisition function 384b determines whether the velocity value is below a threshold and stores the result (step S311). Specifically, the acquisition function 384b determines whether the blood flow velocity value acquired in step S309 is below a threshold, associates the blood flow velocity value with the coordinates of the location where it was acquired, and stores the determination result in the memory circuit 37.

[0139] Next, as shown in Figure 27, the acquisition function 384b acquires the y coordinate Y CIt is determined whether or not +n has been reached (step S313). Specifically, the acquisition function 384b determines whether the y coordinate at the time the velocity value was acquired in step S309 is Y C Determine whether or not +n has been reached. The value of n is, for example, if the value of n is set to 9, then Y C +9 indicates that the acquisition of blood flow velocity values ​​at a coordinate obtained by adding 1 to the y-coordinate is repeated 9 times. The accuracy of blood vessel detection increases as the value of n increases; in other words, the accuracy of blood vessel detection depends on the value of n. This value of n can be set arbitrarily by the user or a fixed value may be set. Note that in step S313, the acquisition function 384b is performed when the y-coordinate is Y C The function is designed to determine whether or not the value has reached +n, but it is not limited to this. For example, the acquisition function 384b may determine whether or not the y coordinate has reached a value arbitrarily set by the user, or it may determine whether or not the y coordinate has reached the lower end of the scan range in the ultrasound image IM.

[0140] Then, in step S313, the y coordinate is Y C If +n has not been reached (step S313: No), the acquisition function 384b returns to step S309 and performs the process of acquiring the velocity value (step S309), the process of determining whether the velocity value is less than the threshold and storing the result (step S311), and the y coordinate is Y C The process of determining whether or not +n has been reached (step S313) is repeated until the y coordinate is Y C Wait until +n is reached.

[0141] On the other hand, in step S313, the y coordinate is Y CIf +n is reached (step S313: Yes), the acquisition function 384b determines whether the speed value is less than the threshold (step S315). Specifically, the acquisition function 384b determines whether the speed value is less than the threshold based on the determination result stored in step S311. Then, in step S315, if the speed value is not less than the threshold (step S315: No), the acquisition function 384b stores the error value in max(X, Y) (step S317).

[0142] On the other hand, in step S315, if the velocity value is less than the threshold (step S315: Yes), the acquisition function 384b stores max(X, Y) (step S319). Specifically, the acquisition function 384b stores as max(X, Y) the coordinates obtained by moving back a predetermined amount in the negative direction of the y axis from the coordinate with the smallest y-coordinate value of the position where the judgment result in which the velocity value was less than the threshold was first obtained, among the judgment results in which the velocity value was less than the threshold stored in step S311. More specifically, the acquisition function 384b stores as max(X, Y) the coordinates obtained by moving back 1 unit in the negative direction of the y axis from the coordinate with the smallest y-coordinate value of the position where the blood flow velocity value corresponding to the judgment result in which the velocity value was less than the threshold was obtained, along the raster RA. For example, in the example shown in Figure 20, the acquisition function 384b determines that the smallest y-coordinate value of the position where the blood flow velocity value corresponding to the judgment result where the velocity value is less than the threshold was obtained was (X'',Y+1). Therefore, it stores (X',Y), obtained by moving the y-coordinate back by 1 from (X'',Y+1) along the raster RA, as max(X,Y).

[0143] After processing in steps S317 and S319, as shown in Figure 27, the acquisition function 384b acquires the velocity value at a coordinate obtained by subtracting 1 from the y-coordinate (step S321). Specifically, the acquisition function 384b acquires the blood flow velocity value at a position obtained by subtracting 1 from the y-coordinate of the center position of the sample volume SV along the raster RA. More specifically, for example, in step S321, the acquisition function 384a acquires the velocity value at a position obtained by subtracting 1 from the y-coordinate of the center position of the sample volume SV along the raster RA (X C ,Y C The coordinate obtained by subtracting 1 from the y-coordinate of (X',Y C The power value of the blood flow at position -1) is obtained. Note that in step S309, the acquisition function 384b obtains the blood flow velocity value at the position of the y coordinate minus 1, but the value subtracted from the y coordinate is not limited to 1. That is, the value subtracted from the y coordinate is arbitrary and may be between 0 and 1, or greater than 1. Note that the processing in step S323 after step S321 is equivalent to the processing in step S311, so the explanation is omitted.

[0144] Next, as shown in Figure 27, the acquisition function 384b acquires the y coordinate Y C It is determined whether -n has been reached (step S325). Specifically, the acquisition function 384b determines whether the y coordinate at the time the velocity value was acquired in step S321 is Y C Determine whether -n has been reached. The value of n is, for example, if the value of n is set to 9, then Y C -9 indicates that the acquisition of blood flow velocity values ​​at a coordinate obtained by subtracting 1 from the y-coordinate is repeated 9 times. The accuracy of blood vessel detection increases as the value of n increases; in other words, the accuracy of blood vessel detection depends on the value of n. This value of n may be set arbitrarily by the user or may be set to a fixed value. Note that in step S321, the acquisition function 384b is performed when the y-coordinate is Y CThe function determines whether or not -n has been reached, but it is not limited to this. For example, the acquisition function 384b may determine whether or not the y coordinate has reached a value arbitrarily set by the user, or it may determine whether or not the y coordinate has reached the upper end of the scan range in the ultrasound image IM.

[0145] Then, in step S325, the y coordinate is Y C If -n has not been reached (step S325: No), the acquisition function 384b returns to step S321 and performs the process of acquiring the velocity value (step S321), the process of determining whether the velocity value is less than the threshold and storing the result (step S323), and the y coordinate is Y C The process of determining whether or not -n has been reached (step S325) is repeated until the y coordinate is Y C Wait until -n is reached.

[0146] On the other hand, in step S325, the y coordinate is Y C If -n is reached (step S325: Yes), the acquisition function 384b determines whether the speed value is less than the threshold (step S327). Specifically, the acquisition function 384b determines whether the speed value is less than the threshold based on the determination result stored in step S323. Then, in step S327, if the speed value is not less than the threshold (step S327: No), the acquisition function 384b in the processing circuit 38 of the device body 30 stores an error value in min(X, Y) (step S329).

[0147] On the other hand, in step S327, if the velocity value is less than the threshold (step S327: Yes), the acquisition function 384b in the processing circuit 38 of the device body 30 stores min(X, Y) (step S331). Specifically, the acquisition function 384b stores as min(X, Y) the coordinates obtained by moving back a predetermined amount in the positive direction of the y axis from the coordinate with the largest y-coordinate value of the position where the judgment result in which the velocity value was less than the threshold was first obtained, among the judgment results in which the velocity value was less than the threshold stored in step S323. More specifically, the acquisition function 384b stores as min(X, Y) the coordinates obtained by moving back 1 unit in the positive direction of the y axis from the coordinate with the largest y-coordinate value of the position where the blood flow velocity value corresponding to the judgment result in which the velocity value was less than the threshold was obtained, along the raster RA.

[0148] Next, as shown in Figure 27, the acquisition function 384b acquires a candidate vessel width based on velocity information (step S333). Specifically, the acquisition function 384b acquires a candidate vessel width based on velocity information based on max(X, Y) and min(X, Y). More specifically, if no error values ​​are stored in either max(X, Y) or min(X, Y), the acquisition function 384b acquires, for example, the absolute value of the difference between the y coordinates of max(X, Y) and min(X, Y) as a candidate vessel width. Also, if an error value is stored in at least one of max(X, Y) or min(X, Y), the acquisition function 384b acquires, for example, the error value as a candidate vessel width.

[0149] Then, in step S333, the process of obtaining candidate vessel widths based on velocity information is terminated by obtaining candidate vessel widths based on velocity information.

[0150] Figure 28 is a flowchart illustrating the process of acquiring candidate vessel widths based on dispersion information, which is performed in the main unit 30 of the device. In this process of acquiring candidate vessel widths based on dispersion information, the dispersion information is used to obtain the dispersion value of the center position of the sample volume, obtain the dispersion on the raster RA, determine whether the dispersion is above a threshold, store max(X,Y) and min(X,Y), and acquire candidate vessel widths based on the dispersion information.

[0151] As shown in Figure 28, first, the acquisition function 384b in the processing circuit 38 of the main unit 30 acquires the dispersion value of the center position of the sample volume SV (step S401). Specifically, the acquisition function 384b uses color Doppler mode to acquire the dispersion value of blood flow at the center position of the sample volume SV acquired by the sample gate setting function 383. More specifically, in the example shown in Figure 20, the acquisition function 384b acquires the coordinates (X) of the center position of the sample volume SV. C ,Y C Get the variance value of ).

[0152] Next, as shown in Figure 28, the acquisition function 384b determines whether the variance value is clearly high or not (step S403). Specifically, the acquisition function 384b determines whether the variance value is clearly high or not by determining whether the variance value of blood flow at the center position of the sample volume SV acquired in step S301 is above a threshold. Then, in step S403, if the variance value is clearly high (step S403: Yes), the acquisition function 384b stores the error value in max(X, Y) and min(X, Y) (step S405).

[0153] On the other hand, in step S403, if the variance is not clearly high (step S403: No), the acquisition function 384b acquires the variance at a coordinate obtained by adding 1 to the y-coordinate (step S407). Specifically, the acquisition function 384b acquires the blood flow variance at a position obtained by adding 1 to the y-coordinate along the raster RA. More specifically, for example, in the example shown in Figure 20, in step S407, the acquisition function 384b acquires the variance at a coordinate obtained by adding 1 to the y-coordinate (X', Y) along the raster RA from the center position of the sample volume SV. C The blood flow velocity value is obtained at the position +1). Note that in step S407, the acquisition function 384b obtains the blood flow dispersion value at the position of the y coordinate +1, but the value added to the y coordinate is not limited to 1. That is, the value added to the y coordinate is arbitrary, and may be between 0 and 1, or greater than 1.

[0154] Next, as shown in Figure 27, the acquisition function 384b determines whether the change in the variance value is greater than or equal to a set value and stores the result (step S409). Specifically, the acquisition function 384b determines whether the change in the blood flow variance value is greater than or equal to a set value, and stores the variance value, the coordinates of the location where the blood flow variance value was acquired, and the determination result in the memory circuit 37. More specifically, the acquisition function 384b determines whether the change in the variance value is greater than or equal to a set value by comparing the variance value acquired in step S407 with the variance value acquired immediately before that variance value and determining whether the variance has increased significantly. For example, the acquisition function 384b, (X',Y C Variance s at position +1) 2 (X',Y C (X',Y +1) and (X',Y C (X) one step before +1 C ,Y C ) Variance value s at position ) 2 (X C ,Y C When comparing with ) to determine whether the variance has significantly increased, the change in the variance value is greater than or equal to the set value, based on whether the following equation (3) is satisfied.

number

[0155] Next, as shown in Figure 27, the acquisition function 384b acquires the y coordinate Y C It is determined whether or not +n has been reached (step S411). Specifically, the acquisition function 384b determines whether the y coordinate when the variance value was acquired in step S407 is Y C Determine whether or not +n has been reached. The value of n is, for example, if the value of n is set to 9, then Y C +9 indicates that the acquisition of blood flow detection values ​​at a coordinate obtained by adding 1 to the y-coordinate is repeated 9 times. The accuracy of blood vessel detection increases as the value of n increases; in other words, the accuracy of blood vessel detection depends on the value of n. This value of n can be set arbitrarily by the user or a fixed value may be set. Note that in step S411, the acquisition function 384b is performed when the y-coordinate is Y C The function is designed to determine whether or not the value has reached +n, but it is not limited to this. For example, the acquisition function 384b may determine whether or not the y coordinate has reached a value arbitrarily set by the user, or it may determine whether or not the y coordinate has reached the lower end of the scan range in the ultrasound image IM.

[0156] Then, in step S411, the y coordinate is Y C If +n has not been reached (step S411: No), the acquisition function 384b returns to step S407 and performs the process of acquiring the variance value (step S407), and the process of determining whether the change in the variance value is greater than or equal to the set value and storing the result (step S409), and the y coordinate is Y C The process of determining whether or not +n has been reached (step S411) is repeated until the y coordinate is Y C Wait until +n is reached.

[0157] On the other hand, in step S411, the y coordinate is Y CIf +n is reached (Step S411: Yes), the acquisition function 384b determines whether the change in the variance value is greater than or equal to a set value (Step S413). Specifically, the acquisition function 384b determines whether the change in the variance value is greater than or equal to a set value based on the determination result stored in Step S311. Then, in Step S413, if the change in the variance value is not greater than or equal to a set value (Step S413: No), the acquisition function 384b stores the error value in max(X, Y) (Step S415).

[0158] On the other hand, in step S413, if the change in the variance value is greater than or equal to the set value (step S413: Yes), the acquisition function 384b stores max(X, Y) (step S417). Specifically, the acquisition function 384b stores as max(X, Y) the coordinates of the position where the judgment result first exceeded the set value among the judgment results stored in step S409 where the change in the variance value was greater than or equal to the set value, that is, the coordinates obtained by moving back a predetermined amount in the negative direction of the y axis from the coordinate with the smallest y coordinate value of the position where the blood flow variance value corresponding to the judgment result that exceeded the set value was acquired. More specifically, the acquisition function 384b stores as max(X, Y) the coordinates obtained by moving back 1 unit in the negative direction of the y axis along the raster RA from the coordinate with the smallest y coordinate value of the position where the blood flow variance value corresponding to the judgment result where the change in the variance value was greater than or equal to the set value was acquired. For example, in the example shown in Figure 20, the acquisition function 384b determines that the smallest y-coordinate value of the location where the blood flow variance value corresponding to the judgment result where the change in variance value exceeds the set value was (X'',Y+1). Therefore, it stores (X',Y), obtained by moving the y-coordinate back by 1 from (X'',Y+1) along the raster RA, as max(X,Y).

[0159] After the processing in steps S415 and S417, as shown in Figure 28, the acquisition function 384b acquires the variance value at a coordinate obtained by subtracting 1 from the y-coordinate (step S419). Specifically, the acquisition function 384b acquires the variance value of blood flow at a position obtained by subtracting 1 from the y-coordinate of the center position of the sample volume SV along the raster RA. In step S309, the acquisition function 384b acquires the blood flow velocity value at a position obtained by subtracting 1 from the y-coordinate, but the value subtracted from the y-coordinate is not limited to 1. That is, the value subtracted from the y-coordinate is arbitrary and may be between 0 and 1, or greater than 1. Note that the processing in step S421 after step S419 is equivalent to the processing in step S409, so the explanation is omitted.

[0160] Next, as shown in Figure 28, the acquisition function 384b acquires the y coordinate Y C It is determined whether -n has been reached (step S423). Specifically, the acquisition function 384b determines whether the y coordinate when the variance value was acquired in step S419 is Y C Determine whether -n has been reached. The value of n is, for example, if the value of n is set to 9, then Y C -9 indicates that the acquisition of the blood flow dispersion value at a coordinate obtained by subtracting 1 from the y-coordinate is repeated 9 times. The accuracy of blood vessel detection increases as the value of n increases; in other words, the accuracy of blood vessel detection depends on the value of n. This value of n may be set arbitrarily by the user or may be set to a fixed value. Note that in step S321, the acquisition function 384b is performed when the y-coordinate is Y C The function determines whether or not -n has been reached, but it is not limited to this. For example, the acquisition function 384b may determine whether or not the y coordinate has reached a value arbitrarily set by the user, or it may determine whether or not the y coordinate has reached the upper end of the scan range in the ultrasound image IM.

[0161] Then, in step S423, the y coordinate is Y CIf -n has not been reached (step S423: No), the acquisition function 384b returns to step S407 and performs the process of acquiring the variance value (step S419), and the process of determining whether the change in the variance value is greater than or equal to the set value and storing the result (step S421), and the y coordinate is Y C The process of determining whether or not -n has been reached (step S423) is repeated until the y coordinate is Y C Wait until -n is reached.

[0162] On the other hand, in step S423, the y coordinate is Y C If -n is reached (step S423: Yes), the acquisition function 384b determines whether the change in the variance value is greater than or equal to a set value (step S425). Specifically, the acquisition function 384b determines whether the change in the variance value is greater than or equal to a set value based on the determination result stored in step S311. Then, in step S425, if the change in the variance value is not greater than or equal to a set value (step S425: No), the acquisition function 384b stores the error value in min(X, Y) (step S427).

[0163] On the other hand, in step S413, if the change in the variance value is greater than or equal to the set value (step S425: Yes), the acquisition function 384b stores min(X, Y) (step S429). Specifically, the acquisition function 384b stores as min(X, Y) the coordinates of the position where the judgment result first exceeded the set value among the judgment results where the change in the variance value stored in step S323 was greater than or equal to the set value, that is, the coordinates obtained by moving back a predetermined amount in the positive direction of the y axis from the coordinate with the largest y coordinate value of the position where the blood flow variance value corresponding to the judgment result where the change in the variance value was greater than or equal to the set value was acquired. More specifically, the acquisition function 384b stores as min(X, Y) the coordinates obtained by moving back 1 unit in the positive direction of the y axis from the coordinate with the largest y coordinate value of the position where the blood flow variance value corresponding to the judgment result where the change in the variance value was greater than or equal to the set value was acquired along the raster RA.

[0164] Next, as shown in Figure 28, the acquisition function 384b acquires a candidate vessel width based on the distributed information (step S431). Specifically, the acquisition function 384b acquires a candidate vessel width based on the distributed information based on max(X, Y) and min(X, Y). More specifically, if no error values ​​are stored in either max(X, Y) or min(X, Y), the acquisition function 384b acquires, for example, the absolute value of the difference between the respective y coordinates of max(X, Y) and min(X, Y) as the candidate vessel width. Also, if an error value is stored in at least one of max(X, Y) or min(X, Y), the acquisition function 384b acquires, for example, the error value as the candidate vessel width.

[0165] Then, in step S431, the process of obtaining candidate vessel widths based on distributed information is terminated by obtaining candidate vessel widths based on distributed information.

[0166] Figure 29 is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic device 1 according to the third embodiment. In the sample volume width adjustment process shown in Figure 29, if the vessel width candidate based on power information is not likely, a vessel width candidate based on velocity information is obtained, or the vessel width candidate based on examination information is compared with the vessel width candidate based on velocity information. If the vessel width candidate based on velocity information is not likely, a vessel width candidate based on dispersion information is obtained, or the vessel width candidate based on examination information is compared with the vessel width candidate based on dispersion information. If the vessel width candidate based on dispersion information is not likely, the vessel width candidate from the examination information is applied to the vessel wall position of the more likely B-mode information to adjust the width of the sample volume SV. For example, the sample volume width adjustment process is performed when the PWD mode is activated. Note that the processes in steps S11 to S17 and step S21 shown in Figure 29 are equivalent to those in Figure 13, so their explanation is omitted. Also, the processes in steps S19a, S23a, and S31 to S35 shown in Figure 29 are equivalent to those in Figure 21, so their explanation is omitted.

[0167] Then, in step S35, if the vessel width candidate is not likely (step S35: No), the acquisition function 384b acquires a vessel width candidate based on velocity information as a fourth vessel width candidate (step S41). Specifically, the acquisition function 384b acquires a vessel width candidate based on velocity information as a fourth vessel width candidate by executing the vessel width candidate acquisition process based on velocity information described above.

[0168] Next, as shown in Figure 29, the adjustment function 385 in the processing circuit 38 of the main body of the device 30 compares the first vessel width candidate with the fourth vessel width candidate (step S43). Specifically, the adjustment function 385 compares multiple vessel width candidates based on multiple vessel width candidates. More specifically, the adjustment function 385 compares the vessel width candidate based on the examination information acquired as the first vessel width candidate in step S17 with the vessel width candidate based on the velocity information acquired as the fourth vessel width candidate in step S41. More specifically, for example, the adjustment function 385 compares whether the vessel width candidate based on the velocity information is within the range of the vessel width candidate based on the examination information.

[0169] Next, as shown in Figure 29, the adjustment function 385 determines whether the vessel width candidate is likely or not (step S45). Specifically, the adjustment function 385 determines whether the vessel width candidate is likely or not based on the comparison result, which is the result of comparing multiple vessel width candidates. More specifically, the adjustment function 385 determines whether the vessel width candidate based on velocity information is likely or not based on the result of comparing the vessel width candidate based on the examination information acquired as the first vessel width candidate in step S43 with the vessel width candidate based on velocity information acquired as the fourth vessel width candidate. More specifically, the adjustment function 385 determines that the vessel width candidate is unlikely if, for example, at least one of the first vessel width candidate and the fourth vessel width candidate is an error value. Also, the adjustment function 385 determines that the vessel width candidate is unlikely if, for example, the vessel width candidate based on velocity information is not within the range of the vessel width candidate based on examination information. On the other hand, the adjustment function 385 determines that the vessel width candidate is likely if, for example, the vessel width candidate based on velocity information is within the range of the vessel width candidate based on examination information.

[0170] Then, in step S45, if the vessel width candidate is not likely (step S45: No), the acquisition function 384b acquires a vessel width candidate based on distributed information as a fifth vessel width candidate (step S47). Specifically, the acquisition function 384b acquires a vessel width candidate based on distributed information as a fifth vessel width candidate by executing the vessel width candidate acquisition process based on distributed information described above.

[0171] Next, as shown in Figure 29, the adjustment function 385 compares the first vessel width candidate with the fifth vessel width candidate (step S49). Specifically, the adjustment function 385 compares multiple vessel width candidates based on multiple vessel width candidates. More specifically, the adjustment function 385 compares the vessel width candidate based on the examination information acquired as the first vessel width candidate in step S17 with the vessel width candidate based on the distributed information acquired as the fifth vessel width candidate in step S47. For example, the adjustment function 385 compares whether the vessel width candidate based on the distributed information falls within the range of the vessel width candidate based on the examination information.

[0172] Next, as shown in Figure 29, the adjustment function 385 determines whether the vessel width candidate is likely or not (step S51). Specifically, the adjustment function 385 determines whether the vessel width candidate is likely or not based on the comparison result, which is the result of comparing multiple vessel width candidates. More specifically, the adjustment function 385 determines whether the vessel width candidate based on distributed information is likely or not based on the result of comparing the vessel width candidate based on the examination information obtained as the first vessel width candidate in step S49 with the vessel width candidate based on distributed information obtained as the fifth vessel width candidate. More specifically, the adjustment function 385 determines that the vessel width candidate is unlikely if, for example, at least one of the first vessel width candidate and the fifth vessel width candidate is an error value. Also, the adjustment function 385 determines that the vessel width candidate is unlikely if, for example, the vessel width candidate based on distributed information is not within the range of the vessel width candidate based on the examination information. On the other hand, the adjustment function 385 determines that the vessel width candidate is likely if, for example, the vessel width candidate based on distributed information is within the range of the vessel width candidate based on the examination information.

[0173] Then, in steps S23a, S35, S45, and S51, if the candidate vessel width is deemed likely (steps S23a, S35, S45, and S51: Yes), the width of the sample volume SV is adjusted (step S25). The specific processing in step S25 is equivalent to that shown in Figure 13, so its explanation is omitted.

[0174] On the other hand, in step S51, if the vessel width candidate is not likely (step S51: No), it is determined whether max(X, Y) and min(X,Y) in the vessel width candidate based on B-mode information are errors (step S53). Specifically, the acquisition function 384b determines whether error values ​​are stored in max(X, Y) and min(X,Y) in the vessel width candidate based on B-mode information acquired in step S19a.

[0175] Then, in step S53, if max(X, Y) and min(X, Y) in the vessel width candidate based on B-mode information are not errors (step S53: No), the acquisition function 384b adjusts the width of the sample volume SV based on either max(X, Y) or min(X, Y) in the vessel width candidate based on B-mode information and the vessel width candidate based on the examination information (step S55). Specifically, the acquisition function 384b adjusts the width of the sample volume SV based on the vessel width candidate based on the examination information acquired in step S17 and either max(X, Y) or min(X, Y) stored by executing the vessel width candidate acquisition process based on B-mode information in step S19.

[0176] The method for adjusting the width of the sample volume SV in step S55 will be explained in detail using Figures 30 and 31. Figure 30 is a diagram showing an example of an ultrasound image IM with a sample gate SG set. Figure 31 is a diagram showing an example of the distribution of brightness values ​​on the raster RA acquired in the ultrasound image IM shown in Figure 30. As shown in Figure 30, a sample gate SG is set in the B-mode image IM1, which is an ultrasound image IM. The sample volume SV included in this sample gate SG is set on the blood vessel BV depicted in the B-mode image IM1. In addition, a color Doppler image IM2 is superimposed on the B-mode image IM1.

[0177] As shown in Figure 31, the acquisition function 384b acquires a graph G8 with the x-axis representing Depth and the y-axis representing Brightness, representing the distribution of Brightness values ​​on the raster RA at the sample gate SG of the ultrasound image IM shown in Figure 30. The acquisition function 384b also stores the coordinates at point P1 as max(X, Y) and the coordinates at point P2 as min(X, Y) by performing a process to acquire candidate vessel widths based on B-mode information. The acquisition function 384b then assumes that the value with the larger difference between the Brightness value and the threshold in the stored max(X, Y) and min(X, Y) values ​​more accurately captures the vessel wall. For example, in the example shown in Figure 31, the difference between the Brightness value and the threshold TH4 is large at point P1, so the max(X, Y) stored as the coordinates at point P1 is assumed to more accurately capture the vessel wall.

[0178] Figure 32 shows an example of an ultrasound image IM with a sample gate SG, including the sample volume SV, set before and after adjustment of the width of the sample volume SV. As shown in Figure 32(a), before adjustment by the adjustment function 385, the sample volume SV is not of an appropriate width for the vessel width. On the other hand, as shown in Figure 32(b), after adjustment by the adjustment function 385, the sample volume SV' is of an appropriate width for the vessel width. Specifically, as shown in Figure 32(b), the adjustment function 385 adjusts the width of the sample volume SV by aligning the lower end SV1 of the sample gate to the max(X, Y) position and opening the upper end SV2 of the sample volume SV by the value W of the vessel width candidate based on the search information relative to the lower end SV1 of the sample volume SV.

[0179] Then, in step S53, if the vessel width candidate is not likely (step S23: No), or if max(X, Y) and min(X, Y) in the vessel width candidate based on B-mode information are errors (step S53: Yes), the sample volume width adjustment process is terminated after the processing in step S25 or after the processing in step S55.

[0180] As described above, in the ultrasound diagnostic device 1, even if none of the vessel width candidates based on other information are likely, the sample volume SV included in the sample gate SG is adjusted based on either max(X, Y) or min(X, Y) of the vessel width candidate based on B-mode information and the vessel width candidate based on the examination information. Therefore, it is no longer necessary to manually adjust the sample volume SV for each vessel, and the sample volume SV can be appropriately adjusted according to the vessel width, thereby improving the examination efficiency and accuracy in PWD mode.

[0181] In step S53 and step S55 of the sample volume width adjustment process performed in the ultrasound diagnostic apparatus 1 according to the third embodiment described above, the acquisition function 384b determines whether max(X, Y) and min(X, Y) in the vessel width candidate based on B-mode information are errors, and if they are not errors, it adjusts the width of the sample volume SV based on either max(X, Y) or min(X, Y) in the vessel width candidate based on B-mode information and the vessel width candidate based on the examination information. However, the vessel width candidate for which the acquisition function 384b determines whether max(X, Y) and min(X, Y) are errors is not limited to B-mode information. In other words, the vessel width candidate for which the acquisition function 384b determines whether max(X, Y) and min(X,Y) are errors is arbitrary. The function determines whether max(X, Y) and min(X,Y) in any of the vessel width candidates based on power information, vessel width candidates based on velocity information, and vessel width candidates based on dispersion information are errors. If they are not errors, the width of the sample volume SV may be adjusted based on either max(X, Y) and min(X,Y) in any of the vessel width candidates based on power information, vessel width candidates based on velocity information, and vessel width candidates based on dispersion information, and the vessel width candidate based on examination information.

[0182] [Fourth Embodiment] The first to third embodiments described above describe cases where a candidate vessel width based on examination information is available, but are not limited to this. The fourth embodiment describes an ultrasound diagnostic device that determines whether a vessel width based on examination information is available, and adjusts the sample volume SV from a candidate vessel width based on information other than examination information if a candidate vessel width based on examination information is unavailable. In the following, a modified example applied to the first embodiment described above will be described as the fourth embodiment, but it is also applicable to the second and third embodiments. Note that the configuration of the ultrasound diagnostic device 1 is the same as that in Figure 1, so its description will be omitted.

[0183] Figure 33 is a flowchart illustrating the sample volume width adjustment process performed in the ultrasound diagnostic apparatus 1 according to the third embodiment, and corresponds to Figure 13. This sample volume width adjustment process involves setting the sample gate SG, obtaining the center position of the sample volume SV, obtaining a vessel width candidate based on examination information, obtaining a vessel width candidate based on B-mode information, determining whether the vessel width candidate based on examination information and the vessel width candidate based on B-mode information are usable, obtaining a vessel width candidate based on power information, obtaining a vessel width candidate based on velocity information, and adjusting the width of the sample volume SV. For example, the sample volume width adjustment process is performed when PWD mode is activated.

[0184] As shown in Figure 33, first, the sample gate setting function 383 in the processing circuit 38 of the main unit 30 sets the sample gate (step S11). The specific processing is equivalent to step S11 in Figure 13, so the explanation is omitted. Figure 34 is a diagram showing an example of an ultrasound image IM with the sample gate SG set, and corresponds to Figure 14. As shown in Figure 34, the color Doppler image IM2 superimposed on the B-mode image IM1, which is an ultrasound image IM, has the sample gate SG set. Note that the processing from steps S13 to S19 after step S11 shown in Figure 33 is equivalent to that in Figure 13, so the explanation is omitted.

[0185] Next, as shown in Figure 33, the acquisition function 384 determines whether the vessel width candidate based on the examination information is usable (step S61). Specifically, the acquisition function 384 determines whether the vessel width candidate based on the examination information acquired in step S17 is usable by determining whether or not it contains an error value.

[0186] Then, in step S61, if the vessel width candidates based on the examination information are available (step S61: Yes), the acquisition function 384 determines whether or not the vessel width candidates based on the B-mode information are available (step S63). Specifically, the acquisition function 384 determines whether or not the B-mode information is available by determining whether or not the vessel width candidates based on the B-mode information contain error values.

[0187] On the other hand, if, in step S61, the vessel width candidates based on the examination information are unavailable (step S61: No), the acquisition function 384 determines whether or not the vessel width candidates based on the B-mode information are available (step S65). Specifically, the acquisition function 384 determines whether or not the B-mode information is available by determining whether or not the vessel width candidates based on the B-mode information contain error values.

[0188] Then, in steps S63 and S65, if the vessel width candidate based on B-mode information is not available (steps S63 and S65: No), the acquisition function 384 acquires a vessel width candidate based on power information as a third vessel width candidate (step S67). Specifically, the acquisition function 384 acquires a vessel width candidate based on power information as a third vessel width candidate by executing a process to acquire a vessel width candidate based on power information.

[0189] Next, the acquisition function 384 acquires a fourth vessel width candidate based on velocity information (step S69). Specifically, the acquisition function 384 acquires a fourth vessel width candidate based on velocity information by executing a process to acquire a vessel width candidate based on velocity information.

[0190] The power information and velocity information obtained in this embodiment will be explained using Figures 35, 36, 37, and 38. Figure 35 is a diagram showing an example of the distribution of power values ​​in the ultrasound image IM shown in Figure 34. Figure 36 is a diagram showing an example of the distribution of velocity values ​​in the ultrasound image IM shown in Figure 34. Figure 37 is a diagram showing an example of the distribution of power values ​​on the raster RA shown in Figure 35 and the distribution of velocity values ​​on the raster RA shown in Figure 36. Figure 38 is a diagram showing the normalized distribution of power values ​​and velocity values ​​shown in Figure 37.

[0191] The distribution of power values ​​on the raster at the sample gate SG, which is set to the power value distribution shown in Figure 35, is shown in graph G9 in Figure 37. Similarly, the distribution of velocity values ​​on the raster at the sample gate SG, which is set to the velocity value distribution shown in Figure 36, is shown in graph G10 in Figure 37. Graphs of these graphs G9 and G10, respectively, after normalization, are shown in Figure 38. The acquisition function 384 then performs a process to acquire vessel width candidates based on power information and a process to acquire vessel width candidates based on velocity information, thereby acquiring vessel width candidates based on power information in step S67 and vessel width candidates based on velocity information in step S69. Specifically, the acquisition function 384 acquires vessel width candidates based on power information and vessel width candidates based on velocity information by taking points where the peak value is below a certain threshold, starting from the peak value closest to the center position of the sample volume SV, based on the graph shown in Figure 38.

[0192] Next, as shown in Figure 33, the adjustment function 385 determines whether the ratio of the third and fourth vessel width candidates is within a threshold (step S71). Specifically, the adjustment function 385 determines whether the ratio of the vessel width candidate based on power information to the vessel width candidate based on velocity information is within a threshold, based on the vessel width candidate based on power information acquired as the third vessel width candidate in step S67 and the vessel width candidate based on velocity information acquired as the fourth vessel width candidate in step S69. More specifically, the adjustment function 385 determines whether the value obtained by dividing the larger of the two vessel width candidates (the one based on power information and the one based on velocity information) by the smaller of the two vessel width candidates (the one based on power information and the one based on velocity information) is within a threshold.

[0193] Then, in step S71, if the ratio of the third and fourth vessel width candidates is within the threshold (step S71: Yes), the adjustment function 385 adjusts the width of the sample volume SV based on the smaller of the third and fourth vessel width candidates (step S73). Specifically, the adjustment function 385 adjusts the width of the sample volume SV based on the max(X, Y) and min(X, Y) of the smaller of the third and fourth vessel width candidates.

[0194] On the other hand, if, in step S71, the ratio of the third and fourth vessel width candidates is not within the threshold (step S71: Yes), the adjustment function 385 adjusts the width of the sample volume SV based on the larger of the third and fourth vessel width candidates (step S75). Specifically, the adjustment function 385 adjusts the width of the sample volume SV based on the max(X, Y) and min(X, Y) of the larger of the third and fourth vessel width candidates.

[0195] On the other hand, in step S65, if a vessel width candidate based on B-mode information is available (step S65: Yes), the acquisition function 384 acquires a vessel width candidate based on power information as a third vessel width candidate (step S77). Specifically, the acquisition function 384 acquires a vessel width candidate based on power information as a third vessel width candidate by executing a process to acquire a vessel width candidate based on power information.

[0196] Next, as shown in Figure 33, the adjustment function 385 compares the second and third vessel width candidates (step S77). Specifically, the adjustment function 385 compares the vessel width candidate based on the B-mode information acquired in step S19 with the vessel width candidate based on the power information acquired in step S77.

[0197] More specifically, adjustment function 385 compares the max(X, Y) of the vessel width candidate based on B-mode information with the max(X, Y) of the vessel width candidate based on power information, and if the max(X, Y) of the vessel width candidate based on B-mode information is greater than the max(X, Y) of the vessel width candidate based on power information, the coordinates (X) of the center position of the sample volume SV C ,Y C If the vessel width candidate based on B-mode information is far from the center position of the sample volume SV and is larger than the vessel width candidate based on power information, the max(X, Y) of the vessel width candidate based on power information is used. On the other hand, adjustment function 385 uses the coordinates (X, Y) of the center position of the sample volume SV if the max(X, Y) of the vessel width candidate based on B-mode information is larger than the max(X, Y) of the vessel width candidate based on power information. C ,Y C Except when the candidate vessel width based on B-mode information is far from the center position of sample volume SV and the candidate vessel width based on power information is greater than the candidate vessel width based on power information, for example, max(X, Y) in the candidate vessel width based on B-mode information is greater than max(X, Y) in the candidate vessel width based on power information. C ,Y CIn cases where the distance is closer than ), the max(X, Y) of the candidate vessel width based on B-mode information is used. Furthermore, adjustment function 385 derives min(X, Y) in the same way as max(X, Y).

[0198] Next, the adjustment function 385 adjusts the width of the sample volume SV based on the comparison results of the second and third vessel width candidates (step S81). Specifically, the adjustment function 385 adjusts the width of the sample volume SV based on max(X, Y) and min(X, Y) derived as the comparison results in step S79.

[0199] As described above, in the ultrasound diagnostic device 1 according to the fourth embodiment, even when a candidate vessel width based on examination information cannot be used, multiple candidate vessel widths based on information other than examination information are acquired, and the width of the sample volume SV is adjusted based on the multiple candidate vessel widths. Therefore, it is no longer necessary to manually adjust the sample volume SV for each vessel, and the sample volume SV can be appropriately adjusted according to the vessel width, thereby improving the examination efficiency and accuracy in PWD mode.

[0200] [Variation 1] In the ultrasound diagnostic apparatus 1 according to the first to fourth embodiments described above, the adjustment function 385 may adjust the sample volume SV according to the ratio of the width of the sample volume SV to the blood vessel width, which is set in advance by the formulas (1) and (2) described above. Specifically, the adjustment function 385 may adjust the width of the sample volume SV using the following formulas (4) and (5), which take into account the ratio of the width of the sample volume SV to the blood vessel width (user-set ratio), which is set in advance by the user, in addition to the formulas (1) and (2) described above.

number

number

[0201] Thus, by adjusting the width of the sample volume SV using the following equations (4) and (5), which take into account the ratio of the width of the sample volume SV to the blood vessel width set by the user, the likelihood of positioning the upper end SV2 and lower end SV1 of the sample volume SV within the width of the blood vessel BV in the ultrasound image IM increases, thereby reducing the possibility of folding occurring due to the edge of the blood vessel BV being included within the width of the sample volume SV.

[0202] [Other variations] In the ultrasound diagnostic apparatus 1 according to the first embodiment described above, the acquisition function 384 acquires a candidate for the second vessel width based on B-mode information. However, the candidate for the second vessel width acquired by the acquisition function 384 is not limited to this. That is, the candidate for the second vessel width acquired by the acquisition function 384 is arbitrary. For example, the acquisition function 384 may acquire a candidate for the second vessel width based on power information, a candidate for the second vessel width based on velocity information, or a candidate for the second vessel width based on dispersion information.

[0203] Furthermore, in the ultrasound diagnostic apparatus 1 according to the first embodiment described above, the acquisition function 384 acquires a vessel width candidate based on examination information as the first vessel width candidate and a vessel width candidate based on B-mode information as the second vessel width candidate. However, the combination of the first vessel width candidate and the second vessel width candidate acquired by the acquisition function 384 is not limited to this. That is, the combination of the first vessel width candidate and the second vessel width candidate acquired by the acquisition function 384 is arbitrary, and the acquisition function 384 may acquire one of the following as the first vessel width candidate: a vessel width candidate based on examination information, a vessel width candidate based on B-mode information, a vessel width candidate based on power information, a vessel width candidate based on velocity information, and a vessel width candidate based on dispersion information, and acquire a vessel width candidate different from the first vessel width candidate as the second vessel width candidate. Note that if the acquisition function 384 does not acquire a vessel width candidate based on examination information as the first vessel width candidate and the second vessel width candidate, the processing in steps S21 and S23 of the sample volume width adjustment process may be omitted. In this case, in step S25, the adjustment function 385 may adjust the width of the sample volume SV based on the first and second vessel width candidates obtained in steps S17 and S19.

[0204] Furthermore, in the ultrasound diagnostic apparatus 1 according to the first embodiment described above, the acquisition function 384 is configured to acquire two vessel width candidates, but it is not limited to this. That is, the acquisition function 384 may acquire three or more vessel width candidates. In this case, the adjustment function 385 may adjust the region included in the sample gate SG based on the three or more vessel width candidates.

[0205] Furthermore, in the ultrasound diagnostic apparatus 1 according to the second embodiment described above, the acquisition function 384a acquired a third vessel width candidate based on power information. However, the third vessel width candidate acquired by the acquisition function 384a is not limited to this. That is, the third vessel width candidate acquired by the acquisition function 384a is arbitrary. For example, the acquisition function 384a may acquire a third vessel width candidate based on velocity information or a vessel width candidate based on dispersion information.

[0206] Furthermore, in the ultrasound diagnostic apparatus 1 according to the third embodiment described above, in step S55, if one of max(X, Y) and min(X, Y) in any of the vessel width candidates based on B-mode information, vessel width candidates based on power information, vessel width candidates based on velocity information, and vessel width candidates based on dispersion information contains an error value, the width of the sample volume SV may be adjusted based on the other of max(X, Y) and min(X, Y) in any of the vessel width candidates based on B-mode information, vessel width candidates based on power information, vessel width candidates based on velocity information, and vessel width candidates based on dispersion information, and the vessel width candidate based on examination information.

[0207] Furthermore, in the ultrasound diagnostic apparatus 1 according to the third embodiment described above, if, in step S53, max(X, Y) and min(X, Y) for all of the vessel width candidates based on B-mode information, vessel width candidates based on power information, vessel width candidates based on velocity information, and vessel width candidates based on dispersion information contain error values, the adjustment function 385 may adjust the width of the sample volume SV based only on the vessel width candidates based on the examination information. In this case, the adjustment function 385 may adjust the width of the sample volume SV by setting max(X, Y) and min(X, Y) to positions obtained by moving the y-coordinate from the center position of the sample volume by the vessel width candidate based on the examination information / 2 in both the positive and negative directions.

[0208] In the ultrasound diagnostic apparatus 1 according to the fourth embodiment described above, the acquisition function 384b acquires a third vessel width candidate based on power information and a fourth vessel width candidate based on velocity information. However, the third and fourth vessel width candidates acquired by the acquisition function 384b are not limited to these. That is, the third and fourth vessel width candidates acquired by the acquisition function 384b are arbitrary. For example, the acquisition function 384b may acquire a third vessel width candidate based on velocity information or a vessel width candidate based on dispersion information, and may acquire a fourth vessel width candidate based on power information or a vessel width candidate based on dispersion information.

[0209] In the ultrasound diagnostic apparatus 1 according to the first to fourth embodiments described above, the sample gate setting function 383, after setting the sample gate SG to the ultrasound image IM during the execution of a PWD mode scan, receives confirmation that the sample volume width adjustment button, which is a first input operation related to adjusting the sample volume, has been pressed, and the acquisition functions 384, 384a, and 384b acquire multiple vessel width candidates. However, this is not limited to this. In other words, the timing of acquiring multiple vessel width candidates is arbitrary. For example, after the sample gate setting function 383 receives confirmation that the sample volume width adjustment button, which is a first input operation related to adjusting the sample volume, has been pressed, the acquisition functions 384, 384a, and 384b may acquire multiple vessel width candidates when the user makes a second input operation related to moving the sample volume SV during the execution of a PWD mode scan. Furthermore, for example, if the sample gate setting function 383 receives confirmation that the sample volume width adjustment button, which is a first input operation related to adjusting the sample volume SV, has been pressed, and then receives a third input operation from the user regarding the start of a PWD mode scan, the acquisition functions 384, 384a, and 384b may acquire multiple vessel width candidates.

[0210] Furthermore, in the ultrasound diagnostic apparatus 1 according to the first to fourth embodiments described above, the width of the sample volume SV is adjusted using the above-described formulas (1) and (2), but the method of adjusting the width of the sample volume SV is not limited to this. For example, the adjustment function 385 may adjust the width of the sample volume SV so that the lower end SV1 and the upper end SV2 of the sample volume SV are positioned at max(X, Y) and min(X, Y) in the blood vessel width candidate based on the B-mode information which is determined to be within the range of the blood vessel width candidate based on the examination information in step S23. In addition, in the ultrasound diagnostic apparatus 1 according to Modification 1, the width of the sample volume SV may be adjusted so that the lower end SV1 and the upper end SV2 of the sample volume SV are positioned at max(X, Y) and min(X, Y) according to the ratio of the width of the sample volume SV to the blood vessel width which is set in advance by the user.

[0211] Furthermore, in the ultrasound diagnostic apparatus according to the first to fourth embodiments and Modification 1 described above, the acquisition functions 384, 384a, and 384b estimate the examination site from information about the examination site included in the setting of the examination mode included in the examination information, but are not limited to this. The acquisition functions 384, 384a, and 384b may also estimate the examination site from information such as Depth, depth and size of the region of interest included in the examination information, or they may estimate the examination site by analyzing the B-mode image IM1 displayed on the display 70 using AI. In this way, by making it possible to estimate the examination site using information such as Depth, depth and size of the region of interest included in the examination information or AI, it becomes possible to determine the examination site even when an examination different from the examination information is being performed, such as examining the blood vessels of the lower limbs when the setting of the examination mode is for abdominal examination.

[0212] In the ultrasound diagnostic device 1 according to the first to fourth embodiments and Modification 1 described above, if the blood vessel width candidate is not within the range of blood vessel width candidates based on the examination information, the device determines that the blood vessel width candidate is unlikely and does not adjust the width of the sample volume SV. However, the device is not limited to this. For example, if the blood vessel width candidate based on B-mode information is not within the range of blood vessel width candidates based on the examination information, the ultrasound diagnostic device 1 may adjust the sample volume SV based on the narrower of the two blood vessel width candidates. If the narrower of the two blood vessel width candidates is the blood vessel width candidate based on the examination information, the adjustment function 385 may adjust the width of the sample volume SV by setting the coordinates of the position obtained by moving the y-coordinate from the coordinate of the center position of the sample volume SV by the blood vessel width candidate based on the examination information / 2 in both the positive and negative directions, respectively, as max(X, Y) and min(X, Y). Although the example given was when the blood vessel width candidate based on B-mode information is not within the range of blood vessel width candidates based on the examination information, the same applies to the case where the blood vessel width candidate based on power information, the blood vessel width based on velocity information, and the blood vessel width candidate based on dispersion information are used instead of the blood vessel width candidate based on B-mode information.

[0213] Furthermore, in the ultrasound diagnostic apparatus 1 according to the first to fourth embodiments and modification 1 described above, the acquisition functions 384, 384a, and 384b may acquire priority information and, based on the priority information, acquire a plurality of vessel width candidates based on at least one of the received information and the examination information. This priority information is information regarding the priority of the ultrasound received information and the examination information. The priority information includes, for example, information regarding the order in which to acquire vessel width candidates based on blood flow velocity values, vessel width candidates based on blood flow dispersion values, vessel width candidates based on blood flow power values, vessel width candidates based on brightness values ​​in B-mode information, and vessel width candidates based on examination information.

[0214] In the above explanation, the term "processor" refers to circuits such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), or a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor functions by reading and executing a program stored in the memory circuit 37. Alternatively, instead of storing the program in the memory circuit 37, the processor may be configured to directly incorporate the program into its circuitry. In this case, the processor functions by reading and executing the program incorporated into the circuitry. The processor is not limited to being configured as a single circuit; it may also be configured by combining multiple independent circuits to form a single processor and realize its functions. Furthermore, the multiple components shown in Figure 1 may be integrated into a single processor to realize its functions.

[0215] According to at least one embodiment described above, inspection efficiency and inspection accuracy in PWD mode can be improved.

[0216] Although several embodiments have been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalent scope. [Explanation of Symbols]

[0217] 1... Ultrasound diagnostic device, 10... Ultrasound probe, 30... Main unit, 31... Transmitting circuit, 32... Receiving circuit, 33... B-mode processing circuit, 34... Doppler processing circuit, 35... Image generation circuit, 36... Image memory, 37... Storage circuit, 38... Processing circuit, 50... Input device, 70... Display, 381... System control function, 382... Display control function, 383... Sample gate setting function, 384... Acquisition function, 385... Adjustment function

Claims

1. A sample gate setting unit sets a sample gate that includes a region on the ultrasound image of the subject from which to acquire blood flow information of the subject, An acquisition unit acquires a plurality of vessel width candidates for a vessel at the location where the sample gate is set, based on at least one of the ultrasound reception information and examination information of the subject. The system includes an adjustment unit that adjusts the region included in the sample gate based on the plurality of candidate blood vessel widths, Ultrasound diagnostic equipment.

2. The received information includes power information relating to the power of blood flow based on the received ultrasound signal, dispersion information relating to the dispersion of blood flow based on the received signal, velocity information relating to the velocity of blood flow based on the received signal, and B-mode information relating to the B-mode based on the received signal. The ultrasound diagnostic apparatus according to claim 1, wherein the acquisition unit acquires, as a plurality of blood vessel width candidates, blood vessel width candidates based on at least two of the information selected from the power information, the dispersion information, the velocity information, the B-mode information, and the inspection information.

3. The sample gate setting unit sets the sample gate on the ultrasound image obtained by imaging the blood vessel from one imaging direction. The acquisition unit acquires a plurality of candidate blood vessel widths for the blood vessels in the ultrasound image obtained from one imaging direction, based on at least one of the ultrasound reception information and examination information of the subject. The ultrasound diagnostic apparatus according to claim 1.

4. The acquisition unit is, Priority information regarding the ultrasound reception information and examination information of the subject is obtained. Based on the priority information, a plurality of blood vessel width candidates are obtained based on at least one of the received information and the inspection information. The ultrasound diagnostic apparatus according to claim 1.

5. The adjustment unit is, Based on the aforementioned multiple candidate vessel widths, the multiple candidate vessel widths are compared, Based on the comparison results obtained by comparing the aforementioned multiple blood vessel width candidates, it is determined whether the blood vessel width candidate is likely or not. If the candidate blood vessel width is determined to be likely, the region included in the sample gate is adjusted. The ultrasound diagnostic apparatus according to claim 1.

6. The acquisition unit acquires, as the plurality of blood vessel width candidates, blood vessel width candidates based on the B-mode information and blood vessel width candidates based on the examination information. The adjustment unit is, Based on the candidate vessel widths based on the B-mode information and the candidate vessel widths based on the examination information, the candidate vessel widths based on the B-mode information and the candidate vessel widths based on the examination information are compared. Based on the comparison result between the candidate vessel width based on the B-mode information and the candidate vessel width based on the examination information, it is determined whether the candidate vessel width based on the B-mode information is likely or not. If the candidate blood vessel width based on the B-mode information is deemed likely, the region is adjusted based on the candidate blood vessel width based on the B-mode information. The ultrasound diagnostic apparatus according to claim 2.

7. The adjustment unit is, If the candidate vessel width based on the B-mode information is determined to be unlikely, the candidate vessel width based on any of the power information, dispersion information, and velocity information is compared with the candidate vessel width based on the examination information. Based on the comparison result between a candidate vessel width based on any of the power information, the dispersion information, and the velocity information and a candidate vessel width based on the examination information, it is determined whether the candidate vessel width based on any of the power information, the dispersion information, and the velocity information is likely to be accurate. The ultrasound diagnostic apparatus according to claim 6.

8. The ultrasound diagnostic apparatus according to claim 1, wherein the received information is raw data before scan conversion processing.

9. The ultrasound diagnostic apparatus according to claim 1, wherein the sample gate setting unit receives a first input operation from the user regarding the adjustment of the region.

10. The ultrasound diagnostic apparatus according to claim 9, wherein the acquisition unit acquires the plurality of blood vessel width candidates when the sample gate setting unit receives the first input operation after setting the sample gate to the ultrasound image while the sample gate setting unit is performing a PWD scan in which pulse waves are transmitted to the scan line for the subject and reflected waves are received.

11. The ultrasound diagnostic apparatus according to claim 9, wherein the acquisition unit acquires the plurality of blood vessel width candidates when the user provides a second input operation regarding the movement of the region while the sample gate setting unit is performing a PWD scan, which involves transmitting a pulse wave to the scan line for the subject and receiving a reflected wave, after the sample gate setting unit has received the first input operation.

12. The ultrasound diagnostic apparatus according to claim 9, wherein the acquisition unit acquires the plurality of blood vessel width candidates when the acquisition unit receives a third input operation from the user after the sample gate setting unit has received the first input operation, the acquisition unit acquires the plurality of blood vessel width candidates when the acquisition unit receives a third input operation from the user regarding the start of execution of a PWD method scan which transmits a pulse wave to the scan line for the subject and receives a reflected wave.

13. The ultrasound diagnostic apparatus according to claim 1, wherein the adjustment unit adjusts the area included in the sample gate according to the ratio of the area to the blood vessel width, which is set in advance by the user.

Images