JP7613989B2 - Ultrasound diagnostic equipment - Google Patents

Description

The embodiments disclosed in this specification and the drawings relate to an ultrasound diagnostic device.

Conventionally, ultrasound diagnostic devices have the function of generating and displaying blood flow information from reflected ultrasound waves using the Doppler effect. The Doppler information obtained from the reflected waves contains not only blood flow signal components caused by blood flow, but also clutter signal components caused by fixed reflections from the subject's organs and respiratory and pulsatile movements of the organs. For this reason, conventional ultrasound diagnostic devices use a technique for removing clutter signal components from the Doppler information in order to generate accurate blood flow information for the subject. Known techniques for removing clutter signal components include, for example, a technique using a wall filter and a technique using blanking processing (also called "blanking processing").

International Publication No. 2013/153921

One of the problems that the embodiments disclosed in this specification and the drawings attempt to solve is to appropriately remove clutter signal components. However, the problems that the embodiments disclosed in this specification and the drawings attempt to solve 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.

The ultrasound diagnostic device according to the embodiment includes a signal processor. The signal processor generates blood flow information from which clutter signal components have been removed for each sample point based on multiple pieces of Doppler information extracted by applying multiple filter processes having different cutoff values in parallel to the received ultrasound signal.

FIG. 1 is a block diagram showing an example of the configuration of an ultrasonic diagnostic apparatus according to the first embodiment. FIG. 2 is a block diagram showing an example of the configuration of a signal processing circuit according to the first embodiment. FIG. 3 is a flowchart showing an example of a processing procedure of the ultrasonic diagnostic apparatus according to the first embodiment. FIG. 4A is a diagram for explaining processing of the blanking function according to the first embodiment. FIG. 4B is a diagram for explaining the process of the blanking function according to the first embodiment. FIG. 5A is a diagram for explaining processing of the blanking function according to the first embodiment. FIG. 5B is a diagram for explaining the process of the blanking function according to the first embodiment. FIG. 6A is a diagram for explaining the effects of the ultrasound diagnostic apparatus according to the first embodiment. FIG. 6B is a diagram for explaining the effect of the ultrasound diagnostic apparatus according to the first embodiment. FIG. 7A is a diagram for explaining a problem with the second method according to the comparative example. FIG. 7B is a diagram for explaining a problem with the second method according to the comparative example. FIG. 8 is a diagram for explaining a problem with the second method according to the comparative example. FIG. 9 is a flowchart showing an example of a processing procedure of an ultrasound diagnostic apparatus according to a modified example of the first embodiment. FIG. 10 is a diagram for explaining the processing of the signal processing circuit according to the second embodiment. FIG. 11 is a block diagram showing an example of the configuration of a signal processing circuit according to the second embodiment. FIG. 12 is a flowchart showing an example of a processing procedure of the ultrasound diagnostic apparatus according to the second embodiment.

The ultrasound diagnostic device according to the embodiment will be described below with reference to the drawings. Note that the embodiment is not limited to the following embodiment. Furthermore, the contents described in one embodiment can, in principle, be similarly applied to other embodiments.

(First embodiment)
Fig. 1 is a block diagram showing an example of the configuration of an ultrasound diagnostic apparatus 1 according to the first embodiment. As shown in Fig. 1, the ultrasound diagnostic apparatus 1 according to the first embodiment includes an apparatus main body 100, an ultrasound probe 101, an input device 102, and a display 103. The ultrasound probe 101, the input device 102, and the display 103 are communicably connected to the apparatus main body 100. Note that a subject P is not included in the configuration of the ultrasound diagnostic apparatus 1.

The ultrasonic probe 101 transmits and receives ultrasonic waves. For example, the ultrasonic probe 101 has a plurality of piezoelectric transducers. These piezoelectric transducers generate ultrasonic waves based on a drive signal supplied from a transmission/reception circuit 110 of the device main body 100 described later. The plurality of piezoelectric transducers of the ultrasonic probe 101 receive reflected waves from the subject P and convert them into electrical signals. The ultrasonic probe 101 also has a matching layer provided on the piezoelectric transducers, and a backing material that prevents ultrasonic waves from propagating backward from the piezoelectric transducers. The ultrasonic probe 101 is detachably connected to the device main body 100.

When ultrasound waves are transmitted from the ultrasound probe 101 to the subject P, the transmitted ultrasound waves are reflected successively by discontinuous surfaces of acoustic impedance in the tissues of the subject P, and are received as reflected wave signals by the multiple piezoelectric transducers of the ultrasound probe 101. The amplitude of the received reflected wave signal depends on the difference in acoustic impedance at the discontinuous surfaces where the ultrasound waves are reflected. When the transmitted ultrasound pulse is reflected by the surface of a moving blood flow, heart wall, etc., the reflected wave signal undergoes a frequency shift due to the Doppler effect depending on the velocity component of the moving body in the direction of ultrasound transmission.

The ultrasound probe 101 according to the first embodiment can be a 1D array probe that scans the subject P in two dimensions, or a mechanical 4D probe or 2D array probe that scans the subject P in three dimensions.

The input device 102 corresponds to devices such as a mouse, a keyboard, a button, a panel switch, a touch command screen, a foot switch, a trackball, a joystick, etc. The input device 102 accepts various setting requests from the operator of the ultrasound diagnostic device 1 and transfers the accepted various setting requests to the device main body 100.

The display 103 displays a GUI (Graphical User Interface) that enables the operator of the ultrasound diagnostic device 1 to input various setting requests using the input device 102, and displays ultrasound image data generated in the device body 100, etc.

The device body 100 is a device that generates ultrasound image data based on a reflected wave signal received by the ultrasound probe 101. The ultrasound image data generated by the device body 100 shown in FIG. 1 may be two-dimensional ultrasound image data generated based on a two-dimensional reflected wave signal, or three-dimensional ultrasound image data generated based on a three-dimensional reflected wave signal.

As shown in FIG. 1, the device main body 100 includes a transmission/reception circuit 110, a signal processing circuit 120, an image generation circuit 130, an image memory 140, a storage circuit 150, and a processing circuit 160. The transmission/reception circuit 110, the signal processing circuit 120, the image generation circuit 130, the image memory 140, the storage circuit 150, and the processing circuit 160 are connected to each other so as to be able to communicate with each other.

The transmission/reception circuit 110 controls the ultrasonic transmission/reception (ultrasonic scan) performed by the ultrasonic probe 101 based on instructions from the processing circuit 160 described later. The transmission/reception circuit 110 has a pulse generator, a transmission delay circuit, a pulser, etc., and supplies a drive signal to the ultrasonic probe 101. The pulse generator repeatedly generates a rate pulse for forming a transmission ultrasonic wave at a predetermined repetition frequency. The transmission delay circuit also focuses the ultrasonic waves generated from the ultrasonic probe 101 into a beam shape and provides each rate pulse generated by the pulse generator with a delay time for each piezoelectric transducer required to determine the transmission directivity. The pulser also applies a drive signal (drive pulse) to the ultrasonic probe 101 at a timing based on the rate pulse. In other words, the transmission delay circuit arbitrarily adjusts the transmission direction of the ultrasonic waves transmitted from the piezoelectric transducer surface by changing the delay time provided to each rate pulse.

The transmission/reception circuit 110 has the ability to instantly change the transmission frequency, transmission drive voltage, etc., in order to execute a specified scan sequence based on instructions from the processing circuit 160, which will be described later. In particular, the change in transmission drive voltage is achieved by a linear amplifier type transmission circuit that can instantly switch its value, or a mechanism that electrically switches between multiple power supply units.

The transmission/reception circuit 110 also has an amplifier circuit, an A/D (Analog/Digital) converter, a reception delay circuit, an adder, a quadrature detection circuit, etc., and performs various processes on the reflected wave signal received by the ultrasound probe 101 to generate reflected wave data. The amplifier circuit amplifies the reflected wave signal for each channel and performs gain correction processing. The A/D converter A/D converts the gain-corrected reflected wave signal. The reception delay circuit gives the digital data a reception delay time required to determine the reception directivity. The adder performs addition processing of the reflected wave signal to which the reception delay time has been given by the reception delay circuit. The addition processing by the adder emphasizes the reflected component from a direction corresponding to the reception directivity of the reflected wave signal.

The quadrature detection circuit then converts the output signal of the adder into an in-phase signal (I signal, I: In-phase) and a quadrature signal (Q signal, Q: Quadrature-phase) in the baseband. The quadrature detection circuit then transmits the I signal and Q signal (hereinafter referred to as IQ signal) as reflected wave data to the signal processing circuit 120. Note that the quadrature detection circuit may convert the output signal of the adder into an RF (Radio Frequency) signal before transmitting it to the signal processing circuit 120. The IQ signal and RF signal are signals (received signals) that contain phase information. Hereinafter, the reflected wave data output by the transmission/reception circuit 110 may be referred to as a received signal.

The transmission/reception circuit 110 can generate reflected wave data for multiple reception foci from the reflected wave signals of each piezoelectric transducer obtained by transmitting an ultrasonic beam once. In other words, the transmission/reception circuit 110 is a circuit capable of performing parallel simultaneous reception processing. The first embodiment can be applied even when the transmission/reception circuit 110 cannot perform parallel simultaneous reception processing.

The signal processing circuit 120 performs various signal processing on the reflected wave data generated by the transmission/reception circuit 110 from the reflected wave signal. For example, the signal processing circuit 120 includes a buffer that temporarily stores the reflected wave data (IQ signal) generated by the transmission/reception circuit 110. The buffer stores several frames of IQ signals or several volumes of IQ signals. For example, the buffer is a FIFO (First-In/First-Out) memory that stores a predetermined number of frames of IQ signals. Then, for example, when a new frame of IQ signals is generated by the transmission/reception circuit 110, the buffer discards the oldest frame of IQ signals and stores the newly generated frame of I/Q signals. Then, the signal processing circuit 120 performs logarithmic amplification, envelope detection processing, logarithmic compression, etc. on the reflected wave data (IQ signal) read from the buffer to generate data (B-mode information) in which the signal intensity at multiple points is expressed as luminance brightness.

The signal processing circuit 120 can change the detection frequency through filter processing, thereby changing the frequency band to be visualized. By using the filter processing function of the signal processing circuit 120, it is possible to perform harmonic imaging such as contrast harmonic imaging (CHI) and tissue harmonic imaging (THI).

In addition, by using the filter processing function of this signal processing circuit 120, the ultrasound diagnostic device 1 according to the first embodiment can perform tissue harmonic imaging (THI).

When performing harmonic imaging of CHI or THI, the signal processing circuit 120 can extract harmonic components using a method other than the above-mentioned filter processing method. In harmonic imaging, an imaging method called the AMPM method, which is a combination of the amplitude modulation (AM) method, the phase modulation (PM) method, and the AM method and PM method, is performed. In the AM method, the PM method, and the AMPM method, ultrasonic waves with different amplitudes and phases are transmitted multiple times for the same scanning line. As a result, the transmission/reception circuit 110 generates and outputs multiple reflected wave data (received signals) for each scanning line. Then, the signal processing circuit 120 extracts harmonic components by performing addition and subtraction processing on the multiple reflected wave data (received signals) for each scanning line according to the modulation method. Then, the signal processing circuit 120 performs envelope detection processing or the like on the reflected wave data (received signals) of the harmonic components to generate B-mode information.

The signal processing circuit 120 performs frequency analysis on the reflected wave data read from the buffer to generate data (Doppler information) that extracts motion information based on the Doppler effect of a moving object within the scanning range. Specifically, the signal processing circuit 120 generates Doppler information that estimates the average velocity, average variance, average power value, etc., as the motion information of the moving object at each of multiple sample points. Here, the moving object is, for example, blood flow, tissue such as the heart wall, or contrast agent. When generating (extracting) motion information of blood flow (blood flow information), the signal processing circuit 120 performs processing to remove clutter signal components caused by fixed reflections of the subject's organs, respiratory movement of the organs, pulsatile movement, etc., from the Doppler information. The blood flow information is expressed as the average velocity, average variance, and average power value of the blood flow.

Using the above-mentioned function of the signal processing circuit 120, the ultrasound diagnostic device 1 according to this embodiment can perform a color Doppler method, also called a color flow mapping method (CFM). In the CFM method, ultrasonic waves are transmitted and received multiple times on multiple scanning lines. In the CFM method, a moving target indicator (MTI) filter is applied to a data sequence at the same position to suppress signals (clutter signals) originating from stationary tissue or slow-moving tissue and extract signals originating from blood flow. In the CFM method, blood flow information such as the blood flow speed, blood flow dispersion, and blood flow power is estimated from this blood flow signal. The image generation circuit 130, which will be described later, generates ultrasound image data (Doppler image data) that displays the distribution of the estimation results in color, for example, in two dimensions. The display 103 displays the Doppler image data.

As the MTI filter, a Butterworth-type IIR (Infinite Impulse Response) filter, a polynomial regression filter, or other filter with fixed coefficients, or an adaptive MTI filter that changes coefficients according to the input signal can be used. As an adaptive MTI filter, for example, a filter called an "Eigenvector Regression Filter" is used. Hereinafter, the "Eigenvector Regression Filter", which is an adaptive MTI filter that uses eigenvectors, will be referred to as an "Eigenvector-type MTI filter".

The eigenvector-type MTI filter calculates eigenvectors from the correlation matrix, and then calculates the coefficients used in the clutter component suppression process from the calculated eigenvectors. This method is an application of the techniques used in principal component analysis, the Karhunen-Loeve transform, and the eigenspace method.

When using an eigenvector type MTI filter, the signal processing circuit 120 calculates the correlation matrix of the scanning range from a data sequence of consecutive reflected wave data at the same position (same sample point). For example, the signal processing circuit 120 calculates the eigenvalues of the correlation matrix and the eigenvectors corresponding to the eigenvalues. Then, the signal processing circuit 120 calculates a matrix in which the rank of the matrix in which the eigenvectors are arranged based on the magnitude of each eigenvalue is reduced as a filter matrix that suppresses clutter components. Here, the signal processing circuit 120 determines the number of principal components to be reduced, that is, the value of the rank cut number, for example, by a preset value or a value specified by the operator. However, when tissues whose moving speed changes over time due to pulsation, such as the heart and blood vessels, are included within the scanning range, it is preferable that the value of the rank cut number is adaptively determined from the magnitude of the eigenvalue. That is, the signal processing circuit 120 changes the number of principal components to be reduced depending on the magnitude of the eigenvalue of the correlation matrix. In this embodiment, the signal processing circuit 120 changes the number of ranks to be reduced depending on the magnitude of the eigenvalue.

The signal processing circuit 120 uses a filter matrix to suppress clutter components from a data string of consecutive reflected wave data from the same position (same sample point) and outputs a data string in which blood flow signals derived from blood flow are extracted. The signal processing circuit 120 performs calculations such as autocorrelation calculations using the output data to estimate blood flow information and output the estimated blood flow information.

The image generation circuit 130 generates ultrasound image data from the data generated by the signal processing circuit 120. For example, the image generation circuit 130 generates two-dimensional B-mode image data in which the intensity of the reflected wave is expressed as brightness from the two-dimensional B-mode information. The image generation circuit 130 also generates two-dimensional Doppler image data in which blood flow information is visualized from the two-dimensional Doppler information. The two-dimensional Doppler image data is velocity image data, variance image data, power image data, or image data that combines these. The image generation circuit 130 generates color Doppler image data in which blood flow information is displayed in color, or Doppler image data in which one piece of blood flow information is displayed in grayscale, as the Doppler image data.

Here, the image generating circuit 130 generally converts (scan converts) the scan line signal sequence of the 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. Specifically, the image generating circuit 130 generates ultrasound image data for display by performing coordinate conversion according to the ultrasound scanning form of the ultrasound probe 101. In addition to scan conversion, the image generating circuit 130 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 generating circuit 130 also combines text information of various parameters, scales, body marks, etc., with the ultrasound image data.

That is, the B-mode information and Doppler information are ultrasound image data before the scan conversion process, and the data generated by the image generation circuit 130 is ultrasound image data for display after the scan conversion process. Note that the B-mode information and Doppler information are also called raw data. The image generation circuit 130 generates two-dimensional ultrasound image data for display from the two-dimensional ultrasound image data before the scan conversion process.

Furthermore, the image generating circuit 130 generates three-dimensional B-mode image data by performing coordinate transformation on the three-dimensional B-mode information generated by the signal processing circuit 120. Furthermore, the image generating circuit 130 generates three-dimensional Doppler image data by performing coordinate transformation on the three-dimensional Doppler information generated by the signal processing circuit 120.

Furthermore, the image generation circuit 130 performs rendering processing on the volume data to generate various types of two-dimensional image data for displaying the volume data on the display 103. The rendering processing performed by the image generation circuit 130 includes, for example, processing for performing multi-planar reconstruction (MPR) to generate MPR image data from the volume data. The rendering processing performed by the image generation circuit 130 also includes, for example, volume rendering (VR) processing for generating two-dimensional image data reflecting three-dimensional information.

The image memory 140 is a memory that stores image data for display generated by the image generation circuit 130. The image memory 140 can also store the signal processing circuit 120 and data generated by the signal processing circuit 120. The B-mode information and Doppler information stored in the image memory 140 can be called up by the operator after diagnosis, for example, and becomes ultrasound image data for display via the image generation circuit 130. The image memory 140 can also store reflected wave data output by the transmission/reception circuit 110.

The memory circuitry 150 stores various data such as control programs for transmitting and receiving ultrasound, image processing, and display processing, diagnostic information (e.g., patient ID, doctor's findings, etc.), diagnostic protocols, and various body marks. The memory circuitry 150 is also used to store image data stored in the image memory 140 as necessary. The data stored in the memory circuitry 150 can be transferred to an external device via an interface not shown. The memory circuitry 150 can also store data transferred from an external device via an interface not shown.

The processing circuitry 160 controls the overall processing of the ultrasound diagnostic device 1. Specifically, the processing circuitry 160 controls the processing of the transmission/reception circuitry 110, the signal processing circuitry 120, and the image generation circuitry 130 based on various setting requests input by the operator via the input device 102 and various control programs and various data read from the memory circuitry 150. The processing circuitry 160 also controls the display 103 to display ultrasound image data for display stored in the image memory 140 and the memory circuitry 150.

Here, each processing function executed by the processing circuitry 160 is recorded in the memory circuitry 150, for example, in the form of a program executable by a computer. The processing circuitry 160 is a processor that realizes the function corresponding to each program by reading each program from the memory circuitry 150 and executing it.

The term "processor" used in this embodiment means, for example, a circuit such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (for example, a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes its function by reading and executing a program stored in a memory circuit. Note that instead of storing a program in the memory circuit 150, the program may be directly built into the circuit of the processor. In this case, the processor realizes its function by reading and executing a program built into the circuit. Note that each processor in this embodiment is not limited to being configured as a single circuit for each processor, but may be configured as a single processor by combining multiple independent circuits to realize its function. Furthermore, multiple components in each figure may be integrated into a single processor to realize its function.

The ultrasound diagnostic device 1 according to the first embodiment has the processing functions described below in order to appropriately remove clutter signal components. That is, the signal processing circuit 120 generates blood flow information from which clutter signal components have been removed for each sample point based on multiple pieces of Doppler information extracted by applying multiple filter processes having different cutoff values in parallel to the received ultrasound signal. The signal processing circuit 120 is an example of a signal processing unit.

Figure 2 is a block diagram showing an example of the configuration of the signal processing circuit 120 according to the first embodiment. As shown in Figure 2, the signal processing circuit 120 executes wall filter processing functions 121A, 121B, autocorrelation calculation functions 122A, 122B, Doppler information calculation functions 123A, 123B, a blank processing function 124, and a persistence function 125.

The processing functions executed by the wall filter processing functions 121A, 121B, autocorrelation calculation functions 122A, 122B, Doppler information calculation functions 123A, 123B, blank processing function 124, and persistence function 125, which are components of the signal processing circuit 120, are recorded in the memory circuit 150, for example, in the form of a program executable by a computer. The processing circuit 160 is a processor that reads out each program from the memory circuit 150 and executes it to realize the function corresponding to each program. The processing functions executed by the signal processing circuit 120 will be described later in the explanation of FIG. 3.

Figure 3 is a flowchart showing an example of a processing procedure of the ultrasound diagnostic device 1 according to the first embodiment. Each process of steps S101 to S109 shown in Figure 3 is started, for example, when a start instruction to start displaying Doppler image data is received from the operator.

As shown in FIG. 3, the ultrasound diagnostic device 1 executes an ultrasound scan (step S101). For example, the transmission/reception circuitry 110 executes an ultrasound scan on a region of interest set by an operator based on control from the processing circuitry 160. Then, the transmission/reception circuitry 110 generates reflected wave data from each sample point in the region of interest for each frame.

Then, the signal processing circuit 120 applies a high cutoff value filter process A and a low cutoff value filter process B (step S102). The process of step S102 is executed by the wall filter processing functions 121A and 121B.

The wall filter processing functions 121A and 121B perform filter processing on the ultrasonic reception signal (data sequence of reflected wave data) received in time series for each sample point. Here, the wall filter processing function 121A performs filter processing A having a cutoff value A on the data sequence of the reflected wave signal. Also, the wall filter processing function 121B performs filter processing B having a cutoff value B smaller than the cutoff value A on the data sequence of the reflected wave signal. Note that the wall filter processing function 121A is an example of a first filter processing unit. Also, the wall filter processing function 121B is an example of a second filter processing unit. Also, the cutoff value A is an example of a first cutoff value. Also, the cutoff value B is an example of a second cutoff value. Also, the filter processing A is an example of a first filter processing. Also, the filter processing B is an example of a second filter processing. Also, when the wall filter processing functions 121A and 121B are collectively referred to without distinction, they are described as "wall filter processing function 121".

For example, the wall filter processing function 121 applies a high-pass filter (e.g., an IIR filter) as the filter processing. To obtain IIR filter output data (Doppler signal) at a predetermined position (sample point) in the nth frame, the wall filter processing function 121 uses the reflected wave data of the nth frame at the same position, the reflected wave data of the past four frames (frame (n-4) to frame (n-1)), and the IIR filter output data (Doppler signal) of the past four frames. As described above, these reflected wave data are reflected wave data generated by transmitting and receiving ultrasound once for each of the multiple scanning lines that form the scanning range of one frame (first scanning range). Note that the wall filter processing function 121 is not limited to a high-pass filter. For example, the wall filter processing function 121B may apply a band-pass filter.

Then, the signal processing circuit 120 calculates Doppler information A based on the filter processing A and Doppler information B based on the filter processing B (step S103). The process of step S103 is executed by the autocorrelation calculation functions 122A and 122B and the Doppler information calculation functions 123A and 123B.

The autocorrelation calculation functions 122A and 122B calculate the autocorrelation value by taking the complex conjugate of the IQ signal of the Doppler signal of the latest frame and the IQ signal of the Doppler signal of the previous frame. Specifically, the autocorrelation calculation function 122A calculates the autocorrelation value using the Doppler signal output by filter processing A. The autocorrelation calculation function 122B calculates the autocorrelation value using the Doppler signal output by filter processing B. Note that when the autocorrelation calculation functions 122A and 122B are referred to collectively without distinction, they are referred to as "autocorrelation calculation function 122."

The Doppler information calculation functions 123A and 123B calculate Doppler information such as average velocity, average variance, and average power from the autocorrelation values calculated by the autocorrelation calculation function 122. Specifically, the Doppler information calculation function 123A calculates Doppler information A from the autocorrelation values calculated by the autocorrelation calculation function 122A. Furthermore, the Doppler information calculation function 123B calculates Doppler information B from the autocorrelation values calculated by the autocorrelation calculation function 122B. Note that the Doppler information A is an example of first Doppler information. Furthermore, the Doppler information B is an example of second Doppler information.

Then, the signal processing circuit 120 sets a threshold value based on the Doppler information B (step S104). The signal processing circuit 120 then determines whether or not the Doppler information A is less than the threshold value (step S105). If the Doppler information A is less than the threshold value (step S105, Yes), the signal processing circuit 120 adopts approximately zero as the blood flow information (step S106). On the other hand, if the Doppler information A is equal to or greater than the threshold value (step S105, No), the signal processing circuit 120 adopts the Doppler information A as the blood flow information (step S107). Each process from step S104 to step S107 is executed by the blank processing function 124.

The blanking function 124 generates blood flow information by performing blanking processing to partially remove Doppler information B from Doppler information A. For example, the blanking function 124 generates blood flow information from which clutter signal components have been removed, based on the Doppler information A of each sample point extracted by filter processing A and the Doppler information B of each sample point extracted by filter processing B. The blanking function 124 is an example of a blood flow information generating unit.

The processing of the blanking function 124 will now be described with reference to Figures 4A, 4B, 5A, and 5B. Figures 4A to 5B are diagrams for explaining the processing of the blanking function 124 according to the first embodiment. In Figures 4A to 5B, the vertical axis corresponds to the intensity of each signal component included in the Doppler information, and the horizontal axis corresponds to the frequency.

For example, as shown in FIG. 4A, when the blood flow movement is sufficiently large relative to the magnitude of the heart's movement, applying high-pass filter A (filter processing A) with a high cutoff value to the received signal extracts Doppler information of the average velocity "Vel-B1". Furthermore, applying high-pass filter B (filter processing B) with a low cutoff value to the same received signal extracts Doppler information of the average velocity "Vel-C1". Here, "Vel-B1" is a high value because the blood flow signal is dominant. On the other hand, "Vel-C1" is a low value depending on the amount of remaining clutter signal because more clutter signal remains compared to the case of high-pass filter A. As a result, the difference in the velocity values between "Vel-B1" and "Vel-C1" becomes large.

On the other hand, as shown in Figure 4B, when blood flow movement is small relative to the magnitude of cardiac movement, applying high-pass filter A (filter processing A) with a high cutoff value to the received signal extracts Doppler information of average velocity "Vel-B2". Furthermore, applying high-pass filter B (filter processing B) with a low cutoff value to the same received signal extracts Doppler information of average velocity "Vel-C2". Here, clutter signals dominate both "Vel-B2" and "Vel-C2". For this reason, the difference in velocity values between "Vel-B2" and "Vel-C2" is smaller than in the case of Figure 4A.

As such, depending on the magnitude of the blood flow signal relative to the clutter signal, there is a difference in the difference between the two pieces of Doppler information (velocity values) obtained from two wall filters with different cutoff values. Therefore, the blanking processing function 124 uses the difference between these two pieces of Doppler information (velocity values) to generate blood flow information from which the clutter signal components have been appropriately removed.

As a specific example, the blanking function 124 sets a threshold value to be used in blanking based on the Doppler information B. For example, the blanking function 124 sets a threshold value obtained by adding a preset fixed value "α" to the average velocity calculated by the Doppler information calculation function 123B. Then, the blanking function 124 generates blood flow information by threshold processing using the set threshold value.

The fixed value "α" here is a value that can be arbitrarily set by the operator. For example, it is preferable that the fixed value "α" be set in advance for each scan area. It is also preferable that the fixed value "α" is a value that is smaller than the difference in the velocity values between "Vel-B1" and "Vel-C1" (the difference in the velocity values in FIG. 4A) and larger than the difference in the velocity values between "Vel-B2" and "Vel-C2" (the difference in the velocity values in FIG. 4B).

For example, when the blood flow signal is sufficiently large relative to the clutter signal, the blanking function 124 sets the threshold value "TH-1" by adding a fixed value "α" to the average velocity "Vel-C1" corresponding to the Doppler information B in FIG. 4A (FIG. 5A). Here, the fixed value "α" is a value smaller than the difference in the velocity values between "Vel-B1" and "Vel-C1", so the threshold value "TH-1" is smaller than the average velocity "Vel-B1".

On the other hand, when the blood flow signal is small relative to the clutter signal, the blanking function 124 sets the threshold value "TH-2" by adding a fixed value "α" to the average velocity "Vel-C2" corresponding to the Doppler information B in FIG. 4B (FIG. 5B). Here, the fixed value "α" is a value larger than the difference in the velocity values between "Vel-B2" and "Vel-C2", so the threshold value "TH-2" is larger than the average velocity "Vel-B2".

In other words, even if the level of clutter signals or blood flow signals contained in the received signal is unknown, the blanking function 124 uses a threshold value to determine the magnitude of the difference between the two pieces of Doppler information (velocity values) obtained from the two wall filters. As a result, the blanking function 124 can estimate the magnitude of the blood flow signal relative to the clutter signal in the received signal.

That is, the blanking function 124 compares the Doppler information A of each sample point with the threshold value for each frame. Then, when the Doppler information A is less than the threshold value, the blanking function 124 can estimate that the blood flow signal is small relative to the clutter signal, and that most of the components included in the Doppler information are clutter signals. For this reason, the blanking function 124 adopts approximately zero as the blood flow information for sample points where the Doppler information A is less than the threshold value. On the other hand, when the Doppler information A is equal to or greater than the threshold value, the blanking function 124 can estimate that the blood flow signal is large relative to the clutter signal, and that most of the components included in the Doppler information are blood flow signals. For this reason, the blanking function 124 adopts the Doppler information A as the blood flow information for sample points where the Doppler information A is equal to or greater than the threshold value.

In this way, the blanking function 124 generates blood flow information based on a comparison between Doppler information A and a threshold based on Doppler information B. As a result, the blanking function 124 can perform blanking processing with an appropriate threshold set for each sample point for each frame, so that blood flow information from which clutter signal components have been appropriately removed can be generated even for living organisms with large individual differences.

Note that in the explanation of Figures 4A to 5B, the blanking function 124 performs blanking using average velocity as Doppler information, but the embodiment is not limited to this. For example, the blanking function 124 can also perform blanking using an average variance value, average power value, or the like as Doppler information. Furthermore, the blanking function 124 can also perform blanking by combining multiple types of parameters rather than using one type of parameter from the Doppler information. As examples of combinations, four combinations are applicable: average velocity and average variance value, average velocity and average power value, average variance value and average power value, and average velocity, average variance value and average power value.

The blanking process is not limited to the threshold process described above. For example, the blanking process function 124 can also perform differential processing as blanking process. The differential processing will be described later in the modified example.

The phrase "almost zero" does not necessarily mean "zero" and is intended to mean that it may have a small value. For example, when visualized as Doppler image data, any small value that is indistinguishable from zero by the viewer on the image can be used in place of "zero."

Returning to the explanation of FIG. 3, the signal processing circuit 120 executes smoothing processing (step S108). For example, the persistence function 125 applies a filter process to the blood flow information output from the blanking processing function 124 to smooth the blood flow information in the time direction. The persistence function 125 outputs the blood flow information after the smoothing process to, for example, the image generation circuit 130.

Then, the image generation circuit 130 generates Doppler image data (step S109). For example, the image generation circuit 130 performs processing such as scan conversion on the smoothed blood flow information output from the persistence function 125 to generate Doppler image data to which pixel values according to the blood flow information are assigned. The generated Doppler image data is stored in the image memory 140 and, as necessary, is displayed on the display 103 or transferred to an external device connected to the ultrasound diagnostic device 1.

In this way, the ultrasound diagnostic device 1 executes each process from step S101 to step S109 to display the Doppler image data of each frame as a moving image. Then, when the ultrasound diagnostic device 1 receives an end instruction from the operator to end the display of the Doppler image data, it ends the execution of each process from step S101 to step S109.

Note that the order of the processing steps described in FIG. 3 is merely an example, and the processing steps are not necessarily executed in the order shown. For example, the order of the processing steps in FIG. 3 can be changed as desired as long as no inconsistencies occur in the processing content.

As described above, the ultrasound diagnostic device 1 according to the first embodiment generates blood flow information from which clutter signal components have been removed for each sample point, based on multiple pieces of Doppler information extracted by applying multiple filter processes having different cutoff values in parallel to the received ultrasound signal. This enables the ultrasound diagnostic device 1 to appropriately remove the clutter signal components.

The effects of the ultrasound diagnostic device 1 according to the first embodiment will be described using Figures 6A and 6B. Figures 6A and 6B are diagrams for explaining the effects of the ultrasound diagnostic device 1 according to the first embodiment. Figure 6A shows an example of Doppler image data obtained by the ultrasound diagnostic device 1 according to the first embodiment. Also, Figure 6B shows an example of Doppler image data obtained by an ultrasound diagnostic device according to a comparative example to which the first embodiment is not applied.

As shown in Figures 6A and 6B, in the Doppler image data obtained by the ultrasound diagnostic device 1 according to the first embodiment, the coronary artery blood flow is clearly depicted near the center of the region of interest (Figure 6A). In contrast, in the Doppler image data obtained by the ultrasound diagnostic device according to the comparative example, the coronary artery blood flow is not depicted, and only clutter signals are depicted.

Here, we will explain the problems with the comparative example. The following two methods are broadly considered as comparative examples to which the first embodiment is not applied, but in either method, it is difficult to appropriately remove clutter signal components.

The first method is a method of applying two filter processes in sequence. Specifically, in the first method, a low-pass filter is first applied to the Doppler information to actively extract clutter signal components. Then, feedback processing is applied to the original Doppler information as necessary based on the extracted clutter signal components. Then, a high-pass filter is applied to the Doppler information after feedback processing to separate the blood flow signal components and the clutter signal components.

However, in the first method, a low-pass filter and a high-pass filter are applied to the original Doppler information in sequence, so the processing time required for the filter processing is required twice, and the feedback processing also requires a certain amount of processing time. In addition, the coefficients used in the feedback processing must be set empirically, and it is not always possible to apply appropriate coefficients. As such, it is difficult to appropriately remove clutter signal components with the first method.

The second method is a method of performing blanking processing. Specifically, in the second method, the velocity of the Doppler information is compared with a threshold, and any velocity below the threshold is set to approximately zero, thereby removing the clutter signal components.

However, in the second method, a single threshold is applied to all sample points in all frames, so clutter signal components cannot always be removed appropriately. For example, in an imaging environment with large clutter signal components, such as coronary artery blood flow, the clutter signal components cannot always be removed appropriately.

The problems with the second method according to the comparative example will be explained using Figures 7A, 7B, and 8. Figures 7A, 7B, and 8 are diagrams for explaining the problems with the second method according to the comparative example. In Figures 7A, 7B, and 8, the vertical axis corresponds to signal strength, and the horizontal axis corresponds to frequency.

For example, as shown in Figure 7A, when blood flow movement is small relative to the magnitude of cardiac movement, clutter signals become dominant. In this case, when a wall filter (high-pass filter) is applied, the signal components after filtering are also dominated by clutter signals, and the average velocity becomes "Vel-C0". On the other hand, as shown in Figure 7B, when a wall filter is applied when blood flow movement is sufficiently large relative to the magnitude of cardiac movement, the signal components after filtering are dominated by blood flow signals, and the average velocity becomes "Vel-B0".

Here, for example, if the average speed "Vel-C0" is greater than the average speed "Vel-B0", and the average speeds "Vel-C0" and "Vel-B0" are close to each other, the clutter signal components cannot be adequately removed by blanking processing using a single threshold.

For example, as shown in FIG. 8, when the threshold is set to "Th-A," both the blood flow signal and the clutter signal remain even after blanking. When the threshold is set to "Th-B," both the blood flow signal and the clutter signal are removed by blanking. In this way, blanking using a single threshold is unable to adequately remove clutter signal components.

In contrast, the ultrasound diagnostic device 1 according to the first embodiment applies two wall filters having different cutoff values in parallel to the same received signal. Therefore, the ultrasound diagnostic device 1 can apply the wall filters in substantially one processing time.

In addition, the ultrasound diagnostic device 1 sets a threshold value to be used for blanking processing for each frame based on the Doppler information B obtained from the received signal at each sample point. Therefore, the ultrasound diagnostic device 1 can appropriately perform blanking processing for each frame according to the proportion of clutter signals and blood flow signals contained in the received signal at each sample point.

(Modification of the first embodiment)
In the above embodiment, a case where threshold processing is applied as blanking processing has been described, but the embodiment is not limited to this. For example, the blanking function 124 can also execute subtraction processing as blanking processing. That is, the blanking function 124 generates blood flow information based on a subtraction process that subtracts a subtraction value based on Doppler information B from Doppler information A.

Figure 9 is a flowchart showing an example of a processing procedure of the ultrasound diagnostic device 1 according to a modified example of the first embodiment. Each process of steps S201 to S210 shown in Figure 9 is started, for example, when a start instruction to start displaying Doppler image data is received from the operator.

Note that among the processing steps in FIG. 9, steps S201 to S203 are similar to steps S101 to S103 shown in FIG. 3, and therefore their explanations are omitted. Also, steps S209 to S210 are similar to steps S108 to S109 shown in FIG. 3, and therefore their explanations are omitted.

As shown in FIG. 9, the signal processing circuit 120 sets a subtraction value based on Doppler information B (step S204). Then, the signal processing circuit 120 subtracts the subtraction value from Doppler information A (step S205). Then, the signal processing circuit 120 determines whether the value after subtraction is less than zero (step S206). Then, if the value after subtraction is less than zero (step S206, Yes), the signal processing circuit 120 adopts approximately zero as the blood flow information (step S207). On the other hand, if the value after subtraction is equal to or greater than zero (step S206, Yes), the signal processing circuit 120 adopts Doppler information A as the blood flow information (step S208).

For example, the blanking function 124 sets the subtraction value to a value obtained by adding a preset fixed value "α" to the Doppler information B. Note that the fixed value "α" is the same as the fixed value "α" described in the above embodiment, and therefore will not be described here.

Then, the blanking function 124 subtracts the subtraction value from the Doppler information A and determines whether the difference value of the subtraction process is less than zero. For sample points where the difference value of the subtraction process is less than zero, the blanking function 124 adopts approximately zero as the blood flow information. On the other hand, for sample points where the difference value of the subtraction process is zero or greater, the blanking function 124 adopts the Doppler information A as the blood flow information.

In this way, the blanking function 124 generates blood flow information based on a subtraction process that subtracts a subtraction value based on Doppler information B from Doppler information A. This allows the blanking function 124 to perform processing similar to the blanking process using threshold processing described in the above embodiment.

Second Embodiment
In the above embodiment, the process using two wall filters has been described, but the embodiment is not limited to this. For example, the present embodiment can also use three or more wall filters.

The processing of the signal processing circuit 120 according to the second embodiment will be described with reference to FIG. 10. FIG. 10 is a diagram for explaining the processing of the signal processing circuit 120 according to the second embodiment. In FIG. 10, the vertical axis corresponds to the intensity of each signal component included in the Doppler information, and the horizontal axis corresponds to the frequency.

As shown in FIG. 10, there are cases where the clutter signal is not large relative to the blood flow signal. In such cases, the blood flow signal dominates in both Doppler information A obtained by high-pass filter A with a high cutoff value and Doppler information B obtained by high-pass filter B with a low cutoff value ("low cutoff value 1" in FIG. 10). As a result, the difference in velocity value between the average velocity "Vel-B3" of Doppler information A and the average velocity "Vel-C3" of Doppler information B becomes small. For this reason, the blanking process according to the first embodiment may function to remove Doppler information A (to reduce it to approximately zero) even though the blood flow signal is dominant.

Therefore, it is preferable to use a third wall filter in a scan area where the clutter signal is not large relative to the blood flow signal. For example, the signal processing circuit 120 applies a high-pass filter C with a low cutoff value 2, which is smaller than the low cutoff value 1, as the third wall filter. The average velocity "Vel-C4" of the Doppler information C obtained by the high-pass filter C becomes a lower value depending on the clutter signal if the clutter signal is large, but becomes a value similar to the average velocity "Vel-B3" or the average velocity "Vel-C3" if the clutter signal is small. Therefore, the signal processing circuit 120 estimates the ratio of the clutter signal and the blood flow signal contained in the received signal by comparing the average velocity "Vel-C4" with at least one of the average velocity "Vel-B3" and the average velocity "Vel-C3".

Fig. 11 is a block diagram showing an example of the configuration of the signal processing circuit 120 according to the second embodiment. As shown in Fig. 11, the signal processing circuit 120 includes a wall filter processing function 121C, an autocorrelation calculation function 122C, and a Doppler information calculation function 123C in addition to the configuration shown in Fig. 2. Each processing function executed by the signal processing circuit 120 according to the second embodiment will be described later in the explanation of Fig. 12.

Figure 12 is a flowchart showing an example of a processing procedure of the ultrasound diagnostic device 1 according to the second embodiment. Each process of steps S301 to S310 shown in Figure 12 is started, for example, when a start instruction to start displaying Doppler image data is received from the operator.

As shown in FIG. 12, the ultrasound diagnostic device 1 executes an ultrasound scan (step S101). Note that the process of step S301 is similar to the process of step S101 in FIG. 3, and therefore a description thereof will be omitted.

Then, the signal processing circuit 120 applies filter processing A with a high cutoff value, filter processing B with a low cutoff value 1, and filter processing C with a low cutoff value 2 (step S302). The processing of step S302 is executed by the wall filter processing functions 121A, 121B, and 121C. Note that the explanation of the wall filter processing functions 121A and 121B shown in FIG. 11 is the same as the explanation of the wall filter processing functions 121A and 121B shown in FIG. 2, so the explanation will be omitted.

The wall filter processing function 121C executes filter processing C having a cutoff value C smaller than the cutoff value B (the cutoff value of the wall filter processing function 121). The wall filter processing function 121C executes filter processing in parallel with the wall filter processing functions 121A and 121B. Note that the configuration of the wall filter processing function 121C is similar to that of the wall filter processing functions 121A and 121B except for the difference in the cutoff value, and therefore a description thereof will be omitted. Also, the wall filter processing function 121C is an example of a third filter processing unit.

Then, the signal processing circuit 120 calculates Doppler information A based on the filter processing A, Doppler information B based on the filter processing B, and Doppler information C based on the filter processing C (step S303). The process of step S303 is executed by the autocorrelation calculation functions 122A, 122B, and 122C and the Doppler information calculation functions 123A, 123B, and 123C.
The autocorrelation calculation functions 122A, 122B and the Doppler information calculation functions 123A, 123B shown in FIG. 11 are similar to the autocorrelation calculation functions 122A, 122B and the Doppler information calculation functions 123A, 123B shown in FIG. 2, and therefore will not be described again.

The autocorrelation calculation function 122C calculates an autocorrelation value using the Doppler signal output by the filter process C. Note that the configuration of the autocorrelation calculation function 122C is similar to that of the autocorrelation calculation functions 122A and 122B, except for the use of the Doppler signal output by the filter process C, so a description thereof will be omitted.

The Doppler information calculation function 123C calculates Doppler information C from the autocorrelation value calculated by the autocorrelation calculation function 122C. Note that the configuration of the Doppler information calculation function 123C is similar to that of the Doppler information calculation functions 123A and 123B, except for the use of the autocorrelation value calculated by the autocorrelation calculation function 122C, and therefore a description thereof will be omitted. Also, the Doppler information C is an example of third Doppler information.

Then, the signal processing circuit 120 sets a threshold value based on the Doppler information B (step S304). Then, the signal processing circuit 120 judges whether or not the Doppler information A is less than the threshold value (step S305). Then, when the Doppler information A is less than the threshold value (step S305, Yes), the signal processing circuit 120 further judges whether or not the difference between the Doppler information B and the Doppler information C is less than a predetermined value (step S306). Then, when the difference between the Doppler information B and the Doppler information C is equal to or greater than a predetermined value (step S305, Yes), the signal processing circuit 120 adopts approximately zero as the blood flow information (step S306). On the other hand, when the Doppler information A is equal to or greater than the threshold value (step S305, No) and when the difference between the Doppler information B and the Doppler information C is less than a predetermined value (step S306, Yes), the signal processing circuit 120 adopts the Doppler information A as the blood flow information (step S308). Each process from step S304 to step S308 is performed by the blank processing function 124.

For example, the blanking function 124 uses a "predetermined value" to determine the magnitude of the difference between the average speed "Vel-C3" and the average speed "Vel-C4" in FIG. 10. This predetermined value is set so that the magnitude of the clutter signal contained in the received signal can be detected.

The blanking function 124 then compares the Doppler information A of each sample point with a threshold value for each frame. If the Doppler information A is equal to or greater than the threshold value, the blanking function 124 can estimate that the blood flow signal is large relative to the clutter signal, and that most of the components contained in the Doppler information are blood flow signals. For this reason, the blanking function 124 employs the Doppler information A as the blood flow information for sample points where the Doppler information A is equal to or greater than the threshold value.

On the other hand, if Doppler information A is less than the threshold value, blanking function 124 further compares the difference between Doppler information B and Doppler information C with a predetermined value. Then, if the difference between Doppler information B and Doppler information C is less than the predetermined value, blanking function 124 can estimate that the clutter signal is small relative to the blood flow signal and the blood flow signal is dominant, as shown in FIG. 10. Therefore, for sample points where Doppler information A is less than the threshold value and the difference between Doppler information B and Doppler information C is less than the predetermined value, blanking function 124 adopts Doppler information A as the blood flow information.

In addition, when the difference between Doppler information B and Doppler information C is equal to or greater than a predetermined value, the blanking function 124 can estimate that the clutter signal is large relative to the blood flow signal, and that most of the components contained in the Doppler information are clutter signals. For this reason, the blanking function 124 adopts approximately zero as the blood flow information for sample points where Doppler information A is less than the threshold value and the difference between Doppler information B and Doppler information C is equal to or greater than a predetermined value.

In this way, the blanking processing function 124 generates a blood flow signal based on Doppler information A, Doppler information B, and Doppler information C.

Then, the signal processing circuit 120 executes a smoothing process (step S309). Then, the image generating circuit 130 generates Doppler image data (step S310). Note that the processes in steps S309 and S310 are similar to those in steps S108 and S109 shown in FIG. 3, and therefore will not be described.

In this way, the ultrasound diagnostic device 1 according to the second embodiment can generate blood flow information from which clutter signal components have been appropriately removed by using three or more wall filters. This makes it possible for the ultrasound diagnostic device 1 according to the second embodiment to be applied to scan sites where the clutter signal is small relative to the blood flow signal.

Note that the content described in the second embodiment is merely an example, and the embodiment is not limited to this. For example, the modified examples and other variations described in the first embodiment can be similarly applied to the second embodiment.

Other Embodiments
In addition to the above-described embodiment, the present invention may be embodied in various different forms.

The components of each device shown in the figure are conceptual and functional, and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown, and all or part of it can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Furthermore, all or any part of each processing function performed by each device can be realized by a CPU and a program analyzed and executed by the CPU, or can be realized as hardware using wired logic.

Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using known methods. In addition, the information including the processing procedures, control procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified.

The imaging method described in the above embodiment can be realized by executing a prepared imaging program on a computer such as a personal computer or a workstation. This imaging program can be distributed via a network such as the Internet. This ultrasound imaging method can also be recorded on a non-transitory recording medium that can be read by a computer, such as a hard disk, a flexible disk (FD), a CD-ROM, an MO, or a DVD, and executed by being read from the recording medium by a computer.

According to at least one of the embodiments described above, clutter signal components can be appropriately removed.

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, modifications, and combinations of embodiments can be made without departing from the spirit of the invention. These embodiments and their modifications are within the scope of the invention and its equivalents as set forth in the claims, as well as the scope and spirit of the invention.

REFERENCE SIGNS LIST 1 Ultrasound diagnostic device 120 Signal processing circuit 121 Wall filter processing function 122 Autocorrelation calculation function 123 Doppler information calculation function 124 Blank processing function 125 Persistence function

Claims (6)

a signal processing unit that generates blood flow information from which clutter signal components have been removed for each sample point based on a plurality of pieces of Doppler information extracted by applying a plurality of filter processes having mutually different cutoff values in parallel to the received ultrasonic signal ,
The signal processing unit includes:
a first filter processing unit that performs a first filter process having a first cutoff value on the received signal received in time series for each sample point, and outputs first Doppler information for each sample point;
a second filter processing unit that performs a second filter process having a second cutoff value smaller than the first cutoff value on the received signal, and outputs second Doppler information of each sample point;
a blood flow information generating unit that sets a threshold value used for blanking for each sample point based on second Doppler information of the sample point, and generates the blood flow information by comparing the set threshold value with the first Doppler information for each sample point;
An ultrasound diagnostic device comprising : The blood flow information generating unit
generating the blood flow information by performing the blanking process to partially remove the second Doppler information from the first Doppler information;
The ultrasonic diagnostic apparatus according to claim 1 . The blood flow information generating unit
For sample points where the first Doppler information is equal to or greater than the threshold, the first Doppler information is adopted as the blood flow information;
For a sample point where the first Doppler information is less than the threshold, approximately zero is adopted as the blood flow information.
The ultrasonic diagnostic apparatus according to claim 1 . the blood flow information generating unit sets a value obtained by adding a preset fixed value to the second Doppler information as the threshold value;
4. The ultrasonic diagnostic apparatus according to claim 1 . The first filtering unit applies a high-pass filter as the first filtering process,
The second filtering unit applies a high-pass filter or a band-pass filter as the second filtering process.
The ultrasonic diagnostic apparatus according to any one of claims 1 to 4 . The signal processing unit includes:
a first filter processing unit that executes a first filter process having a first cutoff value on a reception signal of an ultrasonic wave received in time series for each sample point;
a second filter processing unit that performs a second filter process on the received signal, the second filter process having a second cutoff value smaller than the first cutoff value;
a third filter processing unit that performs a third filter process on the received signal, the third filter process having a third cutoff value smaller than the second cutoff value;
a blood flow information generating unit that generates blood flow information from which the clutter signal components have been removed, based on first Doppler information of each sample point extracted by the first filtering process, second Doppler information of each sample point extracted by the second filtering process, and third Doppler information of each sample point extracted by the third filtering process.
The ultrasonic diagnostic apparatus according to claim 1 .

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