Ultrasound diagnostic device and image processing device

Abstract

To suppress a decrease in an aliasing velocity when adapting a multidirectional plane wave transmission compound to color Doppler.SOLUTION: An ultrasonic diagnostic device includes an ultrasonic probe, an MTI filter processing unit, and an estimation unit. The ultrasonic probe repeats scanning in which plane waves or diffuse waves are transmitted continuously in the same direction a plurality of times for a plurality of directions. The MTI filter processing part executes processing for applying an MTI filter to a data string of irregular intervals in the same direction acquired by the scanning, and extracting a blood flow signal for each of the plurality of directions. The estimation part executes processing for subjecting the plurality of blood flow signals in the same direction to autocorrelation calculation, and generating an autocorrelation signal for each direction, and estimates a velocity value of the blood flow on the basis of a complex signal generated by subjecting the plurality of autocorrelation signals generated for the plurality of directions to complex addition.SELECTED DRAWING: Figure 5B

Description

[Technical Field]

[0001] The embodiments disclosed in the present specification and drawings relate to an ultrasound diagnostic apparatus and an image processing apparatus. [Background technology]

[0002] A known technique involves beamforming each of multiple received signals obtained by transmitting plane waves in multiple directions and then coherently adding (compounding) the signals at the same position after beamforming. This technique is also called plane wave coherent compounding technique. Note that "coherent addition" is also called "coherent compounding." Another known technique is applying the plane wave coherent compounding technique to color Doppler. This method is also called the "Ultra Fast Doppler method."

[0003] In the "Ultra Fast Doppler method," multiple received signals obtained by transmitting plane waves in multiple directions at a repetition period T (1 / PRF (Pulse Repetition Frequency)), are beamformed, and signals from the same position are coherently added. This process is repeated multiple times. In the following explanation, the number of multiple directions in which plane waves are transmitted is defined as "A." In this case, the period of the coherently compounded signal sequence is AT (A / PRF). Therefore, when the direction in which plane waves are transmitted is one direction, the Doppler aliasing frequency is PRF / 2, but when the period of the compounded signal sequence is AT, it becomes PRF / 2A. As a result, the aliasing frequency is reduced by a factor of 1 / A.

[0004] FIG. 1 is a diagram illustrating an example of conventional coherent compounding. FIG. 1 illustrates a case where A=3. Here, a case where plane waves are transmitted in three directions, a first direction, a second direction B, and a third direction, is illustrated. In the example illustrated in FIG. 1, a received signal 81 obtained by transmitting a plane wave in the first direction, a received signal 82 obtained by transmitting a plane wave in the second direction, and a received signal 83 obtained by transmitting a plane wave in the third direction are coherently added to obtain a signal (added signal, complex signal) 84. Color Doppler processing is performed on this signal 84. That is, a moving target indicator (MTI) filter is applied to the signal 84. This processing is then repeated multiple times. The result of the color Doppler processing is then displayed. The transmission interval of the plane waves is "T," and the transmission interval between two adjacent signals 84 on the time axis is "3T."

[0005] FIG. 2A is a diagram showing an example of a color Doppler display when a plane wave is transmitted in one direction, and FIG. 2B is a diagram showing an example of a color Doppler display when a plane wave is transmitted in three directions as shown in FIG. 1 and coherent compounding is performed.

[0006] In Figure 2A, image 85 shows oncoming blood flow 85a and receding blood flow 85b. Figure 2A shows velocity profile 86a on line segment 86. Positive velocities are the velocities of oncoming blood flow 85a, and negative velocities are the velocities of receding blood flow 85b.

[0007] In Figure 2B, image 87 shows oncoming blood flow 85a and receding blood flow 85b. Figure 2B shows velocity profile 88a on line segment 88. Again, positive velocities are the velocities of oncoming blood flow 85a and negative velocities are the velocities of receding blood flow 85b.

[0008] In Figure 2A, blood flows 85a and 85b are displayed without aliasing, but in Figure 2B, the aliasing speed is reduced to 1 / 3, so they are displayed with double aliasing. This type of aliasing can lead to misidentification of the direction of blood flow and underestimation of blood flow velocity.

[0009] For an ultrasound pulse with a center frequency of 5 MHz and a PRF of 10 kHz, the aliasing velocity of color Doppler signals using the packet method when using standard focused transmission without plane wave coherent compounding is C·PRF / 4f0=1540*10e3 / (4*5e6)=0.77 m / s. When targeting a normal carotid artery, this aliasing velocity results in almost no aliasing. On the other hand, when using multidirectional plane wave coherent compounding with A=5, the aliasing velocity is 1 / 5 of the original velocity, at 0.154 m / s, making aliasing highly likely.

[0010] Note that while the frame rate for normal color Doppler, where the number of transmit rasters is "M," is M / PRF, the frame rate for multidirectional plane-wave coherent compounding is A / PRF. Therefore, for example, when M=100 and A=5, the frame rate for multidirectional plane-wave coherent compounding is 20 times that of normal color Doppler. Therefore, multidirectional plane-wave coherent compounding is extremely useful when users want to observe blood flow at a high frame rate.

[0011] Therefore, when multidirectional plane wave transmission compounding is applied to color Doppler, users desire to improve the aliasing speed to PRF / 2, similar to that of normal color Doppler.

[0012] An example of the simplest method for satisfying this requirement will be described with reference to FIG. 3. FIG. 3 is a diagram illustrating an example of a method for increasing the aliasing rate to PRF / 2. Hereinafter, this method for satisfying the above requirement will be referred to as "Method 1." Method 1, for example, involves transmitting packets multiple times consecutively in the same direction. (a) of FIG. 3 illustrates a scan where A=3 and the number of packets (ensemble number) E=2. For example, ultrasonic transmission 90 is an ultrasonic transmission with a deflection angle of -10°. Ultrasonic transmission 91 is an ultrasonic transmission with a deflection angle of 0°. Ultrasonic transmission 92 is an ultrasonic transmission with a deflection angle of 10°. In Method 1, ultrasonic transmission 90, ultrasonic transmission 91, and ultrasonic transmission 92 are each repeated twice, thereby transmitting ultrasonic waves in three directions. Such scans are then repeatedly performed as shown in FIG. 3.

[0013] A received signal (received data) 90a shown in Fig. 3(b) is a received signal obtained by the first (first) ultrasonic transmission 90 of two consecutive ultrasonic transmissions 90. A received signal 90b shown in Fig. 3(c) is a received signal obtained by the second (second) ultrasonic transmission 90 of two consecutive ultrasonic transmissions 90.

[0014] A received signal 91a shown in (d) of Fig. 3 is a received signal obtained by the first ultrasonic transmission 91 of two consecutive ultrasonic transmissions 91. A received signal 91b shown in (e) of Fig. 3 is a received signal obtained by the second ultrasonic transmission 91 of two consecutive ultrasonic transmissions 91.

[0015] A received signal 92a shown in (f) of Fig. 3 is a received signal obtained by the first ultrasonic transmission 92 of two consecutive ultrasonic transmissions 92. A received signal 92b shown in (g) of Fig. 3 is a received signal obtained by the second ultrasonic transmission 92 of two consecutive ultrasonic transmissions 92.

[0016] In Method 1, an MTI filter is applied to a data sequence (signal sequence) composed of multiple received signals 90a. As a result, the MTI filter suppresses signals (clutter signals) originating from stationary or slow-moving tissues from the data sequence and extracts signals originating from blood flow (blood flow signals). The MTI filter then outputs the blood flow signals.

[0017] For example, the MTI filter extracts a blood flow signal from a data sequence consisting of a plurality of received signals 90a and outputs the extracted blood flow signal 90c. Similarly, in method 1, the MTI filter is applied to a data sequence consisting of a plurality of received signals 90b. As a result, the MTI filter outputs a blood flow signal 90d. The MTI filter is also applied to a data sequence consisting of a plurality of received signals 91a. As a result, the MTI filter outputs a blood flow signal 91c. The MTI filter is also applied to a data sequence consisting of a plurality of received signals 91b. As a result, the MTI filter outputs a blood flow signal 91d. The MTI filter is also applied to a data sequence consisting of a plurality of received signals 92a. As a result, the MTI filter outputs a blood flow signal 92c. The MTI filter is also applied to a data sequence consisting of a plurality of received signals 92b. As a result, the MTI filter outputs a blood flow signal 92d.

[0018] Then, as shown in Figure 3(h), the output of the MTI filter is returned to its original order. Figure 4 shows an example of the frequency characteristics of a data string composed of multiple blood flow signals arranged in Figure 3(h). As shown in Figure 4, the aliasing frequency of each MTI filter is 1 / (12T). However, by arranging multiple blood flow signals as shown in Figure 3(h), the aliasing frequency expands to 1 / (2T), and the MTI filter characteristics become as shown in Figure 4. As can be seen from Figure 4, frequencies where the amplitude characteristic is 0, i.e., blind frequencies, occur. This is undesirable because the accuracy of velocity estimation around the blind frequencies drops significantly. [Prior art documents] [Patent documents]

[0019] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-176997 [Patent Document 2] Japanese Patent Application Laid-Open No. 2016-2379 [Non-patent literature]

[0020] [Non-Patent Document 1] J. Bercoff, G. Montaldo, T. Loupas. D. Savery, F. Meziere, M. Fink, M. Tanter, “Ultrafast Compound Doppler Imaging: Providing Full Blood Flow Characterization”, IEEE Trans. Ultrason. Ferroelectr. Freq. Control,vol. 58, no. 1, pp. 134-147, 2011 Summary of the Invention [Problem to be solved by the invention]

[0021] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to suppress a decrease in aliasing speed when a multidirectional plane wave transmission compound is applied to color Doppler. 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]

[0022] An ultrasound diagnostic apparatus according to an embodiment includes an ultrasound probe, an MTI filter processor, and an estimation unit. The ultrasound probe repeatedly performs scans in multiple directions by continuously transmitting plane waves or diverging waves in the same direction multiple times. The MTI filter processor applies an MTI filter to a data sequence obtained by the scan at unequal intervals in the same direction, and performs processing to extract blood flow signals for each of the multiple directions. The estimation unit performs processing for each direction by performing autocorrelation calculation on the multiple blood flow signals in the same direction to generate an autocorrelation signal, and estimates a blood flow velocity value based on a complex signal generated by complex-adding the multiple autocorrelation signals generated for the multiple directions. [Brief explanation of the drawings]

[0023] [Figure 1] FIG. 1 is a diagram for explaining an example of a conventional coherent compound. [Figure 2A] FIG. 2A is a diagram showing an example of a color Doppler display when a plane wave is transmitted in one direction. [Figure 2B] FIG. 2B is a diagram showing an example of a color Doppler display when plane waves are transmitted in three directions as shown in FIG. 1 and coherent compounding is performed. [Figure 3] FIG. 3 is a diagram for explaining an example of a method for increasing the aliasing rate up to PRF / 2. [Figure 4] FIG. 4 is a diagram showing an example of frequency characteristics of a data string made up of a plurality of blood flow signals arranged in line in FIG. 3(h). [Figure 5A] FIG. 5A is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to the first embodiment. [Figure 5B] FIG. 5B is a diagram for explaining an example of the flow of various information (data, signals, etc.) between the units (circuits, functions, etc.) included in the ultrasound diagnostic apparatus according to the first embodiment. [Figure 6] FIG. 6 is a diagram for explaining an example of processing in which the ultrasound diagnostic apparatus according to the first embodiment estimates a power value of a blood flow. [Figure 7]FIG. 7 is a diagram for explaining an example of processing in which the ultrasound diagnostic apparatus according to the first embodiment estimates a velocity value of a blood flow. [Figure 8A] FIG. 8A is a diagram showing the data string at equal intervals shown in FIG. 3(b). [Figure 8B] FIG. 8B is a diagram showing the data string at unequal intervals shown in FIG. 6(b). [Figure 8C] FIG. 8C is a diagram showing the characteristics of a Butterworth IIR type MTI filter for a data sequence with equal intervals, and the characteristics of an MTI filter obtained by polynomial fitting using the least squares method for a data sequence with uneven intervals. [Figure 9] FIG. 9 is a flowchart showing an example of the flow of processing executed by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 10A] FIG. 10A is a diagram showing an example of a color Doppler display when plane waves are transmitted in three directions as shown in FIG. 1 and coherent compounding is performed. [Figure 10B] FIG. 10B is a diagram showing an example of a color Doppler display obtained by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 11A] FIG. 11A is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus according to the second embodiment. [Figure 11B] FIG. 11B is a diagram for explaining an example of processing executed by the ultrasound diagnostic apparatus according to the second embodiment. [Figure 12] FIG. 12 is a flowchart showing an example of the flow of processing executed by the ultrasound diagnostic apparatus according to the second embodiment. [Figure 13] FIG. 13 is a block diagram showing an example of the configuration of an image processing apparatus according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0024] An ultrasound diagnostic apparatus and an image processing apparatus according to an embodiment will be described below with reference to the drawings. The embodiment may be combined with conventional technology, other embodiments, or other modified examples to the extent that no contradiction occurs. Similarly, the modified examples may be combined with conventional technology, other embodiments, or other modified examples to the extent that no contradiction occurs. In the following description, similar components will be assigned common reference numerals, and duplicated descriptions may be omitted.

[0025] (First embodiment) 5A is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 10 according to the first embodiment. As shown in FIG. 5A, the ultrasound diagnostic apparatus 10 according to the first embodiment includes an apparatus main body 100, an ultrasound probe 101, an input device 102, and a display 103.

[0026] The ultrasonic probe 101 has, for example, a plurality of transducers (piezoelectric elements) 101a (see FIG. 5B described later). These transducers 101a 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, when a voltage (transmission drive voltage) is applied to the transducers 101a by the transmission circuit 111, the transducers 101a generate ultrasonic waves having a waveform corresponding to the transmission drive voltage. The ultrasonic probe 101 also receives reflected waves from the subject P, converts the reflected waves into reflected wave signals, which are electrical signals, and outputs (transmits) the reflected wave signals to the device main body 100. The ultrasonic probe 101 also has, for example, a matching layer provided on the transducers 101a and a backing material that prevents ultrasonic waves from propagating backward from the transducers 101a. The ultrasonic probe 101 is detachably connected to the device main body 100.

[0027] When ultrasonic waves (transmitted ultrasonic waves, ultrasonic pulses) 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 the multiple transducers 101a 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 pulses are reflected by the surface of 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 transmits the reflected wave signals to the receiving circuit 112 of the transmitting / receiving circuit 110, which will be described later.

[0028] 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 a plurality of transducers 101a 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. The mechanical 4D probe is capable of two-dimensional scanning using a plurality of transducers 101a arranged in a row like the 1D array probe, and is also capable of three-dimensional scanning by swinging the plurality of transducers 101a at a predetermined angle (swing angle). The 2D array probe is capable of three-dimensional scanning by using a plurality of transducers 101a arranged in a matrix, and is also capable of two-dimensional scanning by focusing and transmitting ultrasonic waves.

[0029] 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 10 and transfers the received various setting requests to the apparatus main body 100.

[0030] The display 103 displays, for example, a GUI (Graphical User Interface) that allows the operator of the ultrasound diagnostic apparatus 10 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.

[0031] The device main body 100 generates ultrasound image data based on reflected wave 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 reflected wave signals transmitted from the ultrasound probe 101 and 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 reflected wave signals transmitted from the ultrasound probe 101 and corresponding to a three-dimensional region of the subject P. As shown in FIG. 5, the device main body 100 includes a transmission / reception circuit 110, a beamformer 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, and a control circuit 180.

[0032] The transmission / reception circuit 110, under the control of the control circuit 180, 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 multiple reception circuits 112.

[0033] The transmission circuit 111, under the control of the control circuit 180, supplies a drive signal to the ultrasonic probe 101 and causes 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.

[0034] The rate pulser generating circuit, under the control of the control circuit 180, repeatedly generates rate pulses for forming a transmission ultrasound wave (transmission beam) at a predetermined rate frequency (PRF: Pulse Repetition Frequency). The rate pulses pass through a transmission delay circuit, so that a voltage having a different transmission delay time is applied to the transmission pulser. For example, the transmission delay circuit imparts a transmission delay time for each transducer 101a, which is required to focus the ultrasound waves generated from the ultrasound probe 101 into a beam and determine the transmission directivity, to each rate pulse generated by the rate pulser generating circuit. The transmission pulser supplies a drive signal (drive pulse) to the ultrasound probe 101 at a timing based on the rate pulse. The transmission delay circuit arbitrarily adjusts the transmission direction of the ultrasound wave from the transducer surface by changing the transmission delay time imparted to each rate pulse.

[0035] After the drive pulse is transmitted from the transmission pulser via a cable to the transducer 101a in the ultrasonic probe 101, the transducer 101a converts the electrical signal into mechanical vibration. That is, when a voltage is applied to the transducer 101a, the transducer 101a vibrates mechanically. Ultrasound waves generated by this mechanical vibration are transmitted into the living body. Here, the ultrasound waves, which have different transmission delay times for each transducer 101a, are focused and propagated in a predetermined direction.

[0036] 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 180. 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.

[0037] The reflected wave of the ultrasonic wave transmitted by the ultrasonic probe 101 reaches the transducer 101a inside the ultrasonic probe 101, where it is converted from mechanical vibration into an electrical signal (reflected wave signal), and the converted reflected wave signal is input to the receiving circuit 112. That is, an analog reflected wave signal is input to the receiving circuit 112. The receiving circuit 112 has an LNA (Low Noise Amplifier), an ATGC (Analog Time Gain Compensation) processing circuit, an ADC (Analog to Digital Converter), a demodulator, etc., and performs various processes on the reflected wave signal transmitted from the ultrasonic probe 101 to generate a baseband in-phase signal (I signal, I: In-phase) and a quadrature signal (Q signal, Q: Quadrature-phase) as a digital reflected wave signal. The I signal and Q signal are called IQ signals. Then, the receiving circuit 112 transmits the generated IQ signal to the beamformer 120 as a reflected wave signal (received signal).

[0038] In this embodiment, one receiving circuit 112 is provided corresponding to one channel. Here, one channel corresponds to one transducer 101a. Therefore, one receiving circuit 112 is provided corresponding to one transducer 101a. Therefore, the transmission / reception circuit 110 includes a plurality of receiving circuits 112 corresponding to each of the plurality of transducers 101a.

[0039] The beamformer 120 generates reflected wave data by performing beamforming (phased addition) on reflected wave signals transmitted by the multiple receiving circuits 112. The reflected wave signals (IQ signals) and reflected wave data are examples of received signals. The beamformer 120 transmits the generated reflected wave data to the B-mode processing circuit 130 and the Doppler processing circuit 140. The beamformer 120 is realized by, for example, a processor. The beamformer 120 is an example of a beamforming processing unit. Details of the beamformer 120 will be described later.

[0040] The B-mode processing circuit 130 receives the reflected wave data transmitted by the beamformer 120, performs various signal processing on the received reflected wave data, and transmits 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. An example of the various signal processing performed by the B-mode processing circuit 130 will be described below.

[0041] For example, the B-mode processing circuit 130 performs various processes, such as envelope detection and logarithmic compression, on the reflected wave data to generate B-mode data in which the signal strength (amplitude strength) at each sample point is expressed as luminance. For example, the B-mode processing circuit 130 includes an envelope detector and a logarithmic compressor. For example, the envelope detector performs envelope detection on the reflected wave data, and the logarithmic compressor logarithmically compresses data related to the envelope obtained by the envelope detection (e.g., data indicating amplitude). This generates B-mode data. The B-mode processing circuit 130 transmits the generated B-mode data to the image generation circuit 150.

[0042] The B-mode processing circuit 130 also performs signal processing for harmonic imaging, which visualizes harmonic components. Examples of harmonic imaging include CHI and THI. In CHI and THI, a phase modulation (PM) method known as a pulse inversion method is known as a scanning method.

[0043] The Doppler processing circuit 140 receives the reflected wave data transmitted by the beamformer 120, performs various signal processing on the received reflected wave data, and transmits 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. An example of the various types of signal processing performed by the Doppler processing circuit 140 will be described below.

[0044] The Doppler processing circuit 140 performs frequency analysis on the reflected wave data to extract motion information of the 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. as motion information of the moving object across multiple points, and generates Doppler data indicating the extracted motion information of the moving object. The Doppler processing circuit 140 transmits the generated Doppler data to the image generation circuit 150.

[0045] Using the functions of the Doppler processing circuit 140, the ultrasound diagnostic device 10 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 (velocity value), blood flow variance (variance value), and blood flow power (power value), from the blood flow signal. The Doppler processing circuit 140 transmits color image data indicating the blood flow information estimated by the color flow mapping method to the image generation circuit 150. The color image data is an example of Doppler data.

[0046] 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.

[0047] The image generation circuitry 150 generates ultrasound image data from the B-mode data transmitted by the B-mode processing circuitry 130 and the Doppler data transmitted by the Doppler processing circuitry 140. The image generation circuitry 150 is realized by a processor.

[0048] 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 in which motion information or blood flow information is visualized from the two-dimensional Doppler data generated by the Doppler processing circuit 140. The two-dimensional Doppler image data in which motion information is visualized is velocity image data, variance image data, power image data, or image data that is a combination of these.

[0049] 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 transmitted by the B-mode processing circuit 130 or 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 also performs 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. The image generation circuit 150 also combines text information of various parameters, scales, body marks, etc. with the ultrasound image data.

[0050] 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.

[0051] 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.

[0052] 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.

[0053] 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 or the Doppler processing circuit 140. The B-mode data or 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.

[0054] 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.

[0055] The control circuit 180 controls the overall processing of the ultrasound diagnostic apparatus 10. Specifically, the control circuit 180 controls the processing of the transmission / reception circuit 110, the beamformer 120, the B-mode processing circuit 130, the Doppler processing circuit 140, and the image generation circuit 150 based on various setting requests input by the operator via the input device 102 and various control programs and data read from the storage circuitry 170. The control circuit 180 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 180 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 180 also controls the display 103 to display a color image superimposed on the B-mode image. The control circuit 180 is an example of a display control unit or a control unit. The control circuit 180 is realized by, for example, a processor. An ultrasound image is an example of an image.

[0056] Furthermore, the control circuit 180 controls the ultrasonic probe 101 via the transmission / reception circuit 110, thereby controlling ultrasonic scanning.

[0057] The overall configuration of the ultrasound diagnostic device 10 according to the first embodiment has been described above. The ultrasound diagnostic device 10 performs various processes described below to suppress a decrease in aliasing speed when multi-directional plane wave transmission compounding is applied to color Doppler.

[0058] 5A, the Doppler processing circuit 140 has an MTI filter processing function 141, a first coherent compound processing function 142, a second coherent compound processing function 143, an autocorrelation signal calculation function 144, a power estimation function 145, and a velocity estimation function 146. Here, the MTI filter processing function 141 is an example of an MTI filter processing unit. The first coherent compound processing function 142 and the second coherent compound processing function 143 are examples of an adder. The autocorrelation signal calculation function 144, the power estimation function 145, and the velocity estimation function 146 are examples of an estimation unit.

[0059] Here, for example, each of the processing functions of the Doppler processing circuitry 140 shown in FIG. 5A , namely, the MTI filter processing function 141, the first coherent compound processing function 142, the second coherent compound processing function 143, the autocorrelation signal calculation function 144, the power estimation function 145, and the velocity estimation function 146, is recorded in the form of a computer-executable program in a storage device (e.g., storage circuitry 170) of the ultrasound diagnostic apparatus 10. The Doppler processing circuitry 140 is a processor that reads each program from the storage device and executes the read program to realize the corresponding function. In other words, the Doppler processing circuitry 140 in the state in which each program has been read has the functions shown in the Doppler processing circuitry 140 of FIG. 5A . The processing performed by each of the processing functions, namely, the MTI filter processing function 141, the first coherent compound processing function 142, the second coherent compound processing function 143, the autocorrelation signal calculation function 144, the power estimation function 145, and the velocity estimation function 146, will be described later.

[0060] Next, an example of processing executed by the ultrasound diagnostic apparatus 10 will be described. Fig. 5B, Fig. 6, and Fig. 7 are diagrams for explaining an example of processing executed by the ultrasound diagnostic apparatus 10 according to the first embodiment. More specifically, Fig. 5B is a diagram for explaining an example of the flow of various information (data, signals, etc.) between each unit (each circuit, each function, etc.) of the ultrasound diagnostic apparatus 10. Fig. 6 is a diagram for explaining an example of processing executed by the ultrasound diagnostic apparatus 10 to estimate a power value of blood flow. Fig. 7 is a diagram for explaining an example of processing executed by the ultrasound diagnostic apparatus 10 to estimate a velocity value of blood flow.

[0061] In the first embodiment, the processing system downstream of the beamformer 120 is divided into a processing system that generates a B-mode image, a processing system that estimates a blood flow power value, and a processing system that estimates a blood flow velocity value. Therefore, for example, the blood flow power value and the blood flow velocity value are estimated independently. The processing system that generates a B-mode image includes a B-mode processing circuit 130 and an image generation circuit 150. The processing system that estimates the blood flow power value includes an MTI filter processing function 141, a second coherent compound processing function 143, and a power estimation function 145. The processing system that estimates the blood flow velocity value includes an MTI filter processing function 141, an autocorrelation signal calculation function 144, a first coherent compound processing function 142, and a velocity estimation function 146.

[0062] First, an example of the process by which the ultrasound diagnostic device 10 estimates a power value of blood flow will be described with reference to Fig. 5B and Fig. 6. The ultrasound probe 101 operates as follows under the control of the transmission circuitry 111. For example, the ultrasound probe 101 transmits plane waves in A directions (A is a natural number and is plural). The ultrasound probe 101 also transmits plane waves E times (A is a natural number and is plural) consecutively in each direction. The following description will be given assuming that A = 3 and E = 2. That is, the description will be given taking as an example a case in which the ultrasound probe 101 transmits plane waves in three directions and transmits the plane waves twice consecutively in each direction. For example, the ultrasound probe 101 transmits plane waves in three directions: a direction with a deflection angle of -10°, a direction with a deflection angle of 0°, and a direction with a deflection angle of 10°.

[0063] The ultrasonic probe 101 transmits plane waves at a pulse repetition period T (1 / PRF). That is, the transmission interval of the plane waves is the pulse repetition period T.

[0064] The ultrasonic probe 101 transmits plane waves in three directions and repeatedly performs scanning by transmitting the plane waves twice in succession in each direction. That is, the ultrasonic probe 101 repeatedly performs scanning in multiple directions by transmitting plane waves multiple times in succession in the same direction.

[0065] 5B, each of the plurality of receiving circuits 112 is connected to each of the plurality of transducers 101a. Each of the plurality of receiving circuits 112 is also connected to the beamformer 120. Each of the plurality of receiving circuits 112 receives as input a reflected wave signal transmitted from each of the plurality of transducers 101a.

[0066] In this embodiment, the receiving circuitry 112 generates an IQ signal (received signal) based on the reflected wave signal transmitted from the ultrasound probe 101, which is derived from a plane wave transmitted in the direction of a deflection angle of −10°, and transmits the generated IQ signal to the beamformer 120. Hereinafter, such an IQ signal based on the reflected wave signal derived from a plane wave transmitted in the direction of a deflection angle of −10° will be referred to as a “first IQ signal.” Note that since a plane wave is transmitted twice consecutively in the direction of a deflection angle of −10°, the IQ signal based on the reflected wave signal derived from the plane wave transmitted the first time (first time) will be referred to as a “first IQ signal (1),” and the IQ signal based on the reflected wave signal derived from the plane wave transmitted the second time (second time) will be referred to as a “first IQ signal (2).”

[0067] Similarly, the receiving circuit 112 generates an IQ signal based on the reflected wave signal transmitted from the ultrasound probe 101 and derived from a plane wave transmitted in the direction of a deflection angle of 0°, and transmits the generated IQ signal to the beamformer 120. Hereinafter, such an IQ signal based on the reflected wave signal derived from a plane wave transmitted in the direction of a deflection angle of 0° will be referred to as a "second IQ signal." Note that, since a plane wave is transmitted twice consecutively in the direction of a deflection angle of 0°, the IQ signal based on the reflected wave signal derived from the plane wave transmitted the first time will be referred to as a "second IQ signal (1)," and the IQ signal based on the reflected wave signal derived from the plane wave transmitted the second time will be referred to as a "second IQ signal (2)."

[0068] The receiving circuit 112 also generates an IQ signal based on the reflected wave signal transmitted from the ultrasound probe 101, which is derived from a plane wave transmitted in a direction with a deflection angle of 10°, and transmits the generated IQ signal to the beamformer 120. For example, the receiving circuit 112 generates multiple IQ signals by transmitting a plane wave once. Hereinafter, an IQ signal based on such a reflected wave signal derived from a plane wave transmitted in a direction with a deflection angle of 10° will be referred to as a "third IQ signal." Note that, since a plane wave is transmitted twice consecutively in a direction with a deflection angle of 10°, the IQ signal based on the reflected wave signal derived from the plane wave transmitted the first time will be referred to as a "third IQ signal (1)," and the IQ signal based on the reflected wave signal derived from the plane wave transmitted the second time will be referred to as a "third IQ signal (2)."

[0069] 5B, the beamformer 120 is connected to a plurality of receiving circuits 112, a B-mode processing circuit 130, and an MTI filter processing function 141. The beamformer 120 receives as input IQ signals transmitted from each of the plurality of receiving circuits 112.

[0070] The beamformer 120 performs beamforming on the multiple IQ signals transmitted by the multiple receiving circuits 112. For example, the beamformer 120 generates reflected wave data (received signals) 20a shown in FIG. 6 by performing pixel beamforming on the multiple first IQ signals (1), and transmits the reflected wave data 20a to the B-mode processing circuit 130 and the Doppler processing circuit 140.

[0071] Here, an example of pixel beamforming will be described. For example, when transmitting plane waves in multiple directions and performing coherent compounding, it is necessary to obtain beamformed signals at the same point for plane wave transmission in all directions. In this case, it is most efficient to obtain beamforming results at the display position (pixel, picture element). Therefore, in this embodiment, the beamformer 120 beamforms multiple first IQ signals (1) so that multiple signals at the same pixel position in multiple image data for display based on the multiple first IQ signals (1) are added together. In other words, the beamformer 120 beamforms multiple first IQ signals (1) so that signals at the same display position are added together. This generates reflected wave data 20a.

[0072] Similarly, the beamformer 120 performs pixel beamforming on a plurality of first IQ signals (2), a plurality of second IQ signals (1), a plurality of second IQ signals (2), a plurality of third IQ signals (1), and a plurality of third IQ signals (2).

[0073] Reflected wave data 20b is generated by pixel beamforming on a plurality of first IQ signals (2). Reflected wave data 21a is generated by pixel beamforming on a plurality of second IQ signals (1). Reflected wave data 21b is generated by pixel beamforming on a plurality of second IQ signals (2). Reflected wave data 22a is generated by pixel beamforming on a plurality of third IQ signals (1). Reflected wave data 22b is generated by pixel beamforming on a plurality of third IQ signals (2).

[0074] Then, as shown in (a) of Figure 6, the beamformer 120 transmits the reflected wave data 20a, the reflected wave data 20b, the reflected wave data 21a, the reflected wave data 21b, the reflected wave data 22a, and the reflected wave data 22b to the B-mode processing circuitry 130 and the Doppler processing circuitry 140.

[0075] 5B, the B-mode processing circuit 130 is connected to the beamformer 120 and the image generation circuit 150. The reflected wave data 20a, 20b, 21a, 21b, 22a, and 22b transmitted from the beamformer 120 are input to the B-mode processing circuit 130.

[0076] The B-mode processing circuitry 130 generates B-mode data based on the reflected wave data 20a, 20b, 21a, 21b, 22a, and 22b. The B-mode processing circuitry 130 then transmits the generated B-mode data to the image generation circuitry 150.

[0077] 5B, the image generation circuitry 150 is connected to the B-mode processing circuitry 130 and the control circuit 180. The image generation circuitry 150 receives as input B-mode data transmitted from the B-mode processing circuitry 130.

[0078] The image generation circuitry 150 generates B-mode image data based on the B-mode data, and then transmits the generated B-mode image data to the control circuitry 180.

[0079] 5B, the MTI filter processing function 141 of the Doppler processing circuit 140 is connected to the beamformer 120, the second coherent compound processing function 143, and the autocorrelation signal calculation function 144. The MTI filter processing function 141 receives as input the reflected wave data 20a, reflected wave data 20b, reflected wave data 21a, reflected wave data 21b, reflected wave data 22a, and reflected wave data 22b transmitted from the beamformer 120.

[0080] The MTI filter processing function 141 applies an MTI filter to the input data sequence at irregular intervals to obtain an output data sequence at the same irregular intervals as the input. For example, the MTI filter processing function 141 applies an MTI filter to the irregularly spaced data sequence composed of a plurality of reflected wave data 20a and a plurality of reflected wave data 20b shown in FIG. 6(b). As a result, the MTI filter processing function 141 (MTI filter) outputs a blood flow signal 20c corresponding to the reflected wave data 20a to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144, and outputs a blood flow signal 20d corresponding to the reflected wave data 20b to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144. In the first embodiment, the MTI filter processing function 141 applies an MTI filter for each pixel (picture element), and therefore applies the MTI filter as many times as the number of pixels. The MTI filter processing function 141 also applies an MTI filter to the non-uniformly spaced data sequence for each direction in which the plane wave is transmitted, and also applies an MTI filter to the non-uniformly spaced data sequence made up of non-uniformly spaced signals obtained as a result of beamforming by the beamformer 120.

[0081] Here, "unequally spaced data sequence" refers to a data sequence consisting of multiple pieces of reflected wave data at different time intervals, obtained by transmitting ultrasonic waves at various transmission intervals and receiving reflected waves. Note that "equally spaced data sequence" refers to a data sequence consisting of reflected wave data at equal time intervals, obtained by transmitting ultrasonic waves at constant transmission intervals and receiving reflected waves. Furthermore, methods for applying an MTI filter to an unevenly spaced data sequence include known methods such as those described in Patent Document 1 (JP 2005-176997 A) or Patent Document 2 (JP 2016-2379 A). Details of the method for applying an MTI filter to an unevenly spaced data sequence will be described later.

[0082] Here, an example of an unevenly spaced data sequence that is subjected to the MTI filter will be described. For example, the unevenly spaced data sequence may be composed of three pieces of reflected wave data 20a and three pieces of reflected wave data 20b. In such a case, the interval between adjacent pieces of reflected wave data 20a and 20b on the time axis is not constant, but is "T" or "5T."

[0083] Similarly, the MTI filter processing function 141 applies an MTI filter to an unequal-interval data string made up of a plurality of reflected wave data 21a and a plurality of reflected wave data 21b shown in (c) of Fig. 6. As a result, the MTI filter processing function 141 (MTI filter) outputs a blood flow signal 21c corresponding to the reflected wave data 21a to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144, and outputs a blood flow signal 21d corresponding to the reflected wave data 21b to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144.

[0084] Similarly, the MTI filter processing function 141 applies an MTI filter to an unequal-interval data string made up of a plurality of reflected wave data 22a and a plurality of reflected wave data 22b shown in (d) of Fig. 6. As a result, the MTI filter processing function 141 (MTI filter) outputs a blood flow signal 22c corresponding to the reflected wave data 22a to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144, and outputs a blood flow signal 22d corresponding to the reflected wave data 22b to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144.

[0085] As described above, the MTI filter processing function 141 applies an MTI filter to a data sequence at unequal intervals in the same direction obtained by scanning with the ultrasound probe 101, and performs processing to extract blood flow signals for each of the multiple directions. The MTI filter processing function 141 repeatedly performs this processing. Then, every time the MTI filter processing function 141 extracts a blood flow signal, it outputs the extracted blood flow signal to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144.

[0086] 5B, the second coherent compound processing function 143 is connected to the MTI filter processing function 141 and the power estimation function 145. The second coherent compound processing function 143 receives as input the blood flow signals 20c, 20d, 21c, 21d, 22c, and 22d output from the MTI filter processing function 141.

[0087] Then, as shown in (e) of Figure 6, the second coherent compound processing function 143 performs multi-directional plane wave transmission coherent compounding by complex-adding the blood flow signals 20c, 20d, 21c, 21d, 22c, and 22d. That is, the second coherent compound processing function 143 performs complex-adding of A*E=3*2=6 blood flow signals. In this way, the second coherent compound processing function 143 performs multi-directional plane wave transmission coherent compounding to generate the sum signal (complex signal) 23.

[0088] The MTI filter processing function 141 and the second coherent compound processing function 143 then repeatedly perform the above-described processing to repeatedly generate the sum signal 23. In this way, the second coherent compound processing function 143 generates a signal by complex-adding a plurality of blood flow signals extracted in a plurality of directions.

[0089] Then, every time the second coherent compound processing function 143 generates the sum signal 23, it transmits the generated sum signal 23 to the power estimation function 145.

[0090] 5B, the power estimation function 145 is connected to the second coherent compound processing function 143 and the control circuit 180. The power estimation function 145 receives the addition signal 23 transmitted from the second coherent compound processing function 143.

[0091] Then, the power estimation function 145 estimates the power value by calculating the square of the amplitude of the sum signal 23 as the power value of the blood flow. For example, every time the sum signal 23 is generated, the power estimation function 145 estimates the power value from the generated sum signal 23. In this way, the power estimation function 145 estimates the power value of the blood flow based on the signal generated by the second coherent compound processing function 143.

[0092] Then, each time the power estimation function 145 estimates a power value, it transmits the estimated power value to the control circuit 180 .

[0093] Next, an example of the process in which the ultrasound diagnostic apparatus 10 estimates a blood flow velocity value will be described with reference to Fig. 5B and Fig. 7. As shown in Fig. 5B, the autocorrelation signal calculation function 144 is connected to the MTI filter processing function 141 and the first coherent compound processing function 142. The autocorrelation signal calculation function 144 receives as input the blood flow signals 20c, 20d, 21c, 21d, 22c, and 22d output from the MTI filter processing function 141.

[0094] Then, the autocorrelation signal calculation function 144 performs a lag-1 autocorrelation calculation between E (in this case, E=2) blood flow signals in the same direction. That is, the autocorrelation signal calculation function 144 calculates (generates) (E-1) lag-1 autocorrelation signals (autocorrelation values) for each direction. Here, the autocorrelation signal calculation function 144 calculates a lag-1 autocorrelation signal between the two blood flow signals with the shortest interval for each direction. For example, as shown in (a) and (b) of Figure 7, the autocorrelation signal calculation function 144 calculates a lag-1 autocorrelation signal 25 between blood flow signals 20c and 20d. Similarly, as shown in (a) and (c) of Figure 7, the autocorrelation signal calculation function 144 calculates a lag-1 autocorrelation signal 26 between blood flow signals 21c and 21d. 7(a) and 7(d), the autocorrelation signal calculation function 144 calculates an autocorrelation signal 27 between the blood flow signal 22c and the blood flow signal 22d with a lag of 1. That is, the autocorrelation signal calculation function 144 performs an autocorrelation calculation on a plurality of blood flow signals in the same direction to generate an autocorrelation signal for each direction.

[0095] Then, the autocorrelation signal calculation function 144 repeatedly performs the above-mentioned processing to repeatedly calculate the autocorrelation signal 25, the autocorrelation signal 26, and the autocorrelation signal 27. Then, every time the autocorrelation signal calculation function 144 calculates the autocorrelation signal 25, the autocorrelation signal 26, and the autocorrelation signal 27, it transmits the calculated autocorrelation signal 25, the autocorrelation signal 26, and the autocorrelation signal 27 to the first coherent compound processing function 142.

[0096] 5B, the first coherent compound processing function 142 is connected to the autocorrelation signal calculation function 144 and the velocity estimation function 146. The first coherent compound processing function 142 receives as input the autocorrelation signals 25, 26, and 27 transmitted from the autocorrelation signal calculation function 144.

[0097] 7(e) and 7(f), the first coherent compound processing function 142 generates a sum signal (complex signal) 28 by complex-adding three signals, namely, autocorrelation signal 25, autocorrelation signal 26, and autocorrelation signal 27. In this manner, the first coherent compound processing function 142 complex-adds A*(E-1)=3*1=3 autocorrelation signals. In this manner, the first coherent compound processing function 142 generates sum signal 28 by complex-adding the newly generated autocorrelation signals 26 and 27 each time autocorrelation signals 25, autocorrelation signal 26, and autocorrelation signal 27 are newly generated. Therefore, the first coherent compound processing function 142 repeatedly generates sum signal 28.

[0098] Then, every time the first coherent compound processing function 142 generates a summed signal 28 , it sends the generated summed signal 28 to the velocity estimation function 146 .

[0099] 5B, the velocity estimation function 146 is connected to the first coherent compound processing function 142 and the control circuit 180. The velocity estimation function 146 receives the sum signal 28 transmitted from the first coherent compound processing function 142.

[0100] The velocity estimation function 146 estimates the velocity value of the blood flow by calculating the argument from the sum signal 28 to calculate a velocity value normalized between -π and π. For example, the velocity estimation function 146 estimates the velocity value from the generated sum signal 28 every time the sum signal 28 is generated. That is, the velocity estimation function 146 estimates the velocity value of the blood flow based on a complex signal generated by complex-adding a plurality of autocorrelation signals generated for a plurality of directions.

[0101] Then, each time the speed estimation function 146 estimates a speed value, it transmits the estimated speed value to the control circuit 180 .

[0102] 5B, the control circuit 180 is connected to the image generation circuit 150, the power estimation function 145, the velocity estimation function 146, and the display 103. The control circuit 180 receives as input the B-mode image data transmitted from the image generation circuit 150, the power value transmitted from the power estimation function 145, and the velocity value transmitted from the velocity estimation function 146.

[0103] The control circuit 180 controls the display 103 to display a B-mode image based on the B-mode image data, blood flow power values, and blood flow velocity values ​​on the display 103. Here, the control circuit 180 controls the display 103 to display the blood flow velocity values ​​only in locations where the blood flow power values ​​are equal to or greater than a certain value when displaying the blood flow velocity values. The lateral resolution of the blood flow velocity values ​​is not improved by complex addition of values ​​in different transmission directions, but the lateral resolution of the blood flow power values ​​is improved by complex addition of values ​​in different transmission directions. Therefore, by displaying velocity values ​​only in locations where the blood flow power values ​​are equal to or greater than a certain value, it is possible to prevent blood flow velocity values ​​from being displayed in artifact areas such as side lobes.

[0104] In the process shown in FIG. 7, compared to (e) and (f) of FIG. 6, the phase information is converted to a movement amount by autocorrelation, and therefore the phase information of a period T (1 / PRF) is averaged between multidirectional plane wave transmissions. With the conventional coherent compounding shown in FIG. 1, only movement information of a period "A*T" is obtained. On the other hand, according to the first embodiment, movement information of a period T is obtained. As described above, according to the first embodiment, the aliasing speed is improved by A times compared to the conventional coherent compounding shown in FIG. 1. Therefore, according to the first embodiment, it is possible to suppress the decrease in aliasing speed when multidirectional plane wave transmission compounding is applied to color Doppler.

[0105] Fig. 8A is a diagram showing the equally spaced data sequence shown in Fig. 3(b) (a data sequence composed of a plurality of received signals 90a). Fig. 8B is a diagram showing the unequally spaced data sequence shown in Fig. 6(b) (a data sequence composed of a plurality of reflected wave data 20a and a plurality of reflected wave data 20b). Fig. 8C is a diagram showing the characteristics of a Butterworth IIR MTI filter for an equally spaced data sequence, and the characteristics of an MTI filter (an MTI filter generated by the method described in Patent Document 1) obtained by polynomial fitting using the least squares method for an unequally spaced data sequence. Fig. 8C shows a curve 30 indicating the characteristics of a Butterworth IIR MTI filter for an equally spaced data sequence, and a curve 31 indicating the characteristics of an MTI filter obtained by polynomial fitting using the least squares method for an unequally spaced data sequence.

[0106] As shown by curve 30, blind frequencies occur in the evenly spaced data sequence. However, as shown by curve 31, blind frequencies do not occur in the unevenly spaced data sequence, and a clean high-pass filter characteristic is observed even when the normalized frequency axis on the horizontal axis exceeds the Nyquist frequency of 0.5 for a period of 6T (the position 1 / (12T) in Figure 4).

[0107] Furthermore, in general, in normal transmission color Doppler, only about 4 to 16 signals can be used in the data sequence input to the MTI filter. In contrast, in the multidirectional plane wave transmission of the first embodiment, an infinite number of signals (data) can, in principle, be used in the data sequence input to the MTI filter. Therefore, according to the first embodiment, an MTI filter with good characteristics can be generated even for data sequences with uneven intervals.

[0108] Here, we will explain how the MTI filter processing function 141 generates an MTI filter by polynomial fitting using the least squares method for an unevenly spaced data sequence based on the method described in Patent Document 1. The method disclosed in Patent Document 1 performs polynomial fitting on an unevenly spaced data sequence using the least squares method and subtracts it from the original signal. This filter can be calculated in advance as a matrix as shown in Equation 6 of Patent Document 1. Since there are other mathematical expressions for the least squares method, these may also be used. The time column vector a of the unevenly spaced data sequence shown in Figure 8B is expressed by the following Equation (1).

[0109]

number

[0110] However, in formula (1), [] T indicates a transposed matrix. When approximating up to a quadratic polynomial, the matrix A is defined as shown in the following equation (2).

[0111]

number

[0112] Here, "a.^k (k is an integer)" means that each of the elements of the time column vector a is raised to the kth power. If the number of elements of the time column vector a is N (12 in this example), the MTI filter matrix W is expressed by the following equation (3).

[0113]

number

[0114] Therefore, the MTI filter processing function 141 may use equations (1) to (3) to generate the MTI filter matrix W. Note that the characteristics of the MTI filter approximated up to a first-order polynomial are those indicated by the curve 31 shown in FIG. 8C.

[0115] The above method does not seem to directly use the least squares method. However, the above method is a least squares solution using a pseudoinverse matrix. There are several other methods for solving the least squares method besides the above method, so any method that is mathematically equivalent to the above method can be used.

[0116] Next, we will explain how the MTI filter processing function 141 generates an MTI filter by using principal component analysis on an unevenly spaced data sequence based on the method described in Patent Document 2. The method disclosed in Patent Document 2 performs fitting using the higher-order eigenvalues ​​(principal components) of a time-direction covariance matrix averaged in two-dimensional space, and subtracting them from the original signal. This method is the same as the method known as principal component analysis. In Patent Document 2, this is expressed as a filter matrix shown in Equation 5. A method using singular values ​​is mathematically equivalent to this. Other mathematical expressions may also be used.

[0117] Let x be the input data column vector from spatial location i. i Then, the covariance matrix R is calculated using the following equation (4): xx Calculate.

[0118]

number

[0119] In equation (4), x m denotes a column vector of received data at the same position of L transmitted data at different times, H denotes a complex conjugate transpose matrix, and m denotes a sample point in the space from 1 to M.

[0120] R xx Let V be the matrix obtained by eigenvalue decomposing the above and arranging the eigenvectors in descending order of eigenvalue as a column matrix. If we create a matrix S with L rows and L columns, where P elements from the top of the diagonal are 1 and the rest are 0, then VSV His a matrix that approximates the signal with its principal components. If this is considered to be tissue movement (clutter), then the result of subtracting the principal components from the original signal can be considered to be the blood flow signal. Therefore, if T is a diagonal matrix with P elements from the top of the diagonal being 0 and the rest being 1, then the MTI filter matrix W is expressed by the following equation (5).

[0121]

number

[0122] Therefore, the MTI filter processing function 141 may use equations (4) and (5) to generate the MTI filter matrix W. Note that, although the above example has been described using a method of determining eigenvalues ​​and eigenvectors by eigenvalue decomposition, it is also possible to use a method of performing principal component analysis from singular values ​​and singular vectors by singular value decomposition, or other mathematically equivalent methods.

[0123] Fig. 9 is a flowchart showing an example of the flow of processing executed by the ultrasound diagnostic apparatus 10 according to the first embodiment. The processing shown in Fig. 9 is processing for displaying a B-mode image and power and velocity values ​​of blood flow. The processing shown in Fig. 9 is executed every time the ultrasound probe 101 transmits plane waves in A (e.g., 3) directions and performs a scan in which plane waves are transmitted E (e.g., 2) times consecutively in each direction.

[0124] 9, the receiving circuit 112 generates IQ signals (received signals) based on reflected wave signals derived from plane waves transmitted in each direction, and transmits the generated IQ signals to the beamformer 120 (step S101). For example, as described above, the receiving circuit 112 generates a first IQ signal (1), a first IQ signal (2), a second IQ signal (1), a second IQ signal (2), a third IQ signal (1), and a third IQ signal (2).

[0125] The beamformer 120 then performs pixel beamforming on the multiple IQ signals transmitted by the multiple receiving circuits 112, and transmits the reflected wave data generated by pixel beamforming to the B-mode processing circuit 130 and the MTI filter processing function 141 (step S102). For example, in step S102, the beamformer 120 generates reflected wave data 20a, reflected wave data 20b, reflected wave data 21a, reflected wave data 21b, reflected wave data 22a, and reflected wave data 22b. The beamformer 120 then transmits this reflected wave data to the B-mode processing circuit 130 and the MTI filter processing function 141.

[0126] The B-mode processing circuit 130 and the image generation circuit 150 generate B-mode image data based on the reflected wave data transmitted from the beamformer 120, and transmit the generated B-mode image data to the control circuit 180 (step S103). Specifically, in step S103, for example, the B-mode processing circuit 130 generates B-mode data based on the reflected wave data 20a, the reflected wave data 20b, the reflected wave data 21a, the reflected wave data 21b, the reflected wave data 22a, and the reflected wave data 22b. Then, the image generation circuit 150 generates B-mode image data based on the generated B-mode data.

[0127] Furthermore, the MTI filter processing function 141 applies an MTI filter to the data sequence at irregular intervals for each direction in which the plane wave is transmitted to extract blood flow signals, and outputs the extracted blood flow signals to the second coherent compound processing function 143 and the autocorrelation signal calculation function 144 (step S104). In step S104, for example, as described above, the MTI filter outputs blood flow signals 20c, 20d, 21c, 21d, 22c, and 22d.

[0128] Then, the second coherent compound processing function 143 performs multi-directional plane wave transmission coherent compounding by complex-adding the blood flow signals 20c, 20d, 21c, 21d, 22c, and 22d (step S105). This generates a sum signal (complex signal) 23. In step S105, the second coherent compound processing function 143 transmits the generated sum signal 23 to the power estimation function 145.

[0129] Then, the power estimation function 145 estimates the power value of the blood flow by calculating the square of the amplitude of the addition signal 23 as the power value of the blood flow, and transmits the estimated power value to the control circuit 180 (step S106).

[0130] Furthermore, the autocorrelation signal calculation function 144 calculates (E-1) autocorrelation signals with a lag of 1 for each of the same directions, and transmits the calculated autocorrelation signals to the first coherent compound processing function 142 (step S107). For example, in step S107, the autocorrelation signal 25, the autocorrelation signal 26, and the autocorrelation signal 27 are calculated.

[0131] Then, the first coherent compound processing function 142 generates sum signal 28 by complex adding the three signals, autocorrelation signal 25, autocorrelation signal 26, and autocorrelation signal 27 (step S108). In step S108, the first coherent compound processing function 142 transmits the generated sum signal 28 to the velocity estimation function 146.

[0132] Then, the velocity estimation function 146 estimates the velocity value of the blood flow by calculating the deflection angle from the sum signal 28, and calculates a velocity value normalized from -π to π, and transmits the estimated velocity value to the control circuit 180 (step S109).

[0133] Then, the control circuit 180 controls the display 103 to display a B-mode image based on the B-mode image data, the blood flow power value, and the blood flow velocity value on the display 103 (step S110), and ends the processing shown in Figure 9.

[0134] Fig. 10A is a diagram showing an example of a color Doppler display when plane waves are transmitted in three directions and coherent compounding is performed as shown in Fig. 1. Fig. 10B is a diagram showing an example of a color Doppler display obtained by the ultrasound diagnostic apparatus 10 according to the first embodiment.

[0135] In Figure 10A, image 35 shows oncoming blood flow 35a and receding blood flow 35b. Figure 10A shows velocity profile 36a on line segment 36. Positive velocities are the velocities of oncoming blood flow 35a, and negative velocities are the velocities of receding blood flow 35b.

[0136] In Figure 10B, image 37 shows oncoming blood flow 35a and receding blood flow 35b. Figure 10B shows velocity profile 38a on line segment 38. Again, positive velocities are the velocities of oncoming blood flow 35a and negative velocities are the velocities of receding blood flow 35b.

[0137] In Fig. 10A, blood flows 85a and 85b are displayed with double aliasing. On the other hand, in Fig. 10B, blood flows 85a and 85b are displayed without aliasing. This is because the aliasing speed in the first embodiment is three times faster than the aliasing speed when coherent compounding is performed by transmitting plane waves in three directions as shown in Fig. 1. In this way, the aliasing speed is improved by a factor "A," which indicates the number of directions in which the plane waves are transmitted.

[0138] The above has described the first embodiment. According to the first embodiment, as described above, it is possible to suppress a decrease in aliasing speed when a multi-directional plane wave transmission compound is applied to color Doppler.

[0139] (Second embodiment) Next, an ultrasound diagnostic apparatus 10a according to a second embodiment will be described. In the first embodiment, an MTI filter is applied to a signal after beamforming, whereas in the second embodiment, an MTI filter is applied to a signal from each transducer 101a before beamforming. In the following description of the second embodiment, differences from the first embodiment will be mainly described, and a description of the same configuration as the first embodiment may be omitted.

[0140] 11A is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 10a according to the second embodiment. The ultrasound diagnostic apparatus 10a according to the second embodiment differs from the ultrasound diagnostic apparatus 10 according to the first embodiment in that it includes a beamformer 120a and a Doppler processing circuit 140a instead of the beamformer 120 and the Doppler processing circuit 140. In addition, some of the functions of the receiving circuit 112 according to the second embodiment differ from some of the functions of the receiving circuit 112.

[0141] In the first embodiment, the case where the receiving circuitry 112 transmits IQ signals as reflected wave signals to the beamformer 120 has been described. On the other hand, in the second embodiment, the receiving circuitry 112 transmits IQ signals as reflected wave signals to the beamformer 120a and the Doppler processing circuitry 140a. For example, in the second embodiment, the receiving circuitry 112 generates a first IQ signal (1), a first IQ signal (2), a second IQ signal (1), a second IQ signal (2), a third IQ signal (1), and a third IQ signal (2), as in the first embodiment, and transmits these IQ signals to the beamformer 120a and the Doppler processing circuitry 140a.

[0142] The beamformer 120a generates reflected wave data by performing beamforming (phased addition) on a plurality of reflected wave signals transmitted by a plurality of receiving circuits 112. Here, in the above-described first embodiment, a case has been described in which the beamformer 120 transmits the generated reflected wave data to the B-mode processing circuit 130 and the Doppler processing circuit 140. On the other hand, the beamformer 120a according to the second embodiment transmits the generated reflected wave data to the B-mode processing circuit 130. The beamformer 120a is realized by, for example, a processor. The beamformer 120a is an example of a beamforming processing unit.

[0143] 11A, the Doppler processing circuit 140a includes a plurality of MTI filter processing functions 141a, a first coherent compound processing function 142a, a second coherent compound processing function 143a, an autocorrelation signal calculation function 144a, a power estimation function 145a, a velocity estimation function 146a, and a beamforming function 147a. Here, the MTI filter processing function 141a is an example of an MTI filter processing unit. The first coherent compound processing function 142a and the second coherent compound processing function 143a are examples of an adder. The autocorrelation signal calculation function 144a, the power estimation function 145a, and the velocity estimation function 146a are examples of an estimation unit. The beamforming function 147a is an example of a beamforming processing unit.

[0144] Here, for example, the processing functions of the Doppler processing circuitry 140a shown in FIG. 11A, including a plurality of MTI filter processing functions 141a, a first coherent compound processing function 142a, a second coherent compound processing function 143a, an autocorrelation signal calculation function 144a, a power estimation function 145a, a velocity estimation function 146a, and a beamforming function 147a, are recorded in the form of computer-executable programs in a storage device (e.g., storage circuitry 170) of the ultrasound diagnostic apparatus 10a. The Doppler processing circuitry 140a is a processor that reads each program from the storage device and executes the read program to realize the corresponding function. In other words, the Doppler processing circuitry 140a in the state in which each program has been read has the functions shown in the Doppler processing circuitry 140a of FIG. 11A. The processing performed by each of the processing functions, namely, the MTI filter processing function 141a, the first coherent compound processing function 142a, the second coherent compound processing function 143a, the autocorrelation signal calculation function 144a, the power estimation function 145a, the velocity estimation function 146a, and the beamforming function 147a, will be described later.

[0145] Next, an example of processing executed by the ultrasonic diagnostic apparatus 10a will be described. Fig. 11B is a diagram for explaining an example of processing executed by the ultrasonic diagnostic apparatus 10a according to the second embodiment. More specifically, Fig. 11B is a diagram for explaining an example of the flow of various information (data, signals, etc.) between each unit (each circuit, each function, etc.) of the ultrasonic diagnostic apparatus 10a.

[0146] 11B, the beamformer 120a is connected to the multiple receiving circuits 112 and the B-mode processing circuit 130. The beamformer 120a receives multiple IQ signals as multiple reflected wave signals. As described above, the beamformer 120a generates reflected wave data by performing beamforming on the multiple reflected wave signals transmitted by the multiple receiving circuits 112. The beamformer 120a then transmits the generated reflected wave data to the B-mode processing circuit 130.

[0147] 11B, the B-mode processing circuitry 130 is connected to the beamformer 120a and the image generating circuitry 150. The B-mode processing circuitry 130 receives reflected wave data transmitted from the beamformer 120a.

[0148] The B-mode processing circuitry 130 generates B-mode data based on the reflected wave data, and then transmits the generated B-mode data to the image generation circuitry 150.

[0149] The image generation circuit 150 according to the second embodiment is connected to the B-mode processing circuit 130 and the control circuit 180 in the same manner as the image generation circuit 150 according to the first embodiment, and has the same functions as the image generation circuit 150 according to the first embodiment.

[0150] 11B, in the second embodiment, one MTI filter processing function 141a is provided corresponding to one channel. Here, one channel corresponds to one transducer 101a and one receiving circuit 112. Therefore, one MTI filter processing function 141a is provided corresponding to one transducer 101a and one receiving circuit 112. Therefore, the Doppler processing circuit 140a includes a plurality of MTI filter processing functions 141a corresponding to each of the plurality of transducers 101a and each of the plurality of receiving circuits 112.

[0151] 11B, one MTI filter processing function 141a is connected to one receiving circuit 112. Furthermore, one MTI filter processing function 141a is connected to a beamforming function 147a. An IQ signal transmitted from one receiving circuit 112 is input to one MTI filter processing function 141a. This IQ signal is a signal of a plurality of sample points.

[0152] In the second embodiment, the MTI filter processing function 141a applies an MTI filter to a data sequence at irregular intervals that is made up of a plurality of IQ signals (received signals) from the transducer 101a. Note that the plurality of IQ signals that make up the data sequence at irregular intervals are a plurality of IQ signals arranged in time series.

[0153] For example, in a similar manner to the MTI filter processing function 141 according to the first embodiment applying an MTI filter to an irregularly spaced data sequence as shown in FIG. 6 to extract a blood flow signal, the MTI filter processing function 141a according to the second embodiment applies an MTI filter to an irregularly spaced data sequence composed of multiple received signals from the transducer 101a to extract a blood flow signal.

[0154] Then, the MTI filtering function 141a outputs the extracted blood flow signal to the beam forming function 147a. Therefore, the multiple MTI filtering functions 141a shown in Fig. 11B output multiple blood flow signals to the beam forming function 147a.

[0155] 11B, the beamforming function 147a is connected to the multiple MTI filter processing functions 141a, the second coherent compound processing function 143a, and the autocorrelation signal calculation function 144a. The beamforming function 147a receives as input multiple blood flow signals transmitted from the multiple MTI filter processing functions 141a.

[0156] Then, the beamforming function 147a performs pixel beamforming on the multiple blood flow signals. For example, the beamforming function 147a performs pixel beamforming on the multiple blood flow signals in a manner similar to the manner in which the beamformer 120 according to the first embodiment performs pixel beamforming on multiple IQ signals to generate reflected wave data, thereby generating signals after pixel beamforming. These signals after pixel beamforming are signals obtained by pixel beamforming and are also blood flow signals subjected to pixel beamforming. The beamforming function 147a then transmits the generated signals after pixel beamforming to the second coherent compound processing function 143a and the autocorrelation signal calculation function 144a.

[0157] 11B, the second coherent compound processing function 143a is connected to the beamforming function 147a and the power estimation function 145a. The signal after pixel beamforming transmitted from the beamforming function 147a is input to the second coherent compound processing function 143a.

[0158] The second coherent compound processing function 143a generates a sum signal (complex signal) by complex-adding multiple signals after pixel beamforming generated for multiple directions, in a manner similar to the manner in which the second coherent compound processing function 143 according to the first embodiment generates the sum signal 23 by complex-adding multiple blood flow signals extracted for multiple directions. That is, the second coherent compound processing function 143a performs multi-directional plane wave transmission coherent compounding by complex-adding multiple signals after pixel beamforming. Then, the second coherent compound processing function 143a transmits the generated sum signal to the power estimation function 145a.

[0159] 11B, the power estimation function 145a is connected to the second coherent compound processing function 143a and the control circuit 180. The power estimation function 145a receives the addition signal transmitted from the second coherent compound processing function 143a as input.

[0160] Then, the power estimation function 145a estimates the power value of the blood flow using a method similar to the method used by the power estimation function 145 according to the first embodiment to estimate the power value of the blood flow. For example, the power estimation function 145a estimates the power value by calculating the square of the amplitude of the input sum signal as the power value of the blood flow. For example, the power estimation function 145a estimates the power value from the generated sum signal every time a sum signal is generated. In this way, the power estimation function 145a estimates the power value of the blood flow based on the signal generated by the second coherent compound processing function 143a.

[0161] Then, the power estimation function 145a transmits the estimated power value to the control circuit 180 every time it estimates a power value.

[0162] 11B, the autocorrelation signal calculation function 144a is connected to the beamforming function 147a and the first coherent compound processing function 142a. The signal after pixel beamforming transmitted from the beamforming function 147a is input to the autocorrelation signal calculation function 144a.

[0163] The autocorrelation signal calculation function 144a performs a lag-1 autocorrelation calculation between E pixel beamforming signals in the same direction in a manner similar to the manner in which the autocorrelation signal calculation function 144 according to the first embodiment performs a lag-1 autocorrelation calculation between E blood flow signals in the same direction. That is, the autocorrelation signal calculation function 144a calculates (E-1) lag-1 autocorrelation signals for each direction. In this way, the autocorrelation signal calculation function 144a performs a process for each direction in which it performs an autocorrelation calculation on multiple beamforming signals in the same direction to generate an autocorrelation signal.

[0164] Then, every time the autocorrelation signal calculation function 144a generates an autocorrelation signal, it transmits the generated autocorrelation signal to the first coherent compound processing function 142a.

[0165] 11B, the first coherent compound processing function 142a is connected to the autocorrelation signal calculation function 144a and the velocity estimation function 146a. The autocorrelation signal transmitted from the autocorrelation signal calculation function 144a is input to the first coherent compound processing function 142a.

[0166] Then, the first coherent compound processing function 142a performs complex addition on the input (A*(E-1)) autocorrelation signals in the same manner as the first coherent compound processing function 142 according to the first embodiment performs complex addition on the input (A*(E-1)) autocorrelation signals. In this manner, the first coherent compound processing function 142a generates a sum signal by complex adding the input (A*(E-1)) autocorrelation signals.

[0167] Then, every time the first coherent compound processing function 142a generates a summed signal, it sends the generated summed signal to the velocity estimation function 146a.

[0168] 11B, the velocity estimation function 146a is connected to the first coherent compound processing function 142a and the control circuit 180. The velocity estimation function 146a receives the sum signal transmitted from the first coherent compound processing function 142a.

[0169] Then, the velocity estimation function 146a estimates the velocity value of the blood flow using a method similar to the method used by the velocity estimation function 146 according to the first embodiment to estimate the velocity value of the blood flow. For example, the velocity estimation function 146a estimates the velocity value of the blood flow by calculating a velocity value normalized from -π to π by calculating the argument from the input sum signal. For example, the velocity estimation function 146a estimates the velocity value from the generated sum signal every time a sum signal is generated. In this way, the velocity estimation function 146a estimates the velocity value of the blood flow based on the signal generated by the first coherent compound processing function 142a.

[0170] Then, the speed estimation function 146a transmits the estimated speed value to the control circuit 180 each time it estimates a speed value.

[0171] The control circuit 180 according to the second embodiment performs the same processing as the processing performed by the control circuit 180 according to the first embodiment. That is, the control circuit 180 according to the second embodiment controls the display 103 so as to display a B-mode image based on B-mode image data, a blood flow power value, and a blood flow velocity value on the display 103.

[0172] In the first embodiment described above, the MTI filter processing function 141 applies an MTI filter as many times as the number of pixels. On the other hand, in the second embodiment, the multiple MTI filter processing functions 141a apply an MTI filter as many times as (number of transducers 101a × number of sample points). In this way, in the second embodiment, an MTI filter is applied before pixel beamforming, so the amount of calculation required by the multiple MTI filter processing functions 141a is only "(number of elements × number of sample points) / number of pixels" times the amount of calculation required by the MTI filter processing function 141.

[0173] Fig. 12 is a flowchart showing an example of the flow of processing executed by the ultrasound diagnostic apparatus 10a according to the second embodiment. The processing shown in Fig. 12 is processing for displaying a B-mode image and power and velocity values ​​of blood flow. The processing shown in Fig. 12 is executed every time the ultrasound probe 101 transmits plane waves in A (e.g., 3) directions and performs a scan in which plane waves are transmitted E (e.g., 2) times consecutively in each direction.

[0174] As shown in FIG. 12, the receiving circuit 112 generates an IQ signal (received signal) based on the reflected wave signal derived from the plane wave transmitted in each direction, and transmits the generated IQ signal to the beamformer 120 and the MTI filter processing function 141a (step S201).

[0175] Then, the beamformer 120a performs beamforming on the plurality of IQ signals transmitted by the plurality of receiving circuits 112, and transmits reflected wave data generated by the beamforming to the B-mode processing circuit 130 (step S202).

[0176] The B-mode processing circuitry 130 and the image generation circuitry 150 generate B-mode image data based on the reflected wave data transmitted from the beamformer 120a, and transmit the generated B-mode image data to the control circuit 180 (step S203). Specifically, in step S203, for example, the B-mode processing circuitry 130 generates B-mode data based on the reflected wave data. Then, the image generation circuitry 150 generates B-mode image data based on the generated B-mode data, and transmits the generated B-mode image data to the control circuit 180.

[0177] In addition, the MTI filter processing function 141a applies an MTI filter to an unevenly spaced data sequence consisting of multiple received signals from the transducer 101a to extract a blood flow signal, and outputs the extracted blood flow signal to the beamforming function 147a (step S204).

[0178] The beamforming function 147a performs pixel beamforming on the plurality of blood flow signals to generate signals after pixel beamforming (step S205). In step S205, the beamforming function 147a transmits the generated signals after pixel beamforming to the second coherent compound processing function 143a and the autocorrelation signal calculation function 144a.

[0179] Then, the second coherent compounding function 143a performs multi-directional plane wave transmission coherent compounding by complex-adding the signals generated for the multiple directions after pixel beamforming (step S206). This generates a sum signal (complex signal). In step S206, the second coherent compounding function 143a transmits the generated sum signal to the power estimation function 145a.

[0180] Then, the power estimation function 145a estimates the power value of the blood flow by calculating the square of the amplitude of the input addition signal as the power value of the blood flow, and transmits the estimated power value to the control circuit 180 (step S207).

[0181] Furthermore, the autocorrelation signal calculation function 144a calculates (E-1) lag-1 autocorrelation signals for each of the same directions, and transmits the calculated autocorrelation signals to the first coherent compound processing function 142a (step S208).

[0182] Then, the first coherent compound processing function 142a generates a sum signal by complex-adding the input (A*(E-1)) autocorrelation signals (step S209). In step S209, the first coherent compound processing function 142a transmits the generated sum signal to the velocity estimation function 146a.

[0183] Then, the velocity estimation function 146 estimates the velocity value of the blood flow by calculating the argument from the input sum signal, and calculates a velocity value normalized from -π to π, and transmits the estimated velocity value to the control circuit 180 (step S210).

[0184] Then, the control circuit 180 controls the display 103 to display a B-mode image based on the B-mode image data, the blood flow power value, and the blood flow velocity value on the display 103 (step S211), and ends the processing shown in Figure 12.

[0185] The second embodiment has been described above. According to the second embodiment, the same effects as those of the first embodiment can be obtained.

[0186] (Third embodiment) In the first and second embodiments, the ultrasound diagnostic apparatus 10, 10a has been described as executing various processes, but an image processing apparatus may execute processes similar to those executed by the ultrasound diagnostic apparatus 10, 10a. Therefore, such an embodiment will be described as the third embodiment. The description of the third embodiment will mainly focus on differences from the first and second embodiments, and descriptions of configurations similar to those of the first and second embodiments may be omitted.

[0187] 13 is a diagram showing an example of the configuration of an image processing device 200 according to the third embodiment. The image processing device 200 acquires a plurality of reflected wave signal groups (IQ signal groups) from the ultrasound diagnostic device 10, 10a via a network. The reflected wave signal groups here are signal groups consisting of the above-described first IQ signal (1), first IQ signal (2), second IQ signal (1), second IQ signal (2), third IQ signal (1), and third IQ signal (2). The image processing device 200 then performs the same processing as that performed by the ultrasound diagnostic device 10, 10a on the acquired plurality of reflected wave signal groups.

[0188] As shown in FIG. 13, the image processing device 200 includes a network (NW) interface 210, a storage circuit 220, an input interface 230, a display 240, and a processing circuit 250.

[0189] The NW interface 210 controls the transmission and communication of various information and data transmitted and received between the image processing device 200 and the ultrasound diagnostic device 10, 10a. The NW interface 210 is connected to the processing circuitry 250. The NW interface 210 receives a plurality of reflected wave signal groups transmitted by the ultrasound diagnostic device 10, 10a via a network. In this case, the NW interface 210 transmits the received plurality of reflected wave signal groups to the processing circuitry 250. Upon receiving the plurality of reflected wave signal groups, the processing circuitry 250 stores the received plurality of reflected wave signal groups in the storage circuitry 220. For example, the NW interface 210 is realized by a network card, a network adapter, a NIC (Network Interface Controller), or the like.

[0190] The memory circuitry 220 is connected to the processing circuitry 250 and stores various data. For example, the memory circuitry 220 is realized by a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, or an optical disk. The memory circuitry 220 is an example of a memory unit.

[0191] Furthermore, the memory circuitry 220 stores various information used in the processing of the processing circuitry 250, processing results by the processing circuitry 250, etc. For example, the memory circuitry 220 stores a plurality of reflected wave signal groups.

[0192] The input interface 230 is connected to the processing circuitry 250, converts input operations received from an operator into electrical signals, and outputs the signals to the processing circuitry 250. In this specification, the input interface 230 is not limited to an interface equipped with physical operation components such as a mouse and a keyboard. For example, a processing circuit that receives electrical signals corresponding to input operations from an external input device provided separately from the device and outputs the electrical signals to the processing circuitry 250 is also included as an example of an input interface.

[0193] For example, the input interface 230 may be realized by a trackball for making various settings, a switch button, a mouse, a keyboard, a touchpad for performing input operations by touching the operation surface, a touchscreen in which the display screen and touchpad are integrated, a non-contact input interface using an optical sensor, or a voice input interface.

[0194] The display 240 is connected to the processing circuit 250 and displays various information and images output from the processing circuit 250. For example, the display 240 is realized by a liquid crystal monitor, a CRT (Cathode Ray Tube) monitor, or a touch panel. For example, the display 240 displays a GUI (Graphical User Interface) for receiving instructions from an operator, various display images, and various processing results by the processing circuit 250. The display 240 is an example of a display unit.

[0195] The processing circuitry 250 is implemented by a processor and executes a beamforming function 250a, an MTI filter processing function 250b, a first coherent compound processing function 250c, a second coherent compound processing function 250d, an autocorrelation signal calculation function 250e, a power estimation function 250f, a velocity estimation function 250g, a B-mode processing function 250h, an image generation function 250i, and a control function 250j. Here, for example, each of the processing functions of the processing circuitry 250 shown in FIG. 13 , namely, a beamforming function 250a, an MTI filter processing function 250b, a first coherent compound processing function 250c, a second coherent compound processing function 250d, an autocorrelation signal calculation function 250e, a power estimation function 250f, a velocity estimation function 250g, a B-mode processing function 250h, an image generation function 250i, and a control function 250j, is recorded in the storage circuitry 220 in the form of a computer-executable program. The processing circuitry 250 reads each program from the storage circuitry 220 and executes the read program to realize the function corresponding to each program. In other words, the processing circuitry 250 in a state in which each program has been read has each function shown in the processing circuitry 250 of FIG. 13 .

[0196] 13 illustrates a case in which the beamforming function 250a, MTI filter processing function 250b, first coherent compound processing function 250c, second coherent compound processing function 250d, autocorrelation signal calculation function 250e, power estimation function 250f, velocity estimation function 250g, B-mode processing function 250h, image generation function 250i, and control function 250j are implemented by a single processing circuit 250, but the embodiment is not limited to this. For example, the processing circuit 250 may be configured by combining multiple independent processors, and each processor may execute a program to implement each processing function. Furthermore, each processing function of the processing circuit 250 may be implemented by being distributed or integrated as appropriate across a single or multiple processing circuits.

[0197] In the third embodiment, the image processing device 200 performs the same processing as that of the first or second embodiment on a group of reflected wave signals stored in a storage circuitry 220. Note that in the third embodiment, when the image processing device 200 performs processing, the storage circuitry 220 and the display 240 are used instead of the storage circuitry 170 and the display 103 of the first or second embodiment.

[0198] Specifically, the beamforming function 250a has the same function as the beamformer 120 or the beamforming function 147a. The MTI filtering function 250b has the same function as the MTI filtering function 141 or the MTI filtering function 141a. However, if the MTI filtering function 250b has the same function as the MTI filtering function 141a, the number of MTI filtering functions 250b provided in the processing circuit 250 is the same as the number of MTI filtering functions 141a.

[0199] The first coherent compound processing function 250c has functionality similar to that of the first coherent compound processing function 142 or the first coherent compound processing function 142a. The second coherent compound processing function 250d has functionality similar to that of the second coherent compound processing function 143 or the second coherent compound processing function 143a.

[0200] The autocorrelation signal calculation function 250e has the same function as the autocorrelation signal calculation function 144 or the autocorrelation signal calculation function 144a. The power estimation function 250f has the same function as the power estimation function 145 or the power estimation function 145a. The speed estimation function 250g has the same function as the speed estimation function 146 or the speed estimation function 146a.

[0201] The B-mode processing function 250h has the same function as the B-mode processing circuit 130. The image generation function 250i has the same function as the image generation circuit 150.

[0202] The control function 250j has the same functions as the control circuit 180. However, while the control circuit 180 controls the entire ultrasonic diagnostic apparatuses 10 and 10a, the control function 250j controls the entire image processing device 200.

[0203] The beamforming function 250a is an example of a beamforming processing unit. The MTI filter processing function 250b is an example of an MTI filter processing unit. The first coherent compound processing function 250c and the second coherent compound processing function 250d are examples of an addition unit. The autocorrelation signal calculation function 250e, the power estimation function 250f, and the velocity estimation function 250g are examples of an estimation unit.

[0204] The image processing device 200 according to the third embodiment has been described above. According to the third embodiment, the same effects as those of the first or second embodiment can be obtained.

[0205] In the first and second embodiments described above, the ultrasonic probe 101 transmits a plane wave. However, for example, the ultrasonic probe 101 may transmit a diverging wave. The ultrasonic diagnostic apparatus 10, 10a may then perform the same processing as in the first or second embodiment on the received signals obtained by transmitting the diverging wave. Similarly, the image processing apparatus 200 may acquire, from the ultrasonic diagnostic apparatus 10, 10a, a plurality of reflected wave signal groups obtained by transmitting diverging waves. The image processing apparatus 200 may then perform the same processing as in the third embodiment on the plurality of reflected wave signal groups thus acquired.

[0206] The term "processor" used in the above 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 realizes its functions by reading and executing a program stored in the memory circuit 170 or the memory circuit 220. Note that instead of storing a program in the memory circuit 170 or the memory circuit 220, the program may be directly embedded in the processor circuit. In this case, the processor realizes its functions by reading and executing the program embedded in the circuit.

[0207] The program may be provided by being recorded in a computer-readable, non-transitory storage medium such as a CD (Compact Disk)-ROM, a FD (Flexible Disk), a CD-R (Recordable), or a DVD (Digital Versatile Disk) in a computer-installable or executable file format. The program may also be provided or distributed by being stored on a computer connected to a network such as the Internet and downloaded via the network. For example, the program may be composed of modules including the above-described processing functions. In actual hardware, a processor 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.

[0208] According to at least one of the embodiments described above, it is possible to suppress a decrease in the aliasing speed when a multi-directional plane wave transmission compound is applied to color Doppler.

[0209] 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. [Explanation of symbols]

[0210] 10,10a Ultrasound diagnostic equipment 101 Ultrasound probe 141,141a,250b MTI filter processing function 146,146a,250g Speed ​​estimation function

Claims

1. an ultrasonic probe that repeatedly scans in multiple directions by continuously transmitting plane waves or diverging waves in the same direction multiple times; an MTI filter processing unit that applies an MTI filter to a data sequence obtained by the scan at unequal intervals in the same direction, and performs processing to extract blood flow signals for each of the plurality of directions; an estimation unit that performs a process of generating an autocorrelation signal for each direction by performing an autocorrelation calculation on a plurality of blood flow signals in the same direction, and estimates a velocity value of the blood flow based on a complex signal generated by complex-adding the plurality of autocorrelation signals generated for the plurality of directions; An ultrasound diagnostic device comprising:

2. an adder unit that generates a signal by complex-adding the plurality of blood flow signals extracted in the plurality of directions; the estimation unit estimates a power value of the blood flow based on the signal generated by the addition unit; The ultrasonic diagnostic apparatus according to claim 1 .

3. Further provided is a beamforming processing unit that performs beamforming on a plurality of reception signals obtained by transmitting the plane wave or the diverging wave so that signals at the same display position are added together, The MTI filter processing unit applies the MTI filter to the irregularly spaced data sequence constituted by irregularly spaced signals obtained as a result of the beamforming by the beamforming processing unit.

3. The ultrasonic diagnostic apparatus according to claim 1.

4. the MTI filter processing unit applies an MTI filter to the irregularly spaced data sequence composed of a plurality of reception signals output from each of a plurality of transducers of the ultrasound probe at irregular intervals, thereby extracting the blood flow signal for each of the plurality of transducers; a beamforming processing unit that performs beamforming on the plurality of blood flow signals so that signals at the same display position are added together; the estimation unit performs a process of performing an autocorrelation calculation on a plurality of signals obtained by the beamforming in the same direction to generate an autocorrelation signal for each of the directions, and estimates a velocity value of blood flow based on a complex signal generated by complex-adding the plurality of autocorrelation signals generated for the plurality of directions. The ultrasonic diagnostic apparatus according to claim 1 .

5. an MTI filter processing unit that applies an MTI filter to a data sequence at unequal intervals in the same direction obtained by repeatedly performing a scan in multiple directions by continuously transmitting plane waves or diverging waves in the same direction multiple times, and performs a process of extracting blood flow signals for each of the multiple directions; an estimation unit that performs a process of generating an autocorrelation signal for each direction by performing an autocorrelation calculation on a plurality of blood flow signals in the same direction, and estimates a velocity value of the blood flow based on a complex signal generated by complex-adding the plurality of autocorrelation signals generated for the plurality of directions; An image processing device comprising:

Images