Ultrasound diagnostic device and display control method

Abstract

To present blood flow information in which aliasing is suppressed for each blood flow by a simple method while suppressing deterioration in real time performance.SOLUTION: An ultrasonic diagnostic device includes a collection part, a generation part, an application part, and a display control part. The collection part collects first time-series data constituted by data lined up in a time axial direction at a first time interval, based on a reflection wave of an ultrasonic wave transmitted on a single ultrasonic condition. The generation part generates second time-series data constituted by data lined up in a time axial direction at a second time interval based on the first time-series data. The application part applies a speed scale in which a ratio of a blood flow advancing in a second advancing direction to a blood flow advancing in a first advancing direction is a threshold or less out of a first speed scale based on the first time-series data and a second speed scale based on the second time-series data, to each of a plurality of blood flows depicted both in the first time-series data and in the second time-series data. The display control part causes a display part to display blood flow information on the plurality of blood flows to which the speed scale is applied.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The embodiments disclosed in this specification and the drawings relate to an ultrasound diagnostic apparatus and a display control method. [Background technology]

[0002] Color flow mapping is a technique used in ultrasound diagnostic devices to observe the velocity of blood flow. Here, a case where color flow mapping is used when a user observes multiple blood flows will be described. The multiple blood flows may include blood flows with relatively high velocity and blood flows with relatively low velocity. That is, the multiple blood flows may include blood flows with various velocities. In such a case, if ultrasound conditions (e.g., pulse repetition frequency (PRF)) are set so that only one of the multiple blood flows can be observed, the set ultrasound conditions may be inappropriate for the other blood flows. This makes it difficult for a user to accurately observe multiple blood flows simultaneously. Therefore, it is desirable to set appropriate ultrasound conditions for multiple blood flows. However, setting appropriate ultrasound conditions for multiple blood flows is cumbersome and time-consuming for a user.

[0003] Therefore, there is a technology that uses a predetermined index to determine the area where the Doppler velocity signal-to-noise ratio is reduced using multiple echo signals acquired under multiple different ultrasound conditions (ultrasound transmission and reception conditions). The determination result is used to change the ultrasound conditions used for Doppler velocity estimation. However, with this technology, multiple ultrasound waves are transmitted under multiple different ultrasound conditions, which results in a relatively large number of ultrasound transmissions. This can result in a decrease in real-time performance.

[0004] Therefore, it is desirable to present blood flow information in which aliasing is suppressed for each blood flow in a simple manner while suppressing degradation in real-time performance. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2018-186923 [Patent Document 2] Japanese Patent Application Publication No. 2-63447 Summary of the Invention [Problem to be solved by the invention]

[0006] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to present blood flow information in which aliasing is suppressed for each blood flow in a simple manner while suppressing a decrease in real-time performance. However, the problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the above problem. Problems corresponding to the effects of each configuration shown in the embodiments described below can also be positioned as other problems. [Means for solving the problem]

[0007] An ultrasound diagnostic apparatus according to an embodiment includes an acquisition unit, a generation unit, an application unit, and a display control unit. The acquisition unit acquires first time series data consisting of data arranged in a time axis direction at a first time interval based on reflected waves of ultrasound transmitted under a single ultrasound condition. The generation unit generates second time series data consisting of data arranged in a time axis direction at a second time interval based on the first time series data. The application unit applies, to each of a plurality of blood flows depicted in both the first time series data and the second time series data, a velocity scale, out of a first velocity scale based on the first time series data and a second velocity scale based on the second time series data, such that a ratio of blood flows proceeding in a second direction of travel to blood flows proceeding in a first direction of travel is equal to or less than a threshold. The display control unit causes the display unit to display blood flow information regarding the plurality of blood flows to which the velocity scales have been applied. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of an ultrasonic diagnostic apparatus according to the first embodiment. [Figure 2] FIG. 2 is a diagram showing an example of the configuration of the Doppler processing circuitry according to the first embodiment. [Figure 3] FIG. 3 is a flowchart showing an example of the flow of processing executed by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 4] FIG. 4 is a diagram for explaining an example of a speed estimation method in the first embodiment. [Figure 5A] FIG. 5A is a diagram for explaining an example of a speed estimation method in the first embodiment. [Figure 5B] FIG. 5B is a diagram for explaining an example of a speed estimation method in the first embodiment. [Figure 6] FIG. 6 is a diagram for explaining a specific example of the process executed by the data interpolation function in step S108 according to the first embodiment. [Figure 7] FIG. 7 is a diagram for explaining a specific example of the process executed by the image generating circuit in step S110 according to the first embodiment. [Figure 8] FIG. 8 is a diagram for explaining an example of another color map. [Figure 9] FIG. 9 shows an example of a display on the display according to the first embodiment. [Figure 10] FIG. 10 shows an example of a display on the display according to the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, ultrasonic diagnostic apparatuses and display control methods according to embodiments and modifications will be described with reference to the drawings.

[0010] (First embodiment) 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 1 according to the first embodiment. As shown in FIG. 1, the ultrasound diagnostic apparatus 1 according to the first embodiment includes an apparatus main body 100, an ultrasound probe 101, an input device 102, and a display 103.

[0011] The ultrasonic probe 101 includes, for example, a plurality of elements (piezoelectric vibrators, piezoelectric elements). These elements generate ultrasonic waves based on a drive signal supplied from a transmission circuit 111 of a transmission / reception circuit 110 included in the device main body 100. Specifically, the elements generate ultrasonic waves having a waveform corresponding to the transmission drive voltage when a voltage (transmission drive voltage) is applied by the transmission circuit 111. The waveform of the transmission drive voltage indicated by the drive signal is the waveform of the voltage applied to the plurality of elements. That is, the ultrasonic probe 101 transmits ultrasonic waves corresponding to the magnitude of the applied transmission drive voltage. The ultrasonic probe 101 also receives reflected waves from the subject P, converts the received reflected waves into received signals (reflected wave signals), which are electrical signals, and outputs the received signals to the device main body 100. The ultrasonic probe 101 also includes, for example, a matching layer provided on the elements and a backing material that prevents ultrasonic waves from propagating backward from the elements. The ultrasonic probe 101 is detachably connected to the device main body 100.

[0012] When ultrasonic waves are transmitted from the ultrasonic probe 101 to the subject P, the transmitted ultrasonic waves are reflected successively by discontinuous surfaces of acoustic impedance in the tissues of the subject P and are received as reflected waves by multiple elements of the ultrasonic probe 101. The amplitude of the received reflected waves depends on the difference in acoustic impedance at the discontinuous surfaces from which the ultrasonic waves are reflected. When the transmitted ultrasonic pulse is reflected by the surface of a moving object such as a moving blood flow or a heart wall, the reflected waves undergo a frequency shift due to the Doppler effect depending on the velocity component of the moving object in the direction of ultrasonic transmission. The ultrasonic probe 101 then outputs the received signal to a receiving circuit 112 of a transmitting / receiving circuit 110, which will be described later.

[0013] The ultrasonic probe 101 is detachably attached to the device main body 100. When scanning a two-dimensional region inside the subject P (two-dimensional scanning), the operator connects, for example, a 1D array probe in which multiple elements are arranged in a row to the device main body 100 as the ultrasonic probe 101. Types of 1D array probes include linear ultrasonic probes, convex ultrasonic probes, and sector ultrasonic probes. When scanning a three-dimensional region inside the subject P (three-dimensional scanning), the operator connects, for example, a mechanical 4D probe or a 2D array probe to the device main body 100 as the ultrasonic probe 101. A mechanical 4D probe is capable of two-dimensional scanning using multiple elements arranged in a row like a 1D array probe, and is also capable of three-dimensional scanning by swinging the multiple elements at a predetermined angle (swing angle). A 2D array probe is capable of three-dimensional scanning using multiple elements arranged in a matrix, and is also capable of two-dimensional scanning by focusing and transmitting ultrasonic waves.

[0014] The input device 102 is realized by input means such as a mouse, keyboard, button, panel switch, touch command screen, foot switch, trackball, joystick, etc. The input device 102 receives various setting requests from the operator of the ultrasound diagnostic apparatus 1 and transfers the received various setting requests to the apparatus main body 100.

[0015] The display 103 displays, for example, a GUI (Graphical User Interface) that allows the operator of the ultrasound diagnostic apparatus 1 to input various setting requests using the input device 102, and displays ultrasound images based on ultrasound image data generated in the apparatus main body 100. The display 103 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, or the like. The display 103 is an example of a display unit.

[0016] The device main body 100 generates ultrasound image data based on reception signals transmitted from the ultrasound probe 101. Note that ultrasound image data is an example of image data. The device main body 100 can generate two-dimensional ultrasound image data based on reception signals transmitted from the ultrasound probe 101 corresponding to a two-dimensional region of the subject P. The device main body 100 can also generate three-dimensional ultrasound image data based on reception signals transmitted from the ultrasound probe 101 corresponding to a three-dimensional region of the subject P. As shown in FIG. 1, the device main body 100 includes a transmission / reception circuit 110, a buffer memory 120, a B-mode processing circuit 130, a Doppler processing circuit 140, an image generation circuit 150, an image memory 160, a storage circuit 170, a processing circuit 180, and a control circuit 190.

[0017] The transmission / reception circuit 110, under the control of the control circuit 190, causes the ultrasonic probe 101 to transmit ultrasonic waves and causes the ultrasonic probe 101 to receive reflected waves of the ultrasonic waves. In other words, the transmission / reception circuit 110 performs scanning via the ultrasonic probe 101. Note that scanning is also referred to as scanning, ultrasonic scanning, or ultrasonic scanning. The transmission / reception circuit 110 is an example of a transmission / reception unit. The transmission / reception circuit 110 has a transmission circuit 111 and a reception circuit 112. The transmission circuit 111 is an example of a transmission unit, and the reception circuit 112 is an example of a reception unit.

[0018] The transmission circuit 111, under the control of the control circuit 190, supplies a drive signal to the ultrasonic probe 101, causing the ultrasonic probe 101 to transmit ultrasonic waves. The transmission circuit 111 has a rate pulser generating circuit, a transmission delay circuit, and a transmission pulser. When scanning a two-dimensional region within the subject P, the transmission circuit 111 causes the ultrasonic probe 101 to transmit an ultrasonic beam for scanning the two-dimensional region. When scanning a three-dimensional region within the subject P, the transmission circuit 111 causes the ultrasonic probe 101 to transmit an ultrasonic beam for scanning the three-dimensional region.

[0019] The rate pulser generating circuit, under the control of the control circuit 190, repeatedly generates rate pulses for forming transmitted ultrasound waves (transmitted beams) at a predetermined pulse repetition frequency (PRF). The rate pulses pass through a transmit delay circuit, so that voltages with different transmit delay times are applied to the transmit pulser. For example, the transmit delay circuit imparts to each rate pulse generated by the rate pulser generating circuit a transmit delay time for each element required to focus the ultrasound waves generated from the ultrasonic probe 101 into a beam and determine the transmit directivity. The transmit pulser supplies a drive signal (drive pulse) to the ultrasonic probe 101 at a timing based on the rate pulse. That is, the transmit pulser applies a voltage (transmitted drive voltage) having a waveform indicated by the drive signal to the ultrasonic probe 101 at a timing based on the rate pulse. The transmit delay circuit arbitrarily adjusts the transmission direction of the ultrasound waves from the element surface by changing the transmit delay time imparted to each rate pulse.

[0020] The drive pulse is transmitted from the transmission pulser via a cable to the elements in the ultrasonic probe 101, and then converted from an electrical signal into mechanical vibration in the elements. That is, when a voltage is applied to the elements, the elements vibrate mechanically. Ultrasound generated by this mechanical vibration is transmitted into the living body (inside the subject P). Here, the ultrasound waves, which have different transmission delay times for each element, are focused and propagate in a predetermined direction.

[0021] The transmission circuit 111 has a function of being able to instantaneously change the transmission frequency, transmission drive voltage, etc. in order to execute a predetermined scanning sequence under the control of the control circuit 190. In particular, the change in the transmission drive voltage is realized by a linear amplifier type oscillation circuit that can instantaneously switch the value of the transmission drive voltage, or a mechanism that electrically switches between multiple power supply units.

[0022] The reflected waves of the ultrasonic waves transmitted by the ultrasonic probe 101 reach the elements inside the ultrasonic probe 101, and are then converted from mechanical vibrations into electrical signals (received signals) in the elements, and the received signals are input to the receiving circuit 112. The receiving circuit 112 has a preamplifier, an A / D (Analog to Digital) converter, a quadrature detection circuit, etc., and performs various processes on the received signals transmitted from the ultrasonic probe 101 to generate reflected wave data (received data). The receiving circuit 112 then stores the generated reflected wave data in the buffer memory 120.

[0023] The preamplifier amplifies the received signal for each channel and performs gain adjustment (gain correction). The A / D converter converts the gain-corrected received signal into a digital signal by A / D converting the gain-corrected received signal. The quadrature detection circuit converts the digitally converted received signal into an in-phase signal (I signal, I: In-phase) and a quadrature signal (Q signal, Q: Quadrature-phase) in the baseband. The quadrature detection circuit then stores the I signal and Q signal (IQ signal) in buffer memory 120 as reflected wave data.

[0024] The receiving circuit 112 generates two-dimensional reflected wave data from the two-dimensional received signals transmitted from the ultrasonic probe 101. The receiving circuit 112 also generates three-dimensional reflected wave data from the three-dimensional received signals transmitted from the ultrasonic probe 101.

[0025] In this embodiment, the ultrasound diagnostic apparatus 1 performs various processes in real time. For example, the ultrasound probe 101 sequentially transmits one frame of reflected wave signals to the receiving circuit 112. Every time the receiving circuit 112 receives one frame of reflected wave signals transmitted from the ultrasound probe 101, it generates one frame of reflected wave data from the one frame of reflected wave signals. Every time the receiving circuit 112 generates one frame of reflected wave data, it stores the one frame of reflected wave data in the buffer memory 120.

[0026] The buffer memory 120 is a memory that temporarily stores reflected wave data generated by the transmission / reception circuit 110. For example, the buffer memory 120 is configured to be able to store a predetermined number of frames of reflected wave data. When a new frame of reflected wave data is generated by the reception circuit 112 while the buffer memory 120 is storing the predetermined number of frames of reflected wave data, the buffer memory 120, under the control of the reception circuit 112, discards the oldest generated frame of reflected wave data and stores the newly generated frame of reflected wave data. For example, the buffer memory 120 is realized by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory.

[0027] The B-mode processing circuit 130 reads the reflected wave data from the buffer memory 120, performs various signal processing on the read reflected wave data, and outputs the reflected wave data that has undergone various signal processing as B-mode data to the image generation circuit 150. The B-mode processing circuit 130 is realized by, for example, a processor. The B-mode processing circuit 130 is an example of a B-mode processing unit.

[0028] For example, every time one new frame of reflected wave data is stored in the buffer memory 120, the B-mode processing circuit 130 reads out the new frame of reflected wave data stored in the buffer memory 120. The B-mode processing circuit 130 then performs various signal processing on the read one frame of reflected wave data to generate one new frame of B-mode data. Every time the B-mode processing circuit 130 generates one frame of B-mode data, it outputs the newly generated one frame of B-mode data to the image generation circuit 150. An example of the various types of signal processing performed by the B-mode processing circuit 130 will be described below.

[0029] For example, the B-mode processing circuit 130 performs quadrature detection, logarithmic amplification, envelope detection processing, etc. on the reflected wave data read out from the buffer memory 120 to generate B-mode data in which the signal strength (amplitude strength) for each sample point is expressed as luminance. Then, the B-mode processing circuit 130 outputs the generated B-mode data to the image generation circuit 150.

[0030] The Doppler processing circuit 140 reads the reflected wave data from the buffer memory 120, performs various signal processing on the read reflected wave data, and outputs the processed reflected wave data as Doppler data to the image generation circuit 150. The Doppler processing circuit 140 is realized by, for example, a processor. The Doppler processing circuit 140 is an example of a Doppler processing unit.

[0031] For example, every time one new frame of reflected wave data is stored in the buffer memory 120, the Doppler processing circuit 140 reads out the new frame of reflected wave data stored in the buffer memory 120. The Doppler processing circuit 140 then performs various signal processing on the read-out frame of reflected wave data to generate a new frame of Doppler data. Every time the Doppler processing circuit 140 generates one frame of Doppler data, it outputs the newly generated frame of Doppler data to the image generation circuit 150. An example of the various types of signal processing performed by the Doppler processing circuit 140 will be described below.

[0032] For example, the Doppler processing circuit 140 performs frequency analysis on the reflected wave data read from the buffer memory 120 to extract motion information of a moving object (blood flow, tissue, contrast agent echo components, etc.) based on the Doppler effect from the reflected wave data, and generates Doppler data indicating the extracted motion information. For example, the Doppler processing circuit 140 extracts average velocity, average variance, average power value, etc. over multiple points as motion information of the moving object, and generates Doppler data indicating the extracted motion information of the moving object. The Doppler processing circuit 140 outputs the generated Doppler data to the image generation circuit 150.

[0033] Using the functions of the Doppler processing circuit 140, the ultrasound diagnostic device 1 can perform a color Doppler method, also known as a color flow mapping (CFM) method. In the color flow mapping method, ultrasonic waves are transmitted and received multiple times along multiple scan lines. The color flow mapping method applies an MTI (Moving Target Indicator) filter to a data sequence at the same position to suppress signals (clutter signals) originating from stationary or slow-moving tissues from the data sequence at the same position and extract signals originating from blood flow (blood flow signals). The color flow mapping method then estimates blood flow information, such as blood flow velocity (average velocity), blood flow variance (average variance value), and blood flow power (average power value), from the blood flow signal. The Doppler processing circuit 140 outputs color Doppler data indicating the blood flow information estimated by the color flow mapping method to the image generation circuit 150. Note that color Doppler data is an example of Doppler data.

[0034] An example of the configuration of the Doppler processing circuit 140 will now be described. FIG. 2 is a diagram showing an example of the configuration of the Doppler processing circuit 140 according to the first embodiment. As shown in FIG. 2, the Doppler processing circuit 140 has a wall filter function 140a, an autocorrelation value calculation function 140b, a blood flow information estimation function 140c, a blanking processing function 140d, and a persistence function 140e. Each processing function of the Doppler processing circuit 140, i.e., the wall filter function 140a, the autocorrelation value calculation function 140b, the blood flow information estimation function 140c, the blanking processing function 140d, and the persistence function 140e, is recorded in a storage device (e.g., the storage circuitry 170) of the ultrasound diagnostic apparatus 1 in the form of a computer-executable program. The Doppler processing circuit 140 is a processor that reads each program from the storage device and executes the read program to realize each processing function corresponding to each program. In other words, the Doppler processing circuitry 140 in a state in which each program has been read out will have each processing function shown in the Doppler processing circuitry 140 of FIG.

[0035] The wall filter function 140a acquires a plurality of pieces of reflected wave data from the buffer memory 120 and applies a wall filter (MTI filter) to the acquired plurality of pieces of reflected wave data to extract, from the plurality of pieces of reflected wave data, a blood flow signal (blood flow Doppler signal) in which clutter signal components are suppressed and blood flow signal components are dominant. Here, the plurality of pieces of reflected wave data to be processed by the wall filter function 140a is a reflected wave data group (time series data, reflected wave data sequence) arranged in the time direction by the number of ensembles (ensemble size, packet size), and is obtained by transmitting and receiving ultrasound waves multiple times to and from the subject P. As described above, the blood flow signal extracted by the wall filter function 140a is dominated by blood flow signal components, but may contain clutter signal components.

[0036] The autocorrelation value calculation function 140b calculates, using a known technique, autocorrelation values ​​(autocorrelation coefficients) used to estimate blood flow information from the blood flow signal extracted by the wall filter function 140a. For example, the autocorrelation value calculation function 140b calculates the autocorrelation values ​​C0 and C1 using the method described in Japanese Patent Application Laid-Open No. 2015-142608.

[0037] The blood flow information estimation function 140c estimates blood flow information using a known technique based on the autocorrelation value calculated by the autocorrelation value calculation function 140b. For example, the blood flow information estimation function 140c estimates blood flow information using the method described in Japanese Patent Application Laid-Open No. 2015-142608. The blood flow information includes blood flow velocity (average velocity), power (average power value), and variance (average variance value).

[0038] The blanking processing function 140d performs blanking processing on the blood flow information estimated by the blood flow information estimation function 140c to remove clutter signal components. For example, the blanking processing sets the velocity value of the clutter signal components to 0. The blanking processing function 140d also performs smoothing filtering, which is filtering in the spatial direction, on the blood flow information that has been subjected to the blanking processing.

[0039] The persistence function 140e applies filtering to smooth the blood flow information that has been subjected to blanking processing and smoothing filtering processing by the blanking processing function 140d in the time direction, and outputs color Doppler data representing the filtered blood flow information to the image generation circuit 150. The persistence function 140e also outputs color Doppler data representing the filtered blood flow information to the PRF calculation function 180a.

[0040] Returning to the explanation of FIG. 1, the B-mode processing circuitry 130 and the Doppler processing circuitry 140 are capable of processing both two-dimensional reflected wave data and three-dimensional reflected wave data.

[0041] The image generation circuitry 150 generates ultrasound image data from the B-mode data output from the B-mode processing circuitry 130 or the Doppler data output from the Doppler processing circuitry 140. The image generation circuitry 150 is realized by a processor.

[0042] For example, the image generation circuit 150 generates two-dimensional B-mode image data that represents the intensity of the reflected wave as brightness from the two-dimensional B-mode data generated by the B-mode processing circuit 130. The image generation circuit 150 also generates two-dimensional Doppler image data or two-dimensional color image data in which motion information or blood flow information is visualized from the two-dimensional Doppler data or Doppler color data generated by the Doppler processing circuit 140. The two-dimensional Doppler image data in which motion information is visualized and the two-dimensional color image data in which blood flow information is visualized are velocity image data, variance image data, power image data, or image data that combines these.

[0043] Here, the image generation circuit 150 generally converts (scan converts) a scan line signal sequence of an ultrasound scan into a scan line signal sequence of a video format, such as that of a television, to generate ultrasound image data for display. For example, the image generation circuit 150 generates ultrasound image data for display by performing coordinate conversion on data output from the B-mode processing circuit 130 and the Doppler processing circuit 140 in accordance with the ultrasound scanning format of the ultrasound probe 101. In addition to scan conversion, the image generation circuit 150 may also perform various image processing, such as image processing (smoothing processing) that regenerates an average brightness image using multiple image frames after scan conversion, and image processing (edge ​​enhancement processing) that uses a differential filter within the image. In addition, the image generation circuit 150 may combine text information of various parameters, scales, body marks, etc. with the ultrasound image data.

[0044] Furthermore, the image generation circuit 150 generates three-dimensional B-mode image data by performing coordinate transformation on the three-dimensional B-mode data generated by the B-mode processing circuit 130. The image generation circuit 150 also generates three-dimensional Doppler image data by performing coordinate transformation on the three-dimensional Doppler data generated by the Doppler processing circuit 140. That is, the image generation circuit 150 generates "three-dimensional B-mode image data and three-dimensional Doppler image data" as "three-dimensional ultrasound image data (volume data)." The image generation circuit 150 then performs various rendering processes on the volume data to generate various types of two-dimensional image data for displaying the volume data on the display 103.

[0045] The rendering process performed by the image generation circuit 150 includes, for example, a process of generating MPR image data from volume data using multi-planar reconstruction (MPR). The rendering process performed by the image generation circuit 150 also includes, for example, a volume rendering (VR) process of generating two-dimensional image data reflecting three-dimensional information. The image generation circuit 150 is an example of an image generation unit.

[0046] The B-mode data and Doppler data are ultrasound image data before scan conversion processing, and the data generated by the image generation circuit 150 is ultrasound image data for display after scan conversion processing. Note that the B-mode data and Doppler data are also called raw data.

[0047] The image memory 160 is a memory that stores various types of image data generated by the image generation circuit 150. The image memory 160 also stores data generated by the B-mode processing circuit 130 and the Doppler processing circuit 140. The B-mode data and Doppler data stored in the image memory 160 can be called up by an operator after diagnosis, for example, and becomes ultrasound image data for display via the image generation circuit 150. For example, the image memory 160 is realized by a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, or a hard disk or an optical disk.

[0048] The memory circuitry 170 stores control programs for scanning (transmitting and receiving ultrasound), image processing, and display processing, as well as various data such as diagnostic information (e.g., patient ID, doctor's findings, etc.), diagnostic protocols, and various body marks. The memory circuitry 170 is also used, as necessary, to store data stored in the image memory 160. For example, the memory circuitry 170 is realized by a semiconductor memory element such as a flash memory, a hard disk, or an optical disk.

[0049] The processing circuitry 180 executes various processes. As shown in FIG. 1 , the processing circuitry 180 has a PRF calculation function 180a, a data interpolation function 180b, a scale adjustment function 180c, and a display mode selection function 180d. Each processing function of the processing circuitry 180, namely, the PRF calculation function 180a, the data interpolation function 180b, the scale adjustment function 180c, and the display mode selection function 180d, is recorded in the form of a computer-executable program in a storage device (e.g., the storage circuitry 170) of the ultrasound diagnostic apparatus 1. The processing circuitry 180 is a processor that reads each program from the storage device and executes the read program to realize each processing function corresponding to each program. In other words, the processing circuitry 180 in a state in which each program has been read has each processing function shown in the processing circuitry 180 of FIG. 1 . The processes executed by the PRF calculation function 180a, the data interpolation function 180b, the scale adjustment function 180c, and the display mode selection function 180d will be described later.

[0050] The control circuit 190 controls the overall processing of the ultrasound diagnostic apparatus 1. Specifically, the control circuit 190 controls the processing of the transmission circuit 111, the reception circuit 112, the B-mode processing circuit 130, the Doppler processing circuit 140, the image generation circuit 150, and the processing circuit 180 based on various setting requests input by the operator via the input device 102 and various control programs and various data read from the storage circuit 170. The control circuit 190 also controls the display 103 to display an ultrasound image based on ultrasound image data for display stored in the image memory 160. For example, the control circuit 190 controls the display 103 to display a B-mode image based on B-mode image data or a color image based on color image data. The control circuit 190 also controls the display 103 to display a color image superimposed on the B-mode image. The control circuit 190 is an example of a display control unit or a control unit. The control circuit 190 is realized by, for example, a processor. An ultrasound image is an example of an image.

[0051] Furthermore, the control circuit 190 controls the ultrasonic probe 101 via the transmission / reception circuit 110, thereby controlling ultrasonic scanning.

[0052] The term "processor" used in the description refers to a circuit such as a central processing unit (CPU), a graphics processing unit (GPU), 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), or a field programmable gate array (FPGA)). The processor reads a program stored in the memory circuit 170 and executes the read program to realize its function. Instead of storing the program in the memory circuit 170, the processor may be configured so that the program is directly embedded in its circuit. In this case, the processor reads and executes the program embedded in the circuit to realize its function. Each processor in this embodiment is not limited to being configured as a single circuit, but may be configured as a single processor by combining multiple independent circuits to realize its function. 1 (for example, the B-mode processing circuitry 130, the Doppler processing circuitry 140, the image generation circuitry 150, the processing circuitry 180, and the control circuitry 190) may be integrated into a single processor to realize its functions. That is, the B-mode processing circuitry 130, the Doppler processing circuitry 140, the image generation circuitry 150, the processing circuitry 180, and the control circuitry 190 may be integrated into a single processing circuit realized by a processor.

[0053] The above has described the overall configuration of the ultrasound diagnostic device 1 according to the first embodiment. Based on the above configuration, the ultrasound diagnostic device 1 executes the processing described below so as to be able to present blood flow information with reduced aliasing for each blood flow in a simple manner while suppressing degradation in real-time performance.

[0054] FIG. 3 is a flowchart showing an example of the flow of processing executed by the ultrasound diagnostic apparatus 1 according to the first embodiment. As shown in FIG. 3, the PRF calculation function 180a acquires blood flow information for one heartbeat (step S101). For example, the PRF calculation function 180a acquires color Doppler data for one heartbeat, which indicates blood flow information for one heartbeat, output from the persistence function 140e of the Doppler processing circuit 140. This blood flow information is blood flow information within a ROI (Region of Interest) set by the ultrasound diagnostic apparatus 1 when scanning the subject P, who is the observation target. The ROI contains multiple blood flows that the user wishes to observe. Furthermore, within the entire region of the ROI, a velocity value of "0" is set for regions where the power value is equal to or less than a predetermined value. This is to display only the blood flow velocity.

[0055] Here, the color Doppler data acquired in step S101 includes a mosaic pattern, which is a pattern in which, for example, reddish pixels (images) indicating blood flow moving toward the ultrasound probe 101 and bluish pixels (images) indicating blood flow moving away from the ultrasound probe 101 are mixed within a certain region.

[0056] Then, the PRF calculation function 180a calculates the mosaic pattern ratio of the region of the fastest blood flow among the regions of the blood flow included in the acquired color Doppler data (step S102).

[0057] A specific example of the process executed by the PRF calculation function 180a in step S102 will be described. For example, the PRF calculation function 180a extracts multiple blood flow regions within the ROI from the color Doppler data using a known region extraction (segmentation) technique. The PRF calculation function 180a then identifies the region with the fastest blood flow velocity from among the multiple blood flow regions. The PRF calculation function 180a then identifies reddish pixels and bluish pixels from among the multiple pixels constituting the identified region with the fastest blood flow velocity. The PRF calculation function 180a then calculates the ratio of the number of bluish pixels to the number of reddish pixels, or the ratio of the number of reddish pixels to the number of bluish pixels, as the mosaic pattern ratio of the fastest blood flow velocity. That is, the PRF calculation function 180a calculates the ratio of blood flow moving in a direction away from the ultrasonic probe 101 to blood flow moving in a direction toward the ultrasonic probe 101, or the ratio of blood flow moving in a direction toward the ultrasonic probe 101 to blood flow moving in a direction away from the ultrasonic probe 101, as a mosaic pattern ratio. If the direction toward the ultrasonic probe 101 is defined as the first traveling direction, the direction away from the ultrasonic probe 101 is defined as the second traveling direction. Also, if the direction away from the ultrasonic probe 101 is defined as the first traveling direction, the direction toward the ultrasonic probe 101 is defined as the second traveling direction.

[0058] Then, the PRF calculation function 180a calculates a PRF that allows estimation (detection) of the maximum flow velocity in a state where aliasing does not occur or aliasing is suppressed (step S103). Here, no aliasing means that a mosaic pattern does not occur. Furthermore, suppression of aliasing means that the size of the area where a mosaic pattern occurs is suppressed.

[0059] A specific example of the process executed by the PRF calculation function 180a in step S103 will be described. For example, the storage circuitry 170 stores a PRF calculation table for calculating the PRF at which the maximum flow velocity can be estimated. The PRF calculation table associates a region, a mosaic pattern ratio, and the PRF at which the maximum flow velocity corresponding to the region and mosaic pattern can be estimated, and these are registered for each subject. That is, the PRF calculation table registers multiple records for each subject, each record including a pair of a region, a mosaic pattern ratio, and a PRF.

[0060] Then, the PRF calculation function 180a identifies a region included in the ROI. For example, the PRF calculation function 180a identifies the region scanned when generating the color Doppler data acquired in step S101 as a region included in the ROI.

[0061] Then, the PRF calculation function 180a refers to the PRF calculation table and identifies a record in which the identified region and the mosaic pattern ratio calculated in step S102 are registered from among multiple records corresponding to the subject P that is the observation target. The PRF calculation function 180a then acquires the PRF registered in the identified record as the PRF at which the above-mentioned maximum flow velocity can be estimated. In this way, the PRF calculation function 180a calculates the PRF at which the maximum flow velocity can be estimated.

[0062] Note that the PRF calculation function 180a may change the PRF, acquire blood flow information for one heartbeat based on the changed PRF in step S101, and repeatedly execute the processes of steps S102 and S103 until the ratio of the mosaic pattern calculated in step S102 becomes 0 or equal to or less than a predetermined value greater than 0. Then, the PRF calculation function 180a may calculate the PRF when the ratio of the mosaic pattern calculated in step S102 becomes 0 or equal to or less than a predetermined value greater than 0 as the PRF at which the above-mentioned maximum flow velocity can be estimated.

[0063] Then, the control circuit 190 determines whether or not the user has pressed a button for executing the scale adjustment process, which is the process from step S105 onwards (the process from steps S105 to S110) (step S104). Such a button is included in the input device 102. If the button has not been pressed (step S104: No), the control circuit 190 again makes the above-mentioned determination in step S104. On the other hand, if the button has been pressed (step S104: Yes), the control circuit 190 proceeds to step S105. Note that the control circuit 190 may proceed from step S103 to step S105 without performing the determination process of step S104.

[0064] In step S105, the control circuit 190 sets the PRF calculated in step S103 in the ultrasound probe 101. In this way, the control circuit 190 sets, as a single ultrasound condition, the PRF corresponding to the fastest (highest) of multiple blood flow velocities included in the region of the subject P that is the observation target. The control circuit 190 is also an example of a setting unit. That is, the control circuit 190 controls the ultrasound probe 101 via the transmission circuitry 111 to start transmitting ultrasound waves at the PRF calculated in step S103. Specifically, the control circuit 190 transmits an instruction to the transmission circuitry 111 to start transmitting ultrasound waves at the PRF calculated in step S103. The transmission circuitry 111, having received this instruction, controls the ultrasound probe 101 to start transmitting ultrasound waves at the PRF calculated in step S103.

[0065] Then, the data interpolation function 180b determines whether the set number of ensembles (ensemble size, packet size) is smaller than the number of ensembles normally used for the region included in the ROI (standard number of ensembles used) (step S106). For example, the standard number of ensembles used for the heart is 8, and the standard number of ensembles used for the abdomen is 16.

[0066] For example, in order to increase the frame rate, the number of ensembles may be set lower than the number of ensembles normally used for the region included in the ROI. In such cases, the accuracy of the blood flow information obtained in the processes after step S107 may be reduced. Therefore, if the set number of ensembles is smaller than the number of ensembles normally used for the region included in the ROI (step S106: Yes), the data interpolation function 180b increases the number of ensembles so that the set number of ensembles becomes the number of ensembles normally used for the region included in the ROI (step S107). Specifically, the data interpolation function 180b sets the number of ensembles normally used for the region included in the ROI to the wall filter function 140a. As a result, the wall filter function 140a sets the number of ensembles normally used for the region included in the ROI. On the other hand, if the set number of ensembles is equal to or greater than the number of ensembles normally used for the region included in the ROI (step S106: No), the data interpolation function 180b proceeds to step S108. The data interpolation function 180b may proceed from step S105 to step S108 without performing the processes of step S106 and step S107.

[0067] Then, the data interpolation function 180b acquires a plurality of time-series data with different data intervals (step S108). A specific example of the process executed by the data interpolation function 180b in step S108 will be described below, but before that, an example of a speed estimation method in this embodiment will be described. Figures 4, 5A, and 5B are diagrams for explaining an example of a speed estimation method in this embodiment.

[0068] In Fig. 4, the horizontal axis is the real axis and the vertical axis is the imaginary axis. For example, when the ensemble number is 3, as shown in Fig. 4, the average values ​​of angles θ1, θ2, and θ3 formed between each of three vectors 11 to 13 and the real axis are estimated as velocity components. That is, in color flow mapping, the angle θv formed between vector 14, which is the sum of the three vectors 11 to 13, and the real axis is estimated as velocity.

[0069] Here, in Figure 5A, if we take the case where the position of object 15 moves by angle θ1 as shown on the left side as a reference, as shown on the right side, even if observed for the same period of time, if object 15 hardly moves, a relatively slow speed will be estimated as the blood flow speed.

[0070] Also, in Figure 5B, if we take the case where the position of object 15 moves by angle θ1 as shown on the left side as a reference, and if object 15 moves significantly even when observed for the same period of time, as shown on the right side, a relatively fast blood flow velocity will be estimated.

[0071] Next, a specific example of the processing executed by the data interpolation function 180b in step S108 will be described. Fig. 6 is a diagram for explaining a specific example of the processing executed by the data interpolation function 180b in step S108 according to the first embodiment. As shown in Fig. 6, the data interpolation function 180b acquires, from the buffer memory 120, a reflected wave data group 21 made up of a plurality of reflected wave data 20 obtained based on the reflected waves of the ultrasound transmitted at the PRF calculated in step S103. Note that the reflected wave data 20 included in the reflected wave data group 21 will be referred to as "reflected wave data 21a" in order to distinguish it from the reflected wave data included in other reflected wave data groups.

[0072] The reflected wave data group 21 is time-series data composed of a plurality of reflected wave data 21a arranged in chronological order. The time interval between two adjacent reflected wave data 21a in the time axis direction is "T". The reflected wave data group 21 is reference time-series data. The reflected wave data group 21 is first time-series data based on reflected waves of ultrasound transmitted under a single ultrasound condition, and is an example of first time-series data composed of data arranged in the time axis direction at a first time interval "T". The reflected wave data group 21 is also time-series data based on reflected waves of ultrasound transmitted to multiple blood flow-containing regions of the subject P, which is the observation target. The ultrasound probe 101 and the transmission / reception circuitry 110 collect this reflected wave data group 21. The ultrasound probe 101 and the transmission / reception circuitry 110 are an example of an acquisition unit.

[0073] The data interpolation function 180b then inserts the reflected wave data 20 into the reference reflected wave data group 21 to generate a reflected wave data group 22. For example, the data interpolation function 180b uses a pulse wave Doppler signal to estimate the reflected wave data 20 between two pieces of reflected wave data 21a that are adjacent in the time axis direction. Specifically, for example, the storage circuitry 170 stores relationship information indicating the relationship between waveform changes indicated by pulse wave Doppler signals previously collected by scanning the region of the subject P identified in step S103 and color Doppler data (color signals) obtained based on these pulse wave Doppler signals. In this case, the data interpolation function 180b refers to the relationship information stored in the storage circuitry 170 and estimates the reflected wave data 20 between two pieces of reflected wave data 21a that are adjacent in the time axis direction from the relationship indicated by the relationship information. The data interpolation function 180b may estimate the reflected wave data 20 between two pieces of reflected wave data 21a adjacent in the time axis direction using other methods. For example, the data interpolation function 180b may estimate the average of two pieces of reflected wave data 21a adjacent in the time axis direction as the reflected wave data 20. The data interpolation function 180b may also determine two weights to be used when performing weighted addition of the two pieces of reflected wave data 21a according to the blood flow accelerations corresponding to the two pieces of reflected wave data 21a, and estimate the reflected wave data 20 between the two pieces of reflected wave data 21a by performing weighted addition of the two pieces of reflected wave data 21a using the determined two weights. The blood flow accelerations corresponding to the two pieces of reflected wave data 21a are calculated from the blood flow velocity indicated by the color Doppler data obtained from the two pieces of reflected wave data 21a. For example, if the two blood flow accelerations corresponding to the two pieces of reflected wave data 21a have the same value, the data interpolation function 180b sets the two weights to be the same. Furthermore, when the accelerations of the two blood flows are different values, the data interpolation function 180b assigns a weight corresponding to the smaller acceleration greater than the weight corresponding to the larger acceleration.

[0074] The data interpolation function 180b then generates a reflected wave data group 22 by inserting the estimated reflected wave data 20 between two pieces of reflected wave data 21a that are adjacent in the time axis direction. The reflected wave data group 22 is time-series data. Note that the reflected wave data 20 included in the reflected wave data group 22 is referred to as "reflected wave data 22a" to distinguish it from reflected wave data included in other reflected wave data groups. The time interval between two pieces of reflected wave data 22a that are adjacent in the time axis direction is "T / 2."

[0075] Furthermore, the data interpolation function 180b thins out reflected wave data 22a from the reflected wave data group 22 to generate a reflected wave data group 23. The reflected wave data group 23 is time-series data. The reflected wave data 20 included in the reflected wave data group 23 is referred to as "reflected wave data 23a" to distinguish it from the reflected wave data included in other reflected wave data groups. The time interval between two adjacent reflected wave data 23a in the time axis direction is "(3T) / 2".

[0076] Similarly, the data interpolation function 180b thins out reflected wave data 22a from the reflected wave data group 22 to generate reflected wave data groups 24 and 25. The reflected wave data groups 24 and 25 are time-series data. The reflected wave data 20 included in the reflected wave data group 24 is referred to as "reflected wave data 24a" to distinguish it from the reflected wave data included in the other reflected wave data groups. The time interval between two adjacent reflected wave data 24a in the time axis direction is "2T." The reflected wave data 20 included in the reflected wave data group 25 is referred to as "reflected wave data 25a" to distinguish it from the reflected wave data included in the other reflected wave data groups. The time interval between two adjacent reflected wave data 25a in the time axis direction is "3T."

[0077] In this way, in step S108, the data interpolation function 180b acquires multiple pieces of time series data 21 to 25 having different data intervals. Furthermore, the data interpolation function 180b generates time series data 22 to 25 based on the time series data 21. Specifically, the data interpolation function 180b generates the time series data 22 to 25 by performing at least one of an interpolation process for interpolating data on the time series data 21 and a thinning process for thinning data from the time series data 22. Each of the time series data 22 to 25 is an example of second time series data made up of data arranged in the time axis direction at a second time interval. The data interpolation function 180b is an example of a generating unit. The data interpolation function 180b may generate time series data used in the processes in step S109 and subsequent steps by performing a thinning process for thinning data from the time series data 21. That is, the data interpolation function 180b may generate time series data to be used in the processing in steps S109 and thereafter by performing a thinning process to thin out data from time series data based on the time series data 21. The time series data generated in this manner is also an example of second time series data.

[0078] The longer the time interval between two adjacent reflected wave data in the time axis direction, the more accurately a slower blood flow velocity can be estimated.Furthermore, the shorter the time interval between two adjacent reflected wave data in the time axis direction, the more accurately a faster blood flow velocity can be estimated.

[0079] 6, the upper limit of the velocity scale (velocity range) 31 when the Doppler processing circuit 140 estimates velocity using the reflected wave data group 21 is set to "reference velocity." In this case, the upper limit of the velocity scale 32 when the Doppler processing circuit 140 estimates velocity using the reflected wave data group 22 is twice the "reference velocity." Note that the velocity scale is, for example, the range of velocities that can be estimated in a state where no aliasing occurs.

[0080] Furthermore, when the Doppler processing circuit 140 estimates velocity using the reflected wave data group 23, the upper limit of the velocity scale 33 is 2 / 3 times the "reference velocity." When the Doppler processing circuit 140 estimates velocity using the reflected wave data group 24, the upper limit of the velocity scale 34 is 1 / 2 times the "reference velocity." When the Doppler processing circuit 140 estimates velocity using the reflected wave data group 25, the upper limit of the velocity scale 35 is 1 / 3 times the "reference velocity."

[0081] Then, the scale adjustment function 180c calculates the ratio of the mosaic pattern of each blood flow region using the plurality of time series data 21 to 25 (step S109). A specific example of the process executed by the scale adjustment function 180c in step S109 will be described.

[0082] For example, the scale adjustment function 180c transmits the time series data 21 to the wall filter function 140a. Then, the wall filter function 140a extracts a blood flow signal from the time series data 21. That is, the wall filter function 140a performs a filter process on the time series data 21. The wall filter function 140a is an example of a filter processing unit. Then, the autocorrelation value calculation function 140b calculates an autocorrelation value from the blood flow signal. Then, the blood flow information estimation function 140c estimates blood flow information using the autocorrelation value. Then, the scale adjustment function 180c acquires color Doppler data indicating the estimated blood flow information. In this way, the scale adjustment function 180c acquires color Doppler data indicating blood flow information based on the time series data 21.

[0083] The scale adjustment function 180c also performs similar processing on each of the time series data 22 to 25. That is, the scale adjustment function 180c acquires color Doppler data indicating blood flow information based on the time series data 22, color Doppler data indicating blood flow information based on the time series data 23, color Doppler data indicating blood flow information based on the time series data 24, and color Doppler data indicating blood flow information based on the time series data 25.

[0084] Then, in a similar manner to the method by which the PRF calculation function 180a extracts multiple blood flow regions in step S102, the scale adjustment function 180c extracts multiple blood flow regions from the color Doppler data indicating blood flow information based on the time-series data 21. Then, in a similar manner to the method by which the PRF calculation function 180a calculates the ratio of the mosaic pattern in the identified region in step S102, the scale adjustment function 180c calculates the ratio of the mosaic pattern in each of the multiple blood flow regions.

[0085] The scale adjustment function 180c also performs similar processing on the color Doppler data indicating blood flow information based on each of the time series data 22 to 25. That is, the scale adjustment function 180c extracts multiple blood flow regions from the color Doppler data indicating blood flow information based on the time series data 22 and calculates the mosaic pattern ratio in each of the extracted blood flow regions. The scale adjustment function 180c also extracts multiple blood flow regions from the color Doppler data indicating blood flow information based on the time series data 23 and calculates the mosaic pattern ratio in each of the extracted blood flow regions. The scale adjustment function 180c also extracts multiple blood flow regions from the color Doppler data indicating blood flow information based on the time series data 24 and calculates the mosaic pattern ratio in each of the extracted blood flow regions. The scale adjustment function 180c also extracts multiple blood flow regions from the color Doppler data indicating blood flow information based on the time series data 25 and calculates the mosaic pattern ratio in each of the extracted blood flow regions.

[0086] Below, we will explain the case where three blood flow regions A to C are extracted from color Doppler data showing blood flow information based on each of time series data 21 to 25. That is, region A extracted from color Doppler data showing blood flow information based on time series data 21, region A extracted from color Doppler data showing blood flow information based on time series data 22, region A extracted from color Doppler data showing blood flow information based on time series data 23, region A extracted from color Doppler data showing blood flow information based on time series data 24, and region A extracted from color Doppler data showing blood flow information based on time series data 25 are the same region. The same is true for region B and region C.

[0087] Then, the scale adjustment function 180c applies, for each region, the velocity scale with the lowest upper limit of the velocity scales at which the ratio of the mosaic pattern is equal to or less than the threshold value X, the image generation circuit 150 applies a color map corresponding to each region, and the control circuit 190 displays the applied result on the display 103 (step S110). A specific example of the processing executed by the scale adjustment function 180c, the image generation circuit 150, and the control circuit 190 in step S110 will be described.

[0088] For example, a case will be described in which, for region A, among multiple speed scales 31 to 35, speed scales 31 to 33 have mosaic pattern ratios equal to or less than threshold X. In this case, the scale adjustment function 180c applies, for region A, speed scale 33, which has the lowest upper speed limit, among speed scales 31 to 33 for which the mosaic pattern ratios are equal to or less than threshold X. That is, the scale adjustment function 180c applies the time-series data 23 corresponding to speed scale 33 to region A. As a result, when threshold X is "0", aliasing does not occur in region A, and speed can be estimated with finer granularity. Furthermore, when threshold X is greater than "0", aliasing that occurs is suppressed to an amount corresponding to threshold X, and speed can be estimated with finer granularity.

[0089] Also, for example, a case will be described in which, for region B, of the multiple speed scales 31 to 35, only speed scale 32 has a mosaic pattern ratio equal to or less than threshold X. In this case, the scale adjustment function 180c applies, to region B, speed scale 32 at which the mosaic pattern ratio is equal to or less than threshold X. That is, the scale adjustment function 180c applies, to region B, time-series data 22 corresponding to speed scale 32. As a result, when threshold X is "0", aliasing does not occur in region B, and a higher speed can be estimated. Furthermore, when threshold X is greater than "0", aliasing that occurs is suppressed to an amount corresponding to threshold X, and a higher speed can be estimated.

[0090] Such a technique of applying a velocity scale (time series data) that does not cause aliasing for each blood flow region can also be applied to techniques for observing blood flow velocity other than color flow mapping.

[0091] Then, the scale adjustment function 180c outputs the color Doppler data to which a velocity scale that does not cause aliasing has been applied to each region of the blood flow to the blanking processing function 140d.

[0092] The scale adjustment function 180c applies, to each of the multiple blood flows depicted in all of the time series data 21 to 25, a velocity scale from among multiple velocity scales based on the multiple time series data 21 to 25, at which the ratio of the mosaic pattern is equal to or less than a threshold. The velocity scale based on the time series data 21 is an example of a first velocity scale. Furthermore, the velocity scales based on each of the time series data 22 to 25 are an example of a second velocity scale. The scale adjustment function 180c is an example of an application unit.

[0093] The blanking processing function 140d performs blanking processing on the color Doppler data to remove clutter signal components, and also performs smoothing filtering, which is filtering in the spatial direction, on the color Doppler data that has been subjected to blanking processing.

[0094] The persistence function 140e performs filtering to smooth the color Doppler data in the time direction after blanking processing and smoothing filtering processing have been performed by the blanking processing function 140d, and outputs the filtered color Doppler data to the image generation circuit 150.

[0095] 7 is a diagram illustrating a specific example of the process executed by the image generation circuit 150 in step S110 according to the first embodiment. The color map 40 is shown on the left side of FIG. 7. However, in the example shown in FIG. 7, the color map 40 is a color map corresponding to reddish colors, and the color map corresponding to bluish colors is not shown. In reality, the color map corresponding to bluish colors is symmetrical to the color map 40 corresponding to reddish colors with respect to the horizontal axis. In this embodiment, the control circuit 190 causes the display 103 to display the color map 40 shown in FIG. 7.

[0096] For example, the color map 40 is a map showing the correspondence between the blood flow velocity, the color corresponding to each velocity scale of the velocity scales 31 to 35, and the pixel value (grayscale) of the displayed color image data.

[0097] For example, the range of blood flow velocity defined in the color map 40 ranges from "0" to twice the reference velocity. Also, in the color map 40, different colors are assigned to the velocity scales 31 to 35. For example, yellow is assigned to the velocity scale 31, blue is assigned to the velocity scale 32, green is assigned to the velocity scale 33, orange is assigned to the velocity scale 34, and purple is assigned to the velocity scale 35.

[0098] For example, the image generation circuit 150 acquires a color and a pixel value corresponding to the blood flow velocity for each pixel of the color image data based on the color map 40. Then, the image generation circuit 150 generates color image data by assigning the acquired color and pixel value to the pixel of the color image data. Then, the control circuit 190 displays on the display 103 a superimposed image in which a color image based on the color image data and a B-mode image are superimposed. That is, the control circuit 190 displays on the display 103 blood flow information regarding a plurality of blood flows to which a velocity scale has been applied.

[0099] The image generating circuit 150 may generate color image data based on the velocity scales 31 to 35 shown on the right side of Fig. 7, instead of the color map 40. In this case, the control circuit 190 causes the display 103 to display the velocity scales 31 to 35 shown on the right side of Fig. 7. However, the velocity scales 31 to 35 shown on the right side of Fig. 7 are velocity scales corresponding to reddish colors, and the velocity scales corresponding to bluish colors are not shown. In reality, the velocity scales corresponding to bluish colors exist in line symmetry with the velocity scales 31 to 35 corresponding to reddish colors, with the horizontal axis as the axis.

[0100] For example, different colors are assigned to the velocity scales 31 to 35 shown on the right side of Fig. 7, similar to the velocity scales 31 to 35 in the color map 40. Note that the upper limit values ​​of the velocity scales 31 to 35 shown on the right side of Fig. 7 are the same as those described above.

[0101] The velocity scales 31 to 35 shown on the right side of FIG. 7 define the correspondence between the blood flow velocity and pixel values ​​at a finer granularity. The image generation circuit 150 may generate color image data based on these velocity scales 31 to 35. That is, the image generation circuit 150 may regard these velocity scales 31 to 35 as a single color map and generate color image data based on this single color map. For example, the image generation circuit 150 generates color image data for each blood flow region using a velocity scale applied by the scale adjustment function 180c from among the multiple velocity scales 31 to 35. More specifically, the image generation circuit 150 acquires a pixel value corresponding to the blood flow velocity for each pixel of the color image data based on the applied velocity scale. The image generation circuit 150 then generates color image data by assigning a color corresponding to the acquired pixel value and the applied velocity scale to the pixel of the color image data.

[0102] In the first embodiment, multiple velocity scales 31 to 35 are obtained from one time series data 25 obtained by transmitting ultrasound under one ultrasound condition, rather than from multiple time series data obtained by transmitting ultrasound under multiple ultrasound conditions. In the first embodiment, an appropriate velocity scale is applied to each blood flow region from among the multiple velocity scales 31 to 35. This makes it possible to present blood flow information with reduced aliasing for each blood flow in a simple manner while suppressing degradation in real-time performance.

[0103] The image generation circuit 150 may use other color maps. FIG. 8 is a diagram illustrating an example of another color map. For example, as shown in FIG. 8, for a blood flow whose velocity is lower than a threshold value α, the image generation circuit 150 acquires a color corresponding to the blood flow velocity for each pixel of the color image data based on a low-velocity color map. For a blood flow whose velocity is higher than a threshold value β, which is higher than the threshold value α, the image generation circuit 150 acquires a color corresponding to the blood flow velocity for each pixel of the color image data based on a high-velocity color map. The image generation circuit 150 then generates color image data by assigning the acquired colors to the pixels of the color image data. The control circuit 190 then displays a superimposed image, in which a color image based on the color image data and a B-mode image are superimposed, on the display 103.

[0104] In this case, the image generating circuit 150 may separately generate color image data including blood flow whose velocity is lower than the threshold value α and color image data including blood flow whose velocity is higher than the threshold value β. In this case, the control circuit 190 causes the display 103 to separately display two color images based on the two color image data.

[0105] The ultrasound diagnostic device 1 may apply time series data obtained by extremely thinning out the reflected wave data 22a from the reflected wave data group 22 to a region of blood flow whose velocity is lower than the threshold value α. The ultrasound diagnostic device 1 may then detect clutter signals and perform clutter evaluation using the detected clutter signals.

[0106] Next, an example of processing executed by the display mode selection function 180d will be described. 9 and 10 are display examples of the display 103 according to the first embodiment. The display mode selection function 180d receives an instruction from the user via the input device 102 to display a plurality of superimposed images with different velocity scales applied to the blood flow region. Then, based on the received instruction, the display mode selection function 180d sets a mode for displaying a plurality of superimposed images with different velocity scales applied to the blood flow region.

[0107] 9 shows a display example when the display mode selection function 180d receives an instruction from the user via the input device 102 to display two superimposed images with different velocity scales applied to the blood flow region. In this case, the display mode selection function 180d sets a mode to display two superimposed images with different velocity scales applied to the blood flow region.

[0108] 9, the control circuit 190 displays two superimposed images 50 and 55 side by side on the display 103. The superimposed image 50 is an image in which a color image 52 is superimposed on a B-mode image 51. The color image 52 is a color image based on color image data generated by processing by the Doppler processing circuit 140 and the image generation circuit 150, without involving the processing by the processing circuit 180 shown in FIG.

[0109] A blood flow 52a included in the color image 52 has aliasing 52b, and blood flows 52c and 52d are displayed dark and unclear.

[0110] The superimposed image 55 is an image in which a color image 57 is superimposed on a B-mode image 56. The color image 57 is a color image based on color image data generated by the processing circuitry 180 through the processing shown in FIG.

[0111] Aliasing 57b occurs in blood flow 57a included in color image 57. This is because threshold value X, which is compared with the ratio of the mosaic pattern in step S110 shown in FIG.

[0112] Furthermore, blood flows 57c and 57d are displayed brightly and clearly. Here, the color map used to generate color image 52 is a color map corresponding to velocity scale 31. On the other hand, the color map used to generate color image 57 is a color map corresponding to velocity scale 32, which is twice the velocity scale 31. Thus, color images 52 and 57 have different color maps. That is, color image 52 uses velocity scale 31 and a color map corresponding to velocity scale 31, whose upper limit value is the "reference velocity," which allows for estimation of relatively high blood flows, even though the velocities of blood flows 52c and 52d are low. As a result, blood flows 52c and 52d appear dark and unclear. On the other hand, color image 57 uses velocity scale 32 and a color map corresponding to velocity scale 32, which are appropriate enough to prevent aliasing in blood flows 57c and 57d, so blood flows 52c and 52d appear bright and clear.

[0113] 10 shows a display example in which the display mode selection function 180d receives an instruction from the user via the input device 102 to display three superimposed images with different velocity scales applied to the blood flow region and one superimposed image in which the reddish colors and bluish colors of one of the three superimposed images in which aliasing does not occur are swapped. In this case, the display mode selection function 180d sets a mode in which the four superimposed images are displayed.

[0114] In accordance with the set mode, the control circuit 190 displays four superimposed images 50, 55, 60, and 65 on the display 103 in a 2×2 arrangement, as shown in FIG. 10. In this manner, the control circuit 190 displays on the display 103 a plurality of pieces of blood flow information relating to a plurality of blood flows to which different velocity scales are applied. The superimposed image 60 is an image in which a color image 62 is superimposed on a B-mode image 61. The color image 62 is a color image based on the color image data generated by the processing shown in FIG. 3 by the processing circuitry 180.

[0115] No aliasing occurs in the blood flow 62a, blood flow 62b, and blood flow 62c included in the color image 62. This is because the threshold value X is 0.

[0116] The superimposed image 65 is an image in which a color image 67 is superimposed on a B-mode image 66. The color image 67 is an image in which the reddish and blueish colors of the color image 62 are swapped. That is, the blood flow 67a and the blood flow 62a are the same blood flow, but the blood flow 62a is bluish and the blood flow 67a is reddish. The blood flow 67b and the blood flow 62b are the same blood flow, but the blood flow 62b is reddish and the blood flow 67b is bluish. The blood flow 67c and the blood flow 62c are the same blood flow, but the blood flow 62c is reddish and the blood flow 67c is bluish.

[0117] Here, the user can narrow down the images to be displayed on the display 103 from among the four superimposed images 50, 55, 60, and 65. For example, a case will be described in which the input device 102 is a touch panel. In this case, when the user's hand 70 touches the touch panel on the displayed superimposed images, the superimposed images corresponding to the touched portion of the touch panel are narrowed down as the images to be displayed. The example of FIG. 10 shows a case in which the superimposed images 50 and 60 have been narrowed down as the images to be displayed. In this case, the control circuit 190 may display the superimposed images 50 and 60 side by side on the display 103, as shown in the upper right side of FIG. 10, or may display the superimposed images 50 and 60 side by side on the display 103, as shown in the lower right side of FIG. 10. In this way, the control circuit 190 updates the display 103 so that the specified blood flow information is displayed among the multiple blood flow information displayed on the display 103.

[0118] The above has described the ultrasound diagnostic device 1 according to the first embodiment. The ultrasound diagnostic device 1 according to the first embodiment can present blood flow information in which aliasing is suppressed for each blood flow in a simple manner while suppressing degradation in real-time performance.

[0119] The program executed by the processor is provided in advance in a read-only memory (ROM) or a storage circuit. The program may be provided in a format installable or executable by these devices, recorded on a non-transitory computer-readable storage medium such as a compact disk (CD)-ROM, a flexible disk (FD), a recordable CD-R, or a digital versatile disk (DVD). The program may also be stored on a computer connected to a network such as the Internet and provided or distributed by downloading it via the network. For example, the program may be composed of modules including the above-described processing functions. In actual hardware, a CPU reads and executes the program from a storage medium such as a ROM, whereby each module is loaded into a main memory device and generated on the main memory device.

[0120] According to at least one of the embodiments described above, it is possible to present blood flow information in which aliasing is suppressed for each blood flow in a simple manner while suppressing a decrease in real-time performance.

[0121] Although several embodiments have been described, 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, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, as well as within the scope of the invention and its equivalents as defined in the claims.

[0122] With respect to the above embodiment, the following supplementary notes are disclosed as one aspect and optional features of the invention. (Appendix 1) a collection unit that collects first time series data based on reflected waves of ultrasound transmitted under a single ultrasound condition, the first time series data being composed of data arranged in a time axis direction at a first time interval; a generation unit that generates second time series data consisting of data arranged in a time axis direction at second time intervals based on the first time series data; an application unit that applies, to each of a plurality of blood flows depicted in both the first time series data and the second time series data, a velocity scale based on the first time series data and a second velocity scale based on the second time series data, such that a ratio of blood flows proceeding in a second direction of travel to blood flows proceeding in a first direction of travel is equal to or less than a threshold; a display control unit that displays blood flow information regarding the plurality of blood flows to which the velocity scale is applied on a display unit; An ultrasound diagnostic device comprising: (Appendix 2) The generating unit may generate the second time series data by performing at least one of an interpolation process that interpolates data for the first time series data and a thinning process that thins out data from the time series data. (Appendix 3) The first time-series data may be time-series data based on reflected waves of ultrasound transmitted to the plurality of blood flow-containing regions of the subject; The acquisition unit may acquire the first time-series data based on reflected waves of ultrasound transmitted at a PRF corresponding to the region as the single ultrasound condition. (Appendix 4) The ultrasonic diagnostic apparatus may further include a setting unit that sets, as the single ultrasonic condition, the PRF corresponding to the highest velocity among the plurality of blood flow velocities included in the region. (Appendix 5) The ultrasound diagnostic apparatus may further include a filter processing unit that performs a filter process on the first time-series data and the second time-series data, The application unit may apply, to each of the plurality of blood flows depicted in both the first time-series data and the second time-series data after the filtering process, a velocity scale of the first velocity scale or the second velocity scale, which velocity scale makes the ratio equal to or less than the threshold value; The filtering unit may set the number of ensembles when performing the filtering process to the number of ensembles corresponding to the part. (Appendix 6) The display control unit may cause the display unit to display a plurality of pieces of blood flow information relating to the plurality of blood flows to which different velocity scales are applied. (Appendix 7) The display control unit may update the display on the display unit so that designated blood flow information is displayed from among the plurality of pieces of blood flow information displayed on the display unit. (Appendix 8) The computer A process of generating second time series data consisting of data arranged in a time axis direction at a second time interval based on first time series data based on reflected waves of ultrasound transmitted under a single ultrasound condition, the first time series data being composed of data arranged in a time axis direction at a first time interval; a process of applying, to each of a plurality of blood flows depicted in both the first time series data and the second time series data, a first velocity scale based on the first time series data and a second velocity scale based on the second time series data, such that a ratio of blood flows proceeding in a second direction to blood flows proceeding in a first direction is equal to or less than a threshold; and displaying, on a display unit, blood flow information relating to the plurality of blood flows to which the velocity scale has been applied. [Explanation of symbols]

[0123] 1. Ultrasound diagnostic equipment 180a PRF calculation function 180b data interpolation function 180c scale adjustment function 180d display mode selection function

Claims

1. an acquisition unit that acquires first time series data based on reflected waves of ultrasound transmitted under a single ultrasound condition, the first time series data being composed of data arranged in a time axis direction at a first time interval; a generation unit that generates second time series data consisting of data arranged in a time axis direction at second time intervals based on the first time series data; an application unit that applies, to each of a plurality of blood flows depicted in both the first time series data and the second time series data, a velocity scale based on the first time series data and a second velocity scale based on the second time series data, such that a ratio of the blood flow proceeding in the second direction of travel to the blood flow proceeding in the first direction of travel is equal to or less than a threshold; a display control unit that displays blood flow information regarding the plurality of blood flows to which the velocity scale is applied on a display unit; An ultrasound diagnostic device comprising:

2. the generation unit generates the second time series data by performing at least one of an interpolation process that interpolates data for the first time series data and a thinning process that thins out data from time series data based on the first time series data. The ultrasonic diagnostic apparatus according to claim 1 .

3. the first time-series data is time-series data based on reflected waves of ultrasound transmitted to the plurality of blood flow-containing regions of the subject; The acquisition unit acquires the first time-series data based on reflected waves of ultrasound transmitted at a PRF corresponding to the region as the single ultrasound condition.

3. The ultrasonic diagnostic apparatus according to claim 1.

4. a setting unit that sets the PRF corresponding to the highest velocity among the plurality of blood flow velocities included in the region as the single ultrasound condition; The ultrasonic diagnostic apparatus according to claim 3 , further comprising:

5. a filter processing unit that performs a filter process on the first time series data and the second time series data, the applying unit applies, to each of the plurality of blood flows depicted in both the first time-series data and the second time-series data after the filtering process, a velocity scale of the first velocity scale or the second velocity scale, which velocity scale makes the ratio equal to or less than the threshold value; the filtering processing unit sets the number of ensembles when performing the filtering process to the number of ensembles corresponding to the part.

5. The ultrasonic diagnostic apparatus according to claim 3 or 4.

6. the display control unit causes the display unit to display a plurality of pieces of blood flow information regarding the plurality of blood flows to which different velocity scales are applied.

6. The ultrasonic diagnostic apparatus according to claim 1.

7. the display control unit updates the display on the display unit so that designated blood flow information is displayed among the plurality of blood flow information displayed on the display unit. The ultrasonic diagnostic apparatus according to claim 6.

8. The computer A process of generating second time series data consisting of data arranged in a time axis direction at a second time interval based on first time series data based on reflected waves of ultrasound transmitted under a single ultrasound condition, the first time series data being composed of data arranged in a time axis direction at a first time interval; a process of applying, to each of a plurality of blood flows depicted in both the first time series data and the second time series data, a velocity scale based on the first time series data and a second velocity scale based on the second time series data, such that a ratio of blood flows moving in a second direction to blood flows moving in a first direction is equal to or less than a threshold; and displaying, on a display unit, blood flow information relating to the plurality of blood flows to which the velocity scale has been applied.

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