Ultrasound diagnostic device, image processing device, medical information processing device, ultrasound diagnostic method and program

Abstract

To improve image quality.SOLUTION: An ultrasound diagnostic device according to an embodiment includes an acquisition unit, a first extraction unit, a specification unit, and a generation unit. The acquisition unit acquires first signal data of multiple frames by scanning a subject. The first extraction unit extracts second signal data of multiple frames by extracting signals from the first signal data through nonlinear processing. The specification unit specifies an inappropriate signal point or an inappropriate frame from the second signal data. The generation unit generates third signal data on the basis of specification results of the inappropriate signal point or the inappropriate frame and the second signal data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The embodiments disclosed in this specification and the drawings relate to an ultrasound diagnostic apparatus, a medical information processing apparatus, an image processing apparatus, an ultrasound diagnostic method, and a program. [Background technology]

[0002] As a method for super-resolution of blood flow signals, for example, the SURE (SUper Resolution using Erythrocytes) method as shown in Non-Patent Document 1 is known. This method utilizes the fact that the amplitude distribution characteristics of the speckle patterns of ultrasound images and blood flow images follow a Rayleigh distribution. In other words, by using the SURE method to integrate high-brightness signals that occur with a low probability for each frame according to the Rayleigh distribution, it is possible to obtain blood flow signals with higher resolution than conventional power Doppler methods.

[0003] However, in the process of extracting high-brightness signals that occur with a low probability according to a Rayleigh distribution for each frame, there is a possibility that signals other than blood flow signals, such as residual tissue signals such as clutter and motion artifacts, may be mistakenly picked up. In this case, signals from clutter may be distributed around the blood flow, reducing the visibility of the blood flow. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Jorgen Arendt Jensen et al., “Fast super resolution ultrasound imaging using the erythrocytes,” Proc. SPIE 12038, Medical Imaging 2022: Ultrasonic Imaging and Tomography,120380E, April 4, 2022 Summary of the Invention [Problem to be solved by the invention]

[0005] One of the problems to be solved by the embodiments disclosed in this specification and the drawings is to improve image quality. 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 later can also be positioned as other problems. [Means for solving the problem]

[0006] An ultrasound diagnostic apparatus according to an embodiment includes an acquisition unit, a first extraction unit, an identification unit, and a generation unit. The acquisition unit acquires a plurality of frames of first signal data by scanning a subject. The first extraction unit extracts a plurality of frames of second signal data by extracting a signal whose signal value corresponds to a local maximum value or a predetermined range from the first signal data. The identification unit identifies an inappropriate signal point or an inappropriate frame from the second signal data. The generation unit generates third signal data based on the identification result of the inappropriate signal point or the inappropriate frame and the second signal data. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an ultrasonic diagnostic apparatus according to the first embodiment. [Diagram 2] FIG. 2 is a flowchart illustrating an example of the flow of processing performed by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 3A] FIG. 3A is a diagram illustrating the processing performed by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 3B] FIG. 3B is a diagram illustrating the processing performed by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 4] FIG. 4 is a diagram illustrating the processing performed by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 5A]FIG. 5A is a diagram showing an example of an ultrasound image in the comparison method. [Figure 5B] FIG. 5B is a diagram showing an example of an ultrasound image output by the ultrasound diagnostic apparatus according to the first embodiment. [Figure 6] FIG. 6 is a flowchart illustrating an example of the flow of processing performed by the ultrasound diagnostic apparatus according to the second embodiment. [Figure 7] FIG. 7 is a diagram illustrating the processing performed by the ultrasound diagnostic apparatus according to the second embodiment. [Figure 8A] FIG. 8A is a diagram showing an example of an ultrasound image in the comparison method. [Figure 8B] FIG. 8B is a diagram showing an example of an ultrasound image captured by the ultrasound diagnostic apparatus according to the second embodiment. [Figure 9] FIG. 9 is a diagram showing an example of the configuration of an ultrasonic diagnostic apparatus according to the third embodiment. [Figure 10] FIG. 10 is a diagram illustrating details of the image generating function 111 according to the third embodiment. [Figure 11] FIG. 11 is a diagram illustrating the background according to the third embodiment. [Figure 12] FIG. 12 is a flowchart showing the flow of processing performed by the medical image processing apparatus according to the third embodiment. [Figure 13A] FIG. 13A is a diagram illustrating processing performed by the medical image processing apparatus according to the third embodiment. [Figure 13B] FIG. 13B is a diagram illustrating the processing performed by the medical image processing device according to the comparative example. [Figure 13C] FIG. 13C is a diagram illustrating the processing performed by the medical image processing apparatus according to the third embodiment. [Figure 14] FIG. 14 is a diagram illustrating an example of processing performed by the medical image processing apparatus according to the third embodiment. [Figure 15] FIG. 15 is a flowchart showing the flow of processing performed by a medical image processing apparatus according to a modified example of the third embodiment. [Figure 16A]FIG. 16A is an example of an ultrasound image generated by a medical information processing device according to a first comparative example. [Figure 16B] FIG. 16B is an example of an ultrasound image generated by a medical information processing device according to a second comparative example. [Figure 16C] FIG. 16C is an example of an ultrasound image generated by the medical information processing device according to the embodiment. [Figure 17A] FIG. 17A is an example of an ultrasound image generated by a medical information processing device according to a first comparative example. [Figure 17B] FIG. 17B is an example of an ultrasound image generated by a medical information processing device according to a second comparative example. [Figure 17C] FIG. 17C is an example of an ultrasound image generated by the medical information processing device according to the embodiment. [Figure 18] FIG. 18 is a diagram illustrating another embodiment. [Figure 19] FIG. 19 is a diagram illustrating details of the image generating function 111 according to the fourth embodiment. [Figure 20] FIG. 20 is a flowchart showing the flow of processing performed by the medical image processing apparatus according to the fourth embodiment. [Figure 21] FIG. 21 is a flowchart illustrating the process of step S400 in FIG. 20 in more detail. [Figure 22] FIG. 22 is a diagram illustrating the processing performed by the medical image processing apparatus according to the fourth embodiment. [Diagram 23] FIG. 23 is a diagram illustrating the processing performed by a medical image processing apparatus according to a comparative example. [Figure 24] FIG. 24 is a diagram illustrating the processing performed by the medical image processing apparatus according to the fourth embodiment. [Diagram 25] FIG. 25 is a diagram illustrating an example of an image output by a medical image processing device according to a comparative example. [Figure 26] FIG. 26 is a diagram illustrating an example of an image output by a medical image processing apparatus according to a comparative example. [Figure 27]FIG. 27 is a diagram illustrating an example of an image output by the medical image processing apparatus according to the fourth embodiment. [Figure 28] FIG. 28 is a flowchart showing the flow of processing performed by a medical image processing apparatus according to a modified example of the fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] (First embodiment) Hereinafter, embodiments of an ultrasound diagnostic apparatus, an image processing apparatus, and an ultrasound diagnostic method will be described in detail with reference to the drawings.

[0009] First, the configuration of an ultrasonic diagnostic apparatus according to the first embodiment will be described. Fig. 1 is a block diagram showing an example of the configuration of an ultrasonic diagnostic apparatus according to the first embodiment. As shown in Fig. 1, the ultrasonic diagnostic apparatus according to the first embodiment includes an ultrasonic probe 5 and an ultrasonic diagnostic apparatus 10. The ultrasonic diagnostic apparatus 10 includes a transmission circuit 9, a reception circuit 11, and a medical image processing apparatus 100.

[0010] The ultrasonic probe 5 has a plurality of piezoelectric transducers, which generate ultrasonic waves based on a drive signal supplied from a transmission circuit 9 of the ultrasonic diagnostic device 10 described later. The plurality of piezoelectric transducers of the ultrasonic probe 5 receive reflected waves from the subject P and convert them into electrical signals (reflected wave signals). The ultrasonic probe 5 also has a matching layer provided on the piezoelectric transducers, a backing material that prevents ultrasonic waves from propagating backward from the piezoelectric transducers, and the like. The ultrasonic probe 5 is detachably connected to the ultrasonic diagnostic device 10.

[0011] When ultrasonic waves are transmitted from the ultrasonic probe 5 to the subject P, the transmitted ultrasonic waves are successively reflected by discontinuous surfaces of acoustic impedance in the internal tissues of the subject P, and are received as reflected waves by a plurality of piezoelectric transducers of the ultrasonic probe 5, and converted into reflected wave signals. The amplitude of the reflected wave signal depends on the difference in acoustic impedance at the discontinuous surfaces where the ultrasonic waves are reflected. When the transmitted ultrasonic pulse is reflected by the surface of a moving blood flow, heart wall, or the like, the reflected wave signal undergoes a frequency shift due to the Doppler effect depending on the velocity component of the moving body in the ultrasonic transmission direction.

[0012] The embodiment is applicable whether the ultrasonic probe 5 is a 1D array probe that scans the subject P two-dimensionally, or a mechanical 4D probe or a 2D array probe that scans the subject P three-dimensionally.

[0013] The ultrasonic diagnostic device 10 is a device that generates ultrasonic image data based on a reflected wave signal received from the ultrasonic probe 5. The ultrasonic diagnostic device 10 shown in Fig. 1 is a device that can generate two-dimensional ultrasonic image data based on a two-dimensional reflected wave signal, and can generate three-dimensional ultrasonic image data based on a three-dimensional reflected wave signal. However, the embodiment is also applicable to cases where the ultrasonic diagnostic device 10 is a device dedicated to two-dimensional data.

[0014] As shown in FIG. 1, the ultrasound diagnostic apparatus 10 includes a transmission circuit 9, a reception circuit 11, and a medical image processing apparatus 100.

[0015] The transmission circuit 9 and the reception circuit 11 control the ultrasonic transmission and reception performed by the ultrasonic probe 5 based on instructions from a processing circuit 110 having a control function (not shown). The transmission circuit 9 has a pulse generator, a transmission delay unit, a pulser, etc., and supplies a drive signal to the ultrasonic probe 5. The pulse generator repeatedly generates a rate pulse for forming a transmission ultrasonic wave at a predetermined pulse repetition frequency (PRF: Pulse Repetition Frequency). In addition, the transmission delay unit focuses the ultrasonic waves generated from the ultrasonic probe 5 into a beam shape and provides a delay time for each piezoelectric transducer required to determine the transmission directivity to each rate pulse generated by the pulse generator. In addition, the pulser applies a drive signal (drive pulse) to the ultrasonic probe 5 at a timing based on the rate pulse.

[0016] That is, the transmission delay unit arbitrarily adjusts the transmission direction of the ultrasonic waves transmitted from the piezoelectric transducer surface by changing the delay time given to each rate pulse. Also, the transmission delay unit controls the position of the focal point (transmission focus) in the depth direction of the ultrasonic transmission by changing the delay time given to each rate pulse.

[0017] The transmission circuit 9 has a function of instantaneously changing the transmission frequency, transmission drive voltage, etc., in order to execute a predetermined scan sequence based on instructions from the processing circuit 110 described later. In particular, the change in the transmission drive voltage is realized by a linear amplifier type oscillation circuit that can instantaneously switch its value, or a mechanism that electrically switches between multiple power supply units.

[0018] The receiving circuit 11 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 from the ultrasonic probe 5 to generate a received signal (reflected wave data). The amplifier circuit amplifies the reflected wave signal for each channel and performs a gain correction process. The A / D converter A / D converts the gain-corrected reflected wave signal. The reception delay circuit provides the digital data with a reception delay time required to determine the reception directivity. The adder performs an addition process of the reflected wave signal to which the reception delay time has been provided by the reception delay circuit. The addition process of the adder emphasizes the reflected component from the direction according to the reception directivity of the reflected wave signal. Then, the quadrature detection circuit 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) of the baseband. Then, the quadrature detection circuit transmits the I signal and the Q signal (hereinafter referred to as IQ signal) to the processing circuit 110 as a received signal (reflected wave data). The quadrature detection circuit may convert the output signal of the adder into an RF (Radio Frequency) signal and transmit it to the processing circuit 110. The IQ signal and the RF signal become received signals having phase information.

[0019] When scanning a two-dimensional region in the subject P, the transmission circuit 9 causes the ultrasonic probe 5 to transmit an ultrasonic beam for scanning the two-dimensional region. Then, the reception circuit 11 generates a two-dimensional reception signal from the two-dimensional reflected wave signal received from the ultrasonic probe 5. When scanning a three-dimensional region in the subject P, the transmission circuit 9 causes the ultrasonic probe 5 to transmit an ultrasonic beam for scanning the three-dimensional region. Then, the reception circuit 11 generates a three-dimensional reception signal from the three-dimensional reflected wave signal received from the ultrasonic probe 5. The reception circuit 11 generates a reception signal based on the reflected wave signal, and transmits the generated reception signal to the processing circuit 110.

[0020] The transmission circuit 9 causes the ultrasonic probe 5 to transmit an ultrasonic beam from a predetermined transmission position (transmission scanning line). The reception circuit 11 receives a signal due to a reflected wave of the ultrasonic beam transmitted by the transmission circuit 9 from the ultrasonic probe 5 at a predetermined reception position (reception scanning line). When parallel simultaneous reception is not performed, the transmission scanning line and the reception scanning line are the same scanning line. On the other hand, when parallel simultaneous reception is performed, when the transmission circuit 9 causes the ultrasonic probe 5 to transmit one ultrasonic beam on one transmission scanning line, the reception circuit 11 simultaneously receives the signal due to the reflected wave originating from the ultrasonic beam transmitted by the transmission circuit 9 to the ultrasonic probe 5 as multiple reception beams at multiple predetermined reception positions (reception scanning lines) through the ultrasonic probe 5.

[0021] The medical image processing device 100 is connected to a transmission circuit 9 and a reception circuit 11, and processes signals received from the reception circuit 11 and controls the transmission circuit 9. The medical image processing device 100 includes a processing circuit 110, a memory 132, an input device 134, and a display 135. The processing circuit 110 has a B-mode processing function 110a, a Doppler processing function 110b, a display control function 110c, a reception function 110d, a generation function 110e, an acquisition function 110f, a first extraction function 110g, and a specification function 110h.

[0022] In the embodiment, each processing function and learned model performed by the B-mode processing function 110a, the Doppler processing function 110b, the display control function 110c, the reception function 110d, the generation function 110e, the acquisition function 110f, the first extraction function 110g, and the identification function 110h are stored in the memory 132 in the form of a program executable by a computer. The processing circuit 110 is a processor that realizes the function corresponding to each program by reading the program from the memory 132 and executing it. In other words, the processing circuit 110 in a state in which each program has been read has each function shown in the processing circuit 110 in FIG. 1. Note that, in FIG. 1, the processing circuit 110 is described as being realized by a single processing circuit, but the processing circuit 110 may be configured by combining multiple independent processors, and each processor may realize the function by executing a program. In other words, each of the above-mentioned functions may be configured as a program, and one processing circuit may execute each program. In addition, two or more functions of the functions of the processing circuit 110 may be realized by a single processing circuit. As another example, certain functions may be implemented in dedicated, separate program execution circuitry.

[0023] In addition, in Figure 1, the B-mode processing function 110a, the Doppler processing function 110b, the display control function 110c, the reception function 110d, the generation function 110e, the acquisition function 110f, the first extraction function 110g, and the identification function 110h are examples of the B-mode processing unit, the Doppler processing function, the display control function 110c, the reception function 110d, the generation function 110e, the acquisition function 110f, the first extraction function 110g, and the identification function 110h, respectively.

[0024] The term "processor" used in the above description means a circuit such as a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), an Application Specific Integrated Circuit (ASIC), a programmable logic device (e.g., a Simple Programmable Logic Device (SPLD), a Complex Programmable Logic Device (CPLD), and a Field Programmable Gate Array (FPGA)). The processor realizes functions by reading and executing a program stored in memory 132.

[0025] Also, the program may be directly embedded in the circuitry of the processor instead of storing the program in the memory 132. In this case, the processor realizes the function by reading and executing the program embedded in the circuitry.

[0026] The transmission circuit 9, reception circuit 11, etc. built into the ultrasound diagnostic device 10 may be configured as hardware such as an integrated circuit, but may also be configured as a modularized program in software form.

[0027] The processing circuit 110 receives data from the receiving circuit 11 using the B-mode processing function 110a, and performs logarithmic amplification processing, envelope detection processing, logarithmic compression processing, etc. to generate data (B-mode data) in which the signal intensity is expressed as brightness (luminance).

[0028] In addition, the processing circuit 110 uses the Doppler processing function 110b to perform frequency analysis of velocity information from the received signal (reflected wave data) received from the receiving circuit 11, and generates data (Doppler data) extracted from multiple points of moving object information such as velocity, dispersion, power, etc. due to the Doppler effect.

[0029] It should be noted that the B-mode processing function 110a and the Doppler processing function 110b illustrated in FIG. 1 are capable of processing both two-dimensional reflected wave data and three-dimensional reflected wave data.

[0030] The processing circuitry 110 controls the display control function 110c so that the ultrasonic image data for display stored in the memory 132 is displayed on the display 135.

[0031] The processing circuit 110 receives various operations from the user via the input device 134 using the reception function 110d.

[0032] The processing circuit 110 generates ultrasound image data from the data generated by the B-mode processing function 110a and the Doppler processing function 110b using the generation function 110e. The processing circuit 110 generates two-dimensional B-mode image data, which expresses the intensity of the reflected wave as brightness, from the two-dimensional B-mode data generated by the B-mode processing function 110a using the generation function 110e. The processing circuit 110 also generates two-dimensional Doppler image data, which expresses moving object information, from the two-dimensional Doppler data generated by the Doppler processing function 110b using the generation function 110e. The two-dimensional Doppler image data is velocity image data, variance image data, power image data, or image data that is a combination of these.

[0033] Moreover, the processing circuit 110 converts (scan converts) the scan line signal sequence of the ultrasonic scan into a scan line signal sequence of a video format represented by a television or the like, using the generation function 110e, and generates ultrasonic image data for display. Furthermore, the processing circuit 110 performs various image processing other than scan conversion, such as image processing (smoothing processing) for regenerating an average brightness image using multiple image frames after scan conversion, and image processing (edge ​​enhancement processing) using a differential filter within an image, using the generation function 110e. Furthermore, the processing circuit 110 performs various rendering processing on the volume data to generate two-dimensional image data for displaying the volume data on the display 135, using the generation function 110e.

[0034] The processing circuitry 110 also controls the overall processing of the ultrasonic diagnostic apparatus using a control function (not shown). Specifically, the processing circuitry 110 controls the processing of the transmission circuitry 9, the reception circuitry 11, and the processing circuitry 110 using the control function based on various setting requests input by an operator via the input device 134 and various control programs and various data read from the memory 132.

[0035] The processing circuit 110 also has an acquisition function 110f, a first extraction function 110g, and a specification function 110h. Each of these functions will be described in detail later.

[0036] The memory 132 is composed of a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc. The memory 132 is a memory that stores data such as image data for display generated by the processing circuit 110. The memory 132 can also store data generated in the B-mode processing function 110a and the Doppler processing function 110b. The B-mode data and Doppler data stored in the memory 132 can be called up by an operator after diagnosis, for example, and become ultrasonic image data for display via the processing circuit 110. The memory 132 can also store a reception signal (reflected wave data) output by the receiving circuit 11.

[0037] In addition, the memory 132 stores, as necessary, control programs for performing ultrasound transmission and reception, 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.

[0038] The input device 134 receives various instructions and information input from an operator. The input device 134 is, for example, a pointing device such as a mouse or a trackball, a selection device such as a mode changeover switch, or an input device such as a keyboard.

[0039] The display 135 displays a GUI (Graphical User Interface) for receiving input of imaging conditions and images generated by the generation function 110e under the control of the display control function 110c, etc. The display 135 is, for example, a display device such as a liquid crystal display. The display 135 is an example of a display unit. The display 135 has a mouse, a keyboard, buttons, a panel switch, a touch command screen, a foot switch, a trackball, a joystick, etc.

[0040] Next, the background of the embodiment will be described.

[0041] As a method for super-resolution of blood flow signals, for example, the SURE (SUper Resolution using Erythrocytes) method as shown in Non-Patent Document 1 is known. This method utilizes the fact that the amplitude distribution characteristics of the speckle patterns of ultrasound images and blood flow images follow a Rayleigh distribution. In other words, by using the SURE method to integrate high-brightness signals that occur with a low probability for each frame according to the Rayleigh distribution, it is possible to obtain blood flow signals with higher resolution than conventional power Doppler methods.

[0042] However, in the process of extracting high-brightness signals that occur with a low probability according to a Rayleigh distribution for each frame, there is a possibility that signals other than blood flow signals, such as residual tissue signals such as clutter and motion artifacts, may be mistakenly picked up. In this case, signals from clutter may be distributed around the blood flow, reducing the visibility of the blood flow.

[0043] Based on this background, an ultrasound diagnostic apparatus according to an embodiment includes an acquisition unit, a first extraction unit, an identification unit, and a generation unit. The acquisition unit acquires first signal data of a plurality of frames by scanning a subject. The first extraction unit extracts second signal data of a plurality of frames by extracting signals from the first signal data by nonlinear processing. As an example, the first extraction unit extracts second signal data of a plurality of frames by extracting signals whose signal values ​​correspond to local maximum values ​​or a predetermined range. The identification unit identifies inappropriate signal points or inappropriate frames from the second signal data. The generation unit generates third signal data based on the identification result of the inappropriate signal points or the inappropriate frames and the second signal data.

[0044] Moreover, the image processing device according to the embodiment includes an acquisition unit, a first extraction unit, an identification unit, and a generation unit. The acquisition unit acquires first signal data of a plurality of frames obtained by scanning a subject. The first extraction unit extracts second signal data of a plurality of frames by extracting signal values ​​from the first signal data by nonlinear processing. As an example, the first extraction unit extracts second signal data of a plurality of frames by extracting signals whose signal values ​​correspond to local maximum values ​​or a predetermined range from the first signal data. The identification unit identifies inappropriate signal points or inappropriate frames from the second signal data. The generation unit generates third signal data by integrating the second signal data while excluding inappropriate signal points or inappropriate frames from integration targets.

[0045] In addition, the ultrasound diagnostic method acquires first signal data of multiple frames by scanning a subject, extracts second signal data of multiple frames by extracting signal values ​​from the first signal data by nonlinear processing, for example by extracting signals whose signal values ​​are local maximum values ​​or fall within a predetermined range, identifies inappropriate signal points or inappropriate frames from the second signal data, and generates third signal data by accumulating the second signal data while excluding the inappropriate signal points or inappropriate frames from the accumulation target.

[0046] That is, by performing an operation to identify inappropriate signal points or inappropriate frames from the accumulated second signal data based on, for example, the number of signal point extractions or the change in the number of extracted signals per frame, it is possible to eliminate signals other than blood flow. This makes it possible to obtain a high-quality blood flow signal from which inappropriate signal points or frames have been removed.

[0047] The processing performed by the ultrasound diagnostic device 10 according to the first embodiment will be described in detail using Fig. 2 while also referring to Fig. 3A, Fig. 3B, and Fig. 4 as appropriate. Fig. 2 is a flowchart showing the flow of processing performed by the ultrasound diagnostic device 10 according to the first embodiment.

[0048] First, in step S100, the transmission circuitry 9 executes an ultrasonic scan on the subject by transmitting ultrasonic waves to the subject through the ultrasonic probe 5. The reception circuitry 11 receives ultrasonic echoes. The processing circuitry 110 acquires, by the acquisition function 110f, first signal data of a plurality of frames obtained by scanning the subject from the reception circuitry 11 as echo data.

[0049] As another example, the processing circuitry 110 may acquire the first signal data based on signal processing for blood flow imaging by the acquisition function 110f. As one example, the processing circuitry 110 may acquire, as the first signal data, signal data obtained by performing signal processing for blood flow imaging on signal data of a plurality of frames obtained by scanning a subject by the acquisition function 110f.

[0050] Next, in step S200, the processing circuitry 110 uses the first extraction function 110g to remove clutter from the first signal data by wall filtering (MTI filtering), and extracts a blood flow signal with reduced tissue signals.

[0051] Next, in step S300, the processing circuitry 110 extracts second signal data for multiple frames by using the first extraction function 110g to extract a portion with a high signal value from the blood flow signal extracted in step S200. As an example, the processing circuitry 110 extracts second signal data for multiple frames by using the first extraction function 110g to extract a signal from the first signal data by nonlinear processing. As an example, the processing circuitry 110 extracts second signal data for multiple frames by using the first extraction function 110g to extract a signal whose signal value falls within a local maximum value or a predetermined range, for example, a signal whose signal value is equal to or greater than a predetermined value.

[0052] 3A and 3B specifically show a method for extracting a portion with a high signal value. FIG. 3A shows a method for performing threshold processing and extracting a signal whose signal value is a predetermined value. For the sake of simplicity, the first signal data is shown as one-dimensional signal data. Here, points 90a to 90k are schematic diagrams showing signal points of each signal data in a certain frame, and the vertical direction of the paper represents the magnitude of each signal data. Here, the processing circuit 110 uses the first extraction function 110g to extract points 90b, 90c, 90d, 90e, 90g, 90h, and 90i, which are points whose signal values ​​are equal to or greater than the threshold values ​​shown by the lines in FIG. 3A, as second signal data.

[0053] On the other hand, Fig. 3B shows a case where the processing circuit 110 performs local peak detection processing by using the first extraction function 110g to extract a signal whose signal value is a local maximum value from the first signal data, thereby extracting second signal data of a plurality of frames. Here, like Fig. 3A, points 90a to 90k are schematic representations of each signal data in one frame, and the vertical direction of the paper represents the size of each signal data. In Fig. 3B, the processing circuit 110 extracts points 90d and 90h, which are local maximum values, as second signal data by using the first extraction function 110g.

[0054] 3A and 3B, for the sake of simplicity, the first signal data is illustrated as being one-dimensional signal data, but the data of each frame of the first signal data of multiple frames is usually two-dimensional signal data. Even if the first signal data is two-dimensional or higher dimensional signal data, the processing circuit 110 can extract the second signal data of multiple frames by the first extraction function 110g by performing the same process as described above.

[0055] FIG. 4 shows a plurality of second signal data extracted in this manner. Here, frames 21 to 24 represent each frame of the first signal data of the plurality of frames, or each frame of the blood flow signal data obtained by performing the process of step S200 on the first signal data of the plurality of frames and performing clutter removal processing. For example, the data of frame 21 represents the first signal data in the first frame, or the blood flow signal data after the first signal data in the first frame has been subjected to clutter removal processing. Moreover, the data of frame 22 represents the first signal data in the second frame, or the blood flow signal data after the second signal data in the second frame has been subjected to clutter removal processing.

[0056] Moreover, in frames 21 to 24, pixels shown in gray or black represent signal data extracted as the second signal data. For example, in Fig. 4, points 31a to 31d are signal data extracted as the second signal data in frame 21, which is the first frame. Moreover, points 31e, 31f, 31g, 31h and area 32a are signal data extracted as the second signal data in frame 22, which is the second frame. Moreover, in frames 21 to 24, gray pixels represent signal points that are not extracted as inappropriate signal points in step S400A described below, and black pixels represent signal points that are extracted as inappropriate signal points in step S400A.

[0057] Next, in step S400A, the processing circuit 110 uses the identification function 110h to identify inappropriate signal points from the second signal data extracted in step S300. Here, the inappropriate signal points are signal points that are not considered to be blood flow signals of the observation target, such as clutter. Here, since clutter and the like tend not to be extracted as high signal points across multiple frames at the same position, the processing circuit 110 uses the identification function 110h to identify inappropriate signal points based on the number of signal extractions across multiple frames. As an example, the processing circuit 110 uses the identification function 110h to identify signal points at positions where the number of signal extractions is less than a reference number, as inappropriate signal points.

[0058] For example, in Fig. 4, the integrated signal data 30 indicates the second signal data on which an integration process has been performed in step S500 described later. In step S400A, the processing circuit 110 generates a table 40 using the identification function 110h to count how many times each point has been extracted as a high signal point. For example, points 31a, 31b, 31c, etc. are extracted as high signal points in two or more frames, so the signal extraction count is "2". On the other hand, points belonging to region 32a are extracted as high signal points only in frame 22, which is the second frame, i.e., only in one frame, so the signal extraction count is "1".

[0059] Here, the processing circuit 110 sets the reference signal extraction count to "2", for example. In this case, the processing circuit 110 uses the identification function 110h to determine that signal points in region 31, such as points 31a, 31b, 31c, and the like, whose signal extraction count is two or more, are appropriate signal points. On the other hand, the processing circuit 110 uses the identification function 110h to identify signal points in region 32, whose signal extraction count is one, as inappropriate signal points.

[0060] In the above example, the processing circuit 110 uses the identifying function 110h to determine whether a signal point is inappropriate based on the number of signal extractions, but the embodiment is not limited to this. As an example, the processing circuit 110 may use the identifying function 110 to identify an inappropriate signal point in step S300A using a neural network.

[0061] Next, in step S500, processing circuit 110 causes generation function 110e to accumulate second signal data in the multiple frames extracted in step S300 to generate accumulated signal data that integrates the data of each frame. As an example, in Fig. 4, processing circuit 110 causes generation function 110e to accumulate multiple pieces of second signal data that are high signal points shown in gray or black in frames 21 to 24, thereby generating accumulated signal data 30.

[0062] Next, in step S600A, the processing circuit 110 generates third signal data from which inappropriate signals have been removed, based on the result of identifying the inappropriate signal points identified in step S400A and the second signal data extracted in step S300, using the generation function 110e. As an example, the processing circuit 110 generates the third signal data by removing inappropriate signal points from the accumulated signal data 30 obtained by accumulating the second signal data, using the generation function 110e. In other words, the processing circuit 110 generates the third signal data by removing inappropriate signal points from the signal points after accumulation, using the generation function 110e. 4, processing circuit 110 uses generation function 110e to remove, as inappropriate signal points, signal points in region 32, which are signal points at positions where the number of signal point extractions is less than a reference number, from accumulated signal data 30 obtained by accumulating second signal data, from the signal points after accumulation, and generates third signal data 50 in which only signal points in appropriate region 31 are accumulated. Note that the embodiment is not limited to this, and processing circuit 110 may generate the third signal data by accumulating the second signal data while excluding inappropriate signal points from the accumulation targets, using generation function 110e.

[0063] In the above embodiment, the processing circuit 110 removes the inappropriate signal points using the generating function 110e, but the embodiment is not limited to this. The processing circuit 110 may generate the third signal data while reducing the signal strength of the inappropriate signal points using the generating function 110e.

[0064] In steps 400A to S600A, the criteria for identifying inappropriate signal points and the method for generating the third signal data may be automatically set by the ultrasound diagnostic device 10, and the processing circuitry 110 may automatically remove inappropriate signals without depending on user input.

[0065] Next, in step S700, the processing circuit 110 causes the display control function 110c to display the third signal data on the display 135 as a display unit. This makes it possible to obtain a high-quality blood flow signal image from which signals other than blood flow are excluded.

[0066] Fig. 5A is a diagram showing an example of an ultrasound image in the comparison method. In contrast, Fig. 5B is a diagram showing an example of an ultrasound image generated by the ultrasound diagnostic device 10 according to the first embodiment. As shown in Fig. 5A, in the ultrasound image in the comparison method, signals other than blood flow signals are included in a region 70. In contrast, as shown in Fig. 5B, in the ultrasound image generated by the ultrasound diagnostic device 10 according to the first embodiment, signals other than blood flow signals are removed in a region 71 that is the same as the region 70.

[0067] As described above, in the first embodiment, the processing circuit 110 generates the third signal data by identifying inappropriate signal points based on the number of times the signal points are extracted using the identifying function 110h. This makes it possible to remove signal points that become noise, thereby improving image quality.

[0068] (Modification of the first embodiment) It should be noted that the embodiment is not limited to the above-mentioned example.

[0069] In the above example, in steps S400A to S600A, the ultrasonic diagnostic apparatus 10 automatically determines the criteria for identifying inappropriate signal points by the first extraction function 110g of the processing circuitry 110, but the embodiment is not limited to this. As an example, the processing circuitry 110 may receive an input of criteria for identifying inappropriate signal points or inappropriate frames from a user by the reception function 110d, and cause the display control function 110c to display the index value for each position or frame for the user to set the criteria on the display 135 as a display unit.

[0070] As an example, in step S400A, the processing circuit 110 uses the display control function 110c to measure how many times each point has been extracted as a high signal point by the identification function 110h, and generates a table 40 shown in FIG. 4 indicating the number of times each point has been extracted as a high signal point. Next, the processing circuit 110 uses the display control function 110c to display information corresponding to the table 40 indicating the number of times each point has been extracted as a high signal point on the display 135 as a display unit. In addition, the processing circuit 110 uses the reception function 110d to receive from the user an input of criteria for identifying an inappropriate signal point. In step S400A, the processing circuit 110 uses the identification function 110h to identify an inappropriate signal point from the second signal data based on the criteria input by the user.

[0071] In the embodiment, in step S400A, the processing circuit 110 uses the identifying function 110h to identify an inappropriate signal based on the number of times the signal is extracted at each point, but the embodiment is not limited to this. As an example, the processing circuit 110 may use the identifying function 110h to identify an inappropriate signal point based on the signal strength at each position. For example, the processing circuit 110 uses the identifying function 110h to identify a signal point whose signal strength at each position is lower than a reference value as an inappropriate signal point.

[0072] Second Embodiment In the first embodiment, a case has been described in which the processing circuit 110 identifies inappropriate signal points by the identifying function 110h in step S400A, and generates third signal data by excluding the identified inappropriate signal points from the accumulated signal points by the generating function 110e in step S600A. In the second embodiment, a case will be described in which the third signal data is generated by identifying inappropriate frames rather than identifying inappropriate signal points.

[0073] 6 is a flowchart showing an example of the flow of processing performed by the ultrasound diagnostic apparatus 10 according to the second embodiment. Here, the processing other than step S400B and step S600B is the same as that in the first embodiment, so repeated explanation will be omitted.

[0074] In step S400B, the processing circuit 110 uses the identification function 110h to identify an inappropriate frame from the second signal data extracted in step S300. Here, an inappropriate frame is a frame that is estimated to include a signal point that is not considered to be a blood flow signal of an observation target, such as clutter. Here, it is considered that the number of extracted signals extracted as high signal points changes suddenly when viewed in the frame direction near a frame where clutter occurs, so the processing circuit 110 uses the identification function 110h to identify an inappropriate frame based on the number of extracted signals in the frame direction. As an example, the processing circuit 110 uses the identification function 110h to identify a frame in which the change in the number of extracted signals in the frame direction is greater than a reference as an inappropriate frame.

[0075] For example, in FIG. 7, frames 21 to 24 indicate each frame of the first signal data of a plurality of frames. Among frames 21 to 24, signal points indicated in gray or black represent signal points of high signal values ​​extracted by the processing circuit 110 as a part with high signal values ​​by the first extraction function 110g in step S300. Here, in step S400B, the processing circuit 110 uses the identification function 110h to identify a frame in which the change in the number of extracted signals in the frame direction is greater than the reference as an inappropriate frame. In the example of FIG. 7, the number of signal points extracted as signal points of high signal values ​​in frame 22 is "12". In contrast, the number of signal points extracted as signal points of high signal values ​​in frames 21 and 23 is "4". Therefore, since the change in the number of extracted signals in the frame direction exceeds the reference near frame 22, the processing circuit 110 uses the identification function 110h to identify frame 22 as an inappropriate frame.

[0076] In the above example, the processing circuit 110 uses the identifying function 110h to determine whether a frame is inappropriate based on the change in the number of extracted signals in the frame direction, but the embodiment is not limited to this. As an example, the processing circuit 110 may use the identifying function 110h to identify inappropriate signal points in step S400B based on a comprehensive determination criterion using a neural network.

[0077] In step S600B, the processing circuit 110 generates third signal data from which the inappropriate frames have been excluded, based on the results of identifying the inappropriate frames identified in step S400B and the second signal data identified in step S300, using the generation function 110e. As an example, the processing circuit 110 generates the third signal data by integrating the second signal data while excluding the inappropriate frames from the integration target, using the generation function 110e. As an example, in FIG. 7, the processing circuit 110 generates the third signal data 60 by integrating the second signal data while excluding frame 22, which is an inappropriate frame, from the integration target, using the generation function 110e.

[0078] In the above embodiment, the processing circuit 110 uses the identifying function 110h to extract inappropriate frames based on a change in the number of extracted signals in the frame direction in step S400B, but the embodiment is not limited to this. The processing circuit 110 may use the identifying function 110h to identify inappropriate frames based on the number of extracted signals in the frame direction itself in step S400B. As an example, the processing circuit 110 may use the identifying function 110h to identify frames in which the number of extracted signals in the frame direction exceeds a reference value as inappropriate frames.

[0079] Furthermore, in steps 400B to S600B, the criteria for identifying inappropriate signal points and the method for generating the third signal data may be automatically set by the ultrasound diagnostic device 10, and the processing circuitry 110 may automatically remove inappropriate signals without depending on user input.

[0080] Fig. 8A is a diagram showing an example of an ultrasound image in the comparison method. In contrast, Fig. 8B is a diagram showing an example of an ultrasound image generated by the ultrasound diagnostic device 10 according to the second embodiment. As shown in Fig. 8A, in the ultrasound image in the comparison method, signals other than blood flow signals are included in a region 80. In contrast, as shown in Fig. 8B, in the ultrasound image generated by the ultrasound diagnostic device 10 according to the second embodiment, signals other than blood flow signals are removed in a region 81 that is the same as the region 80.

[0081] As described above, in the second embodiment, the processing circuit 110 generates the third signal data by identifying inappropriate frames based on the change in the number of extracted signals in the frame direction using the identifying function 110h. This makes it possible to remove frames that become noise, thereby improving image quality.

[0082] (Third embodiment) Hereinafter, the third embodiment will be described in detail with reference to the drawings regarding a medical information processing apparatus, an ultrasonic diagnostic apparatus, and a program.

[0083] First, the definitions of some terms used in the third embodiment will be briefly explained.

[0084] The ultrasound diagnostic apparatus according to the third embodiment causes an ultrasound probe to perform an ultrasound scan, and collects multiple frame data (multiple frame data within a predetermined time) that are continuous in the time direction and obtained by the execution of the ultrasound scan. The frame data is collected at a predetermined frame rate by the execution of an ultrasound scan, and refers to any of a received image, a measurement image, and a blood flow image. The received image is a two-dimensional image representation of an ultrasound reception signal received by the ultrasound probe. The measurement image is a two-dimensional image representation of measurement data obtained by performing phasing addition and quadrature detection processing on the reception signal. The blood flow image is a two-dimensional image representation of blood flow data in which information derived from blood flow in the measurement data has been extracted or emphasized.

[0085] The measurement data includes, for example, information derived from tissue (tissue image component) and information derived from blood flow (blood flow image component). The information derived from blood flow may include not only information derived from blood but also information derived from contrast agents in blood. Furthermore, the blood flow data is data having pixel values ​​from which information derived from blood flow is extracted or emphasized, and includes the velocity, variance, and power value of blood flow.

[0086] Extracting information derived from blood flow is, for example, an operation of selectively extracting image features of blood flow image components from measurement data. Emphasizing information derived from blood flow is, for example, an operation of making image features of blood flow image components more prominent than image features of tissue image components. Note that blood flow data may be obtained by a process of extracting or emphasizing information derived from blood flow, or by a process of removing or reducing information derived from tissue.

[0087] The ultrasound diagnostic apparatus also performs a process of continuously extracting image components representing an object from the first ultrasound image data, which will be described later. The object includes, for example, any one of blood, body tissue, and contrast agent.

[0088] The ultrasonic diagnostic device outputs second ultrasonic image data based on image components representing the object continuously extracted from the first ultrasonic image data. The second ultrasonic image data may be any of synthetic image data obtained by synthesizing image components representing the continuously extracted object with the first ultrasonic image data, corrected image data obtained by correcting the first ultrasonic image data based on image components representing the continuously extracted object, and image data including image components representing the continuously extracted object. According to the ultrasonic diagnostic device of this embodiment, even if the number of images used to extract the object is small, image components (pixel values) representing the object can be continuously extracted, and a high-resolution ultrasonic image with high responsiveness can be obtained. Moreover, according to the ultrasonic diagnostic device of this embodiment, the calculation load of signal extraction can be suppressed to 1 / number of frames compared to the conventional one, and the calculation load of signal extraction can be reduced.

[0089] Although the embodiment has been described so far as applied to an ultrasonic diagnostic device, the embodiment may be applied to a modality (medical information processing device) other than an ultrasonic diagnostic device. For example, the embodiment may be applied to a medical information processing device such as a workstation or server that acquires ultrasonic image data obtained based on the result of an ultrasonic scan of a subject.

[0090] FIG. 9 is a block diagram showing an example of the configuration of an ultrasonic diagnostic device according to the third embodiment. The ultrasonic diagnostic device 10 is a device that generates ultrasonic image data based on a reflected wave signal received from an ultrasonic probe 5. The ultrasonic diagnostic device 10 shown in FIG. 9 is a device that can generate two-dimensional ultrasonic image data based on a two-dimensional reflected wave signal and can generate three-dimensional ultrasonic image data based on a three-dimensional reflected wave signal. However, the embodiment is also applicable to the case where the ultrasonic diagnostic device 10 is a device dedicated to two-dimensional data. The ultrasonic diagnostic device 10 includes a transmission circuit 9, a reception circuit 11, and an image processing device 100 as a medical information processing device according to the embodiment.

[0091] The ultrasonic probe 5 is, for example, an electronic scanning type probe, and has a plurality of transducers 101 arranged one-dimensionally or two-dimensionally at its tip. The transducer 101 is a piezoelectric element (electromechanical conversion element) that performs mutual conversion between an electric signal (voltage pulse signal) and an ultrasonic wave (acoustic wave). The ultrasonic probe 5 transmits ultrasonic waves from the plurality of transducers 101 to a subject, and receives reflected ultrasonic waves from the subject by the plurality of transducers 101. The reflected acoustic wave reflects the difference in acoustic impedance within the subject. Note that the reflected ultrasonic signal when the transmitted ultrasonic pulse is reflected by the surface of a moving blood flow, a heart wall, or the like, undergoes a frequency shift due to the Doppler effect depending on the velocity image component in the ultrasonic transmission direction of the moving object.

[0092] The probe connection unit 103 connects to the ultrasonic probe 5 and transmits and receives ultrasonic waves to and from the ultrasonic probe 5. The connection means of the ultrasonic probe 5 by the probe connection unit 103 may be either wired or wireless. In the case of a wired connection, the probe connection unit 103 has a connector unit (receptacle) for connecting a connector (plug) of the ultrasonic probe 5. In the case of a wireless connection, the probe connection unit 103 has a communication unit for wireless communication with the ultrasonic probe 5.

[0093] The transmission circuit 9 is a transmission unit that outputs a pulse signal (drive signal) to the multiple transducers 101. By applying a pulse signal to the multiple transducers 101 with a time difference, ultrasonic waves with different delay times are transmitted from the multiple transducers 101, and a transmitted ultrasonic beam is formed. The direction and focus of the transmitted ultrasonic beam can be controlled by selectively changing the transducer 101 to which the pulse signal is applied (i.e., the transducer 101 to be driven) or by changing the delay time (application timing) of the pulse signal. By sequentially changing the direction and focus of the transmitted ultrasonic beam, an observation area inside the subject is scanned. In addition, by changing the delay time of the pulse signal, a transmitted ultrasonic beam that is a plane wave (focus is far away) or a diverging wave (focus point is the opposite ultrasonic transmission direction for the multiple transducers 101) may be formed. Alternatively, a transmitted ultrasonic beam may be formed using one transducer or a part of the multiple transducers 101. The transmission circuit 9 transmits a pulse signal of a predetermined drive waveform to the transducer 101, causing the transducer 101 to generate a transmitted ultrasonic wave having a predetermined transmission waveform. The receiving circuit 11 is a receiving section that inputs, as a received signal, an electrical signal output from the transducer 101 that has received a reflected ultrasonic wave. The received signal is input to an image generating section of the processing circuit 110.

[0094] The operation of the transmission circuit 9 and the reception circuit 11, i.e., the transmission and reception of ultrasound, is controlled by a control function 113 of the processing circuit 110. The processing circuit 110 changes the position at which a voltage signal or a transmitted ultrasound is formed in accordance with the generation of a B-mode image and a blood flow image, which will be described later, by the control function 113. The transmission circuit 9 and the reception circuit 11 are an example of an execution unit.

[0095] When generating a B-mode image, the reception signal of the reflected ultrasound obtained by scanning the observation area is acquired and used for image generation. When generating a blood flow image, the transmission and reception of ultrasound is performed multiple times on one or multiple scanning lines in the observation area, and multiple frames of the reception signal of the reflected ultrasound are acquired and used for image generation, i.e., extraction of blood flow information. The scanning for generating the blood flow image may be a method of performing multiple transmissions and receptions on one scanning line and then performing transmission and reception on the next scanning line, or a method of performing transmission and reception once on each scanning line multiple times. In addition, the generation of the B-mode image and the blood flow image may be performed so as to reduce the number of scanning lines, that is, so that the ultrasound is transmitted over a wide range of the observation area by transmitting plane waves or diverging waves. In addition, the transmission angle of the plane waves or diverging waves, the range of the observation area to be transmitted, etc. may be changed, transmission and reception may be performed multiple times over a wide range of the observation area, and the received signals may be added and used. In this specification, both the analog signal output from the transducer 101 and the digital data sampled (digitally converted) from the analog signal are called the received signal without any particular distinction. However, depending on the context, the received signal may be referred to as received data or measured data to clarify that it is digital data.

[0096] The image processing device 100 is connected to a transmitting circuit 9 and a receiving circuit 11, and processes signals received from the receiving circuit 11 and controls the transmitting circuit 9. The image processing device 100 includes a processing circuit 110, a memory 132, an input device 134, and a display 135. The processing circuit 110 has an image generating function 111, an image processing function 112, a control function 113, and a display control function 114.

[0097] 10, the image generating function 111 more specifically includes an acquiring function 110f, an extracting function 1110g, and an output function 1110h. More specifically, the acquiring function 110f includes a received signal storing function 1110a, a delay-and-sum processing function 1110b, a signal storing function 1110c, a B-mode processing function 1110d, a displacement amount correcting function 1110e, a Doppler processing function 1110i, and the like.

[0098] In the embodiment, the processing functions and learned models performed by the received signal storage function 1110a, the phasing addition processing function 1110b, the signal storage function 1110c, the B-mode processing function 1110d, the displacement amount correction function 1110e, the acquisition function 110f, the extraction function 1110g, the output function 1110h, the Doppler processing function 1110i, the image generation function 111, the image processing function 112, the control function 113, the display control function 114, etc. are stored in the memory 132 in the form of a program executable by a computer. The processing circuitry 110 is a processor that realizes a function corresponding to each program by reading and executing the program from the memory 132. In other words, the processing circuitry 110 in a state in which each program has been read has each function shown in the processing circuitry 110 in FIG. 9 or the image generation function 111 in FIG. 10. 1, the functions of the processing circuit 110 are described as being realized by a single processing circuit, but the processing circuit 110 may be configured by combining multiple independent processors, and each processor may execute a program to realize the functions. In other words, each of the above-mentioned functions may be configured as a program, and one processing circuit may execute each program. Also, two or more of the functions of the processing circuit 110 may be realized by a single processing circuit. As another example, a specific function may be implemented in a dedicated independent program execution circuit.

[0099] 9 and 10, the image generation function 111, the image processing function 112, the control function 113, the display control function 114, the acquisition function 110f, the extraction function 1110g, and the output function 1110h are examples of an image generation unit, a processing unit, a control unit, a display control unit, an acquisition unit, an extraction unit, and an output unit, respectively.

[0100] The term "processor" used in the above description means a circuit such as a CPU, as in the first embodiment. The processor realizes functions by reading and executing a program stored in the memory 132.

[0101] Also, the program may be directly embedded in the circuitry of the processor instead of storing the program in the memory 132. In this case, the processor realizes the function by reading and executing the program embedded in the circuitry.

[0102] The transmission circuit 9, reception circuit 11, etc. built into the ultrasound diagnostic device 10 may be configured as hardware such as an integrated circuit, but may also be configured as a modularized program in software form.

[0103] The processing circuit 110 generates image data based on the reception signal obtained from the ultrasonic probe 5 using an image generation function 111. The image generation function 111 will be described in detail later. The processing circuit 110 performs image processing such as brightness adjustment, interpolation, and filter processing on the image data generated by the reception signal processing unit 106 using an image processing function 112. The processing circuit 110 is a control unit that generally controls the transmission circuit 9, the reception circuit 11, the image processing function 112, the display 135, etc. using a control function 113. The processing circuit 110 controls the display of image data and various information using a display control function 114.

[0104] The memory 132 is composed of a semiconductor memory element such as a RAM (Random Access Memory), a flash memory, a hard disk, an optical disk, etc. The memory 132 is a memory that stores data such as image data for display generated by the processing circuit 110. The memory 132 can also store data generated by the B-mode processing function 1110d and the Doppler processing function 1110i. The B-mode data and Doppler data stored in the memory 132 can be called by an operator after diagnosis, for example, and become ultrasonic image data for display via the processing circuit 110. The memory 132 can also store a reception signal (reflected wave data) output by the receiving circuit 11. In addition, the memory 132 stores various data such as a control program for performing ultrasonic transmission / reception, image processing, and display processing, diagnosis information (for example, a patient ID, a doctor's findings, etc.), a diagnosis protocol, and various body marks, as necessary.

[0105] The input device 134 accepts various instructions and information input from an operator. The input device 134 is, for example, a pointing device such as a mouse or a trackball, a selection device such as a mode changeover switch, or an input device such as a keyboard. The display 135 displays a GUI (Graphical User Interface) for accepting input of imaging conditions and images generated by the output function 1110h or the like under the control of the display control function 114 or the like. The display 135 is, for example, a display device such as a liquid crystal display. The display 135 is an example of a display unit. The display 135 has a mouse, a keyboard, a button, a panel switch, a touch command screen, a foot switch, a trackball, a joystick, or the like.

[0106] (Configuration of the receiving signal processing block) FIG. 10 is a block diagram showing an example of the image generating function 111. The image generating function 111 includes an acquisition function 110f, an extraction function 1110g, and an output function 1110h. The acquisition function 110f includes a received signal storage function 1110a, a delay-and-sum processing function 1110b, a signal storage function 1110c, a B-mode processing function 1110d, a displacement amount correction function 1110e, and a Doppler processing function 1110i. The received signal storage function 1110a stores the received signal received by the receiving circuit 11. Depending on the device configuration and the type of the received signal, the received signal storage function 1110a may not store the received signal received by the receiving circuit 11, and may be stored in the signal storage function 1110c after the delay-and-sum processing function 1110b described later. Furthermore, the received signal storage function 1110a may be formed from a common block with the signal storage function 1110c described later, and may store the received signal from the receiving circuit 11 and the received signal after the phasing and summing processing function 1110b.

[0107] The delay and sum processing function 1110b performs delay and sum processing and quadrature detection processing on the reception signal obtained by the reception circuit 11, and the processed reception signal is stored by the signal storage function 1110c. The delay and sum processing is a process of forming a reception ultrasonic beam by changing the delay time and weight for each transducer 101 and adding up the reception signals of multiple transducers 101, and is also called delay and sum (DAS) beamforming. The quadrature detection processing is a process of converting the reception signal into an in-phase signal (I signal) and a quadrature signal (Q signal) of the baseband. The delay and sum processing and quadrature detection processing are performed based on the element arrangement and various conditions for image generation (aperture control, signal filter) input by the control function 113. The reception signal after the delay and sum processing and quadrature detection processing is stored by the signal storage function 1110c. Here, a typical example of DAS beamforming is shown, but any process that forms a reception ultrasonic beam, such as adaptive beamforming, model-based processing, and processing using machine learning, may be used. The reception signal (digital data) obtained by the reception circuit 11 is also called RAW data. The reception signal (digital data) obtained by the phasing and summing processing function 1110b is also called RF data. The RAW data and RF data are examples of measurement data acquired based on the reception signal of the ultrasound reflected inside the living body.

[0108] The B-mode processing function 1110d performs envelope detection processing, logarithmic compression processing, etc. on the received signals for generating B-mode images stored by the signal storage function 1110c to generate image data in which the signal intensity at each point in the observation region is expressed as luminance intensity. The B-mode processing function 1110d may also perform B-mode processing on the received signals whose displacement has been corrected by the displacement correction function 1110e.

[0109] The displacement amount correction function 1110e calculates the amount of tissue displacement caused by body movement between frames from the received signals acquired over multiple frames. This is generally calculated by a block matching calculation called a speckle tracking method. A region of interest is set within a frame, and the region of interest between frames is tracked by correlation to calculate the displacement amount of the region of interest. A plurality of regions of interest are set within a frame to calculate the displacement amount of the entire frame. Here, an example of a method using correlation between frames is shown, but any method may be used as long as it can calculate the displacement amount of the region of interest. In the case of an ultrasonic signal, it is called speckle tracking because it tracks speckles, which are scattered images of ultrasonic waves reflected from scatterers in the body tissue. The correlation calculation of the region of interest between frames may be performed on the received signal after any of delay and sum processing, quadrature detection processing, and envelope detection processing. In addition, the correlation calculation may be performed on the time waveform of the received signal, or may be performed on frequency space data obtained by performing a discrete Fourier transform on the received signal. The displacement amount correction function 1110e corrects the displacement amount by moving the received signal with respect to a reference frame using the calculated displacement amount. The amount of displacement to be corrected may be a uniform value for the entire frame, such as the average value of the amount of displacement for each region of interest, or may be changed within the frame, such as for each region of interest. The amount of displacement for the entire frame calculated for each region of interest may be interpolated in the time direction within the frame and in the data strings of multiple frames, using linear interpolation, spline interpolation, or the like. When correcting the amount of displacement, the received signal may be similarly interpolated and then moved to allow for more fine correction.

[0110] The Doppler processing function 1110i extracts blood flow data from the reception signals for generating a blood flow image stored by the signal storage function 1110c. The Doppler processing function 1110i may also perform Doppler processing on the reception signals whose displacement has been corrected by the displacement correction function 1110e. The Doppler processing function 1110i extracts blood flow data based on the Doppler effect of the object within the scanning range by frequency analyzing the reception signals for generating a blood flow image stored by the signal storage function 1110c.

[0111] In generating blood flow data by the Doppler method, a series of received signal data of multiple frames is acquired in the time direction for the same measurement position. The Doppler processing function 1110i applies an MTI (Moving Target Indicator) filter to the received signal data series. This reduces information (clutter image components) derived from tissues that are stationary between frames or tissues with little movement, and extracts information derived from blood flow (blood flow image components). The processing circuit 110 calculates blood flow data such as blood flow velocity, variance, and power from the blood flow image components using the Doppler processing function 1110i.

[0112] The MTI filter may be a filter with fixed filter coefficients, such as a Butterworth type IIR (infinite impulse response) filter or a polynomial regression filter. The MTI filter may be an adaptive filter that changes coefficients according to an input signal using eigenvalue decomposition or singular value decomposition. Alternatively, the processing circuit 110 may use the Doppler processing function 1110i to decompose the received signal into one or more bases using eigenvalue decomposition or singular value decomposition, extract only a specific base, and remove clutter image components. The processing circuit 110 may also use the Doppler processing function 1110i to obtain a velocity vector for each coordinate in the image and obtain a blood flow vector representing the magnitude and direction of the blood flow by using a method such as a vector Doppler method, a speckle tracking method, or a vector flow mapping method. In addition to the methods exemplified here, any method may be used as long as it can extract or emphasize information derived from blood flow contained in the received signal (measurement data), or can remove or reduce information derived from tissue.

[0113] The processing circuit 110 acquires, by the acquisition function 110f, data of a plurality of frames consecutive in the time direction obtained based on the result of an ultrasound scan on the subject as the first ultrasound image data. As another example, the processing circuit 110 acquires, by the acquisition function 110f, a plurality of frames of blood flow images (here, power Doppler images) generated by the Doppler processing function 1110i, and acquires, by adding these, added image data obtained as the first ultrasound image data. Note that the received image or the measured image may be treated as frame data, and a blood flow image obtained by adding the plurality of frames may be used as the first ultrasound image data.

[0114] Furthermore, the processing circuitry 110 performs a process of continuously extracting image components representing an object from the first ultrasonic image data by the extraction function 1110g. Specifically, the processing circuitry 110 extracts second ultrasonic image data by applying a kernel that extracts continuous components in a direction of interest to the first ultrasonic image data obtained based on the result of an ultrasonic scan on the subject by the extraction function 1110g. Furthermore, the processing circuitry 110 performs a process of outputting the second ultrasonic image data based on the image components representing the object continuously extracted from the first ultrasonic image data by the output function 1110h.

[0115] The image data output after processing by the B-mode processing function 1110d, the Doppler processing function 1110i, and the extraction function 1110g is processed by the image generation function 111 shown in Figure 9, and then finally displayed on the display 135.

[0116] The processing circuit 110 having the image generating function 111 may be configured with one or more processors and a memory. In that case, each function shown in FIG. 10 is realized by a computer program. For example, each function can be provided by a CPU reading and executing a program stored in the memory. The processing circuit 110 having the image generating function 111 may include a processor (GPU, FPGA, etc.) in charge of calculations of the B-mode processing function 1110d, the displacement amount correction function 1110e, the Doppler processing function 1110i, and the extraction function 1110g in addition to the CPU. The memory may include a memory for non-temporarily storing a program, a memory for temporarily storing data such as a received signal, a working memory used by the CPU, etc.

[0117] Next, the background of the third embodiment will be described.

[0118] One method for super-resolution of blood flow signals that does not use contrast agents involves extracting high-signal areas that occur with low frequency for each frame of the blood flow signal after it passes through a wall filter, generating a signal with higher resolution than the resolution limit of ultrasound, and accumulating this between frames to obtain a blood flow signal with higher resolution than conventional blood flow signals.

[0119] More specifically, it is described that the amplitude distribution characteristic 1050 of the speckle pattern of an ultrasound image or blood flow image can be approximated by a probability distribution called a Rayleigh distribution, as shown in Fig. 11. This allows high-intensity and spatially sparse signals, which are areas with low occurrence probability but large amplitude values, such as signals corresponding to area 1051, to be extracted from each blood flow image and integrated.

[0120] However, with this method, blood flow may become discontinuous or may not be depicted smoothly.

[0121] In view of this background, an image processing device 100 serving as a medical information processing device according to the third embodiment includes a processing circuit 110. The processing circuit 110 uses an extraction function 1110g to compare a pixel value of a position of interest included in the first ultrasound image data with a pixel value of an adjacent position for each direction of interest relative to the position of interest, and weights an image component of the position of interest for each direction of interest.

[0122] Moreover, the ultrasound diagnostic device 10 according to the third embodiment includes a transmission / reception circuit (a transmission circuit 9 and a reception circuit 11) as an execution unit, and a processing circuit 110. The execution unit causes the ultrasound probe 5 to execute an ultrasound scan on a subject. The processing circuit 110 uses an extraction function 1110g to extract second ultrasound image data by applying a kernel that extracts continuous components in a direction of interest to first ultrasound image data obtained based on the result of the ultrasound scan.

[0123] In addition, the program according to the third embodiment causes a computer to execute a process of extracting second ultrasound image data by applying a kernel that extracts continuous components in a direction of interest to first ultrasound image data obtained based on the results of an ultrasound scan on a subject.

[0124] This makes it possible to extract continuous objects, enabling imaging that emphasizes objects such as blood flow.

[0125] The processing performed by the image processing device 100 as a medical information processing device according to the third embodiment will be described with reference to Fig. 12 to Fig. 14. Fig. 12 is a flowchart illustrating the flow of the processing performed by the image processing device 100 according to the embodiment.

[0126] Note that, unlike FIG. 15 in which an addition process is performed between frames and then a kernel application process is performed to extract continuous components, FIG. 12 performs a kernel application process for each frame to extract continuous components.

[0127] First, in step S1100, the processing circuitry 110 collects multiple frames of data to be processed. That is, the processing circuitry 110 uses the acquisition function 110f to acquire multiple frames of frame data 20 by performing a scan on a subject by the ultrasound diagnostic device 10. That is, the processing circuitry 110 uses the acquisition function 110f to acquire multiple frames of frame data that are continuous in the time direction and obtained by performing an ultrasound scan.

[0128] In other words, the processing circuit 110 uses the acquisition function 110f to set a measurement position so as to include a region in which blood flow information is to be observed, and repeats ultrasonic transmission and reception while fixed at the same measurement position to acquire a reception signal including a data string of multiple frames in the time direction. The number of frames of the reception signal when generating a super-resolution blood flow image according to this embodiment is generally greater than that when generating a normal Doppler image. For example, the number of frames (number of packets) of the reception signal when generating a normal Doppler image is about 5 to 20, whereas the number of frames of the reception signal when generating a super-resolution blood flow image is at least 100 frames or more, preferably several hundred to tens of thousands.

[0129] Here, the frame rate of the ultrasound diagnostic device 10 is about several hundred Hz to several thousand Hz, depending on the model and the measurement method. Therefore, the measurement time of the received signal to generate a super-resolution blood flow image is about several hundred msec to several tens of sec. The received signal including a data string of multiple frames is subjected to phasing addition and quadrature detection processing by the phasing addition processing function 1110b, and is stored by the signal storage function 1110c.

[0130] Furthermore, one frame in the data sequence may be a received signal obtained by transmitting and receiving ultrasound once to include the observation area, or may be a sum of received signals transmitted and received multiple times to include the observation area. For example, a plane wave or diverging wave is transmitted to include the observation area, and multiple received signals with different transmission angles are added together to obtain one frame of data.

[0131] Next, in step S1200, the processing circuit 110 uses the displacement amount correction function 1110e to calculate the amount of tissue displacement between frames due to body movement, etc., from the received signal including data strings of multiple frames. Then, the processing circuit 110 uses the calculated displacement amount to correct the displacement amount by moving the received signal so that its position is aligned within the frame where the integration process described later is performed, using the displacement amount correction function 1110e.

[0132] Here, the reference frame for calculating the displacement may be only one frame in the entire data sequence, the reference frame may be changed depending on the time direction position (i.e., multiple reference frames may be provided), or the previous frame in the adjacent frames may be used as the reference frame. The reference frame may be selected arbitrarily from the data sequence, and for example, any of the first frame, the middle frame, and the last frame may be used as the reference frame.

[0133] Next, in step S1300, the processing circuit 110 uses the Doppler processing function 1110i to apply an MTI filter to the received signal including the data sequence of multiple frames with the displacement corrected, thereby reducing clutter image components and extracting image components derived from blood flow to generate blood flow images of multiple frames. At this time, a part of the data sequence may be extracted and used to design the MTI filter, or the entire data sequence may be used.

[0134] Furthermore, it is preferable that the parameters of the MTI filter (cutoff frequency, number of packets / overlap of extracted frames, etc.) can be adjusted automatically or by the user according to the properties of the received signal, the subject to be measured, etc. In this way, the processing circuitry 110 generates first ultrasound image data. In other words, by the processes of steps S1100 to S1300, the processing circuitry 110 acquires the first ultrasound image data by the acquisition function 110f based on data of multiple frames that are continuous in the time direction and obtained based on the results of an ultrasound scan on the subject.

[0135] Next, in step S1400, the processing circuitry 110 uses the extraction function 1110g to apply a kernel that extracts continuous components in a direction of interest to the first ultrasound image data obtained based on the results of the ultrasound scan of the subject obtained in the processes up to step S1300, thereby extracting second ultrasound image data in which continuous components in a direction representing the object are extracted. In an embodiment in which the second ultrasound image data is extracted by applying a kernel to each frame as shown in Fig. 12, the processing circuitry 110 uses the extraction function 1110g to extract the second ultrasound image data for each of a plurality of frames by applying a kernel that extracts continuous components in a direction of interest.

[0136] In other words, the processing circuit 110 uses the extraction function 1110g to extract image components of the positions of interest as image components representing the object, based on a comparison result between pixel values ​​of positions adjacent to the positions of interest in a direction of interest and pixel values ​​of the positions of interest for each of the multiple frames included in the first ultrasound image data. Here, the object refers to a structure of interest, and includes at least one of blood, body tissue, and contrast agent, for example. In addition, the direction representing the object means, for example, the direction of blood flow, when the object is blood. That is, the processing circuit 110 uses the extraction function 1110g to generate second ultrasound image data by extracting components that are continuous in the direction of blood flow, for example, from the first ultrasound image data. This makes it possible to depict the structure of the object, for example, the structure of blood vessels, with higher image quality.

[0137] Here, as a specific method for extracting components continuous in a direction representing an object, the processing circuitry 110 extracts the second ultrasound image data using a kernel extending in a specific direction. That is, in step S1400, the processing circuitry 110 uses the extraction function 1110g to extract the second ultrasound image data from the first ultrasound image data using a kernel extending in a specific direction. Here, Fig. 13C and Fig. 14 show specific examples of the kernel extending in a specific direction.

[0138] Here, each square in Fig. 13A represents each pixel of the first ultrasonic image data, and the number written in each square indicates the signal value of each pixel. Here, for example, when extracting high signal points from the first ultrasonic image data, in the conventional method, the high signal points are extracted using a kernel 1021 that spreads over a total of 9 squares of 3 x 3 including a point of interest and 8 squares adjacent to the point of interest, as shown in Fig. 13B. In this case, the processing circuit 110 extracts the point of interest as a high signal point only when the point of interest has a higher signal value than any of the signal points in the 8 adjacent squares.

[0139] In this way, in the conventional method of extracting high signal points using a 3×3 kernel, there are cases where structures such as blood vessels extending in a specific direction cannot be sufficiently detected. Therefore, in the method according to the embodiment, the processing circuit 110 uses an extraction function 1110g to extract second ultrasound image data from the first ultrasound image data using a kernel extending in a specific direction, such as the kernel 1040 or kernel 1041 having a size of 3×1 shown in FIG.

[0140] Here, the kernel 1040 is a kernel that compares the signal value of a point of interest as the signal value of the upper left square and the signal value of the lower right square, and the processing circuit 110 uses the kernel 1040 by the extraction function 1110g to extract the point as a high signal point in the second ultrasound image data when the signal value of the point is larger than the signal value of the upper left square and the signal value of the lower right square of the point.

[0141] Furthermore, the kernel 1041 is a kernel that compares the signal value of a point of interest with the signal value one square to the lower left and the signal value one square to the upper right. The processing circuit 110 uses the kernel 1041 by the extraction function 1110g to extract a point as a high signal point in the second ultrasound image data when the signal value of a certain point is larger than the signal value one square to the lower left of the point and the signal value one square to the upper right of the point.

[0142] Furthermore, the kernel 1042 is a kernel that compares the signal value of a point of interest with the signal value one square to the left and the signal value one square to the right. The processing circuit 110 uses the kernel 1042 by the extraction function 1110g to extract a point from the second ultrasound image data as a high signal point when the signal value of the point is larger than the signal value one square to the left and the signal value one square to the right of the point.

[0143] Furthermore, the kernel 1043 is a kernel that compares the signal value of a point of interest with the signal value of one square above and one square below, and the processing circuit 110 uses the kernel 1043 by the extraction function 1110g to extract a point from the second ultrasound image data as a high signal point when the signal value of a certain point is larger than the signal value of one square to the left of the point and the signal value of one square to the right of the point.

[0144] That is, the processing circuit 110 uses the extraction function 1110g to extract the image component at the position of interest as the image component representing the object when the pixel value at the position of interest is greater than or equal to the pixel value at a position adjacent to the position of interest in one direction.

[0145] Fig. 13C shows an extraction result when the second ultrasonic image data is extracted from the first ultrasonic image data using such a kernel 1022 extending in a specific direction. When signal extraction is performed using a kernel extending in a specific direction such as kernel 1040 or kernel 1041 as in Fig. 14, it is possible to extract a high-luminance signal region in a relatively wide range, compared to the case of Fig. 13B in which signal extraction is performed using a kernel extending in all adjacent directions.

[0146] In this way, in the method according to the embodiment, for example, the processing circuit 110 extracts the second ultrasound image data from the first ultrasound image data using a kernel extending in a specific direction of, for example, 3×1 by the extraction function 1110g, so that the components continuous in the direction representing the object can be appropriately extracted. That is, in the conventional method, the extraction of the image components representing the object is discrete, whereas in the method according to the embodiment, the extraction of the image components representing the object is continuous. That is, in the embodiment, the extraction conditions can be made more lenient than in the past in order to enable the peak pixel values ​​to be extracted continuously. Note that the position of interest for peak determination is basically in pixel units, but may be in group units having multiple pixels. When peak determination is performed in group units, the pixel value of the group may be the average value of the pixel values ​​of the pixels included in the multiple groups, or an integrated value may be used.

[0147] As described above, the processing circuit 110 uses the extraction function 1110g to extract the image component at the position of interest as an image component representing the object, for example, if the pixel value at the position of interest is greater than or equal to the pixel value at a position adjacent to the position of interest in one direction. Here, one direction is, for example, the 45 degree direction at the lower left, the 45 degree direction at the lower right, the 45 degree direction at the upper left, the 45 degree direction at the upper right, the 45 degree direction at the lower left and the 45 degree direction at the upper right, the 45 degree direction at the upper left and the 45 degree direction at the lower right, the left direction, the right direction, the upper direction, the lower direction, the left-right direction, the up-down direction, etc.

[0148] Furthermore, the embodiment is not limited to this, and the processing circuit 110 may use the extraction function 1110g to extract the image component of the position of interest as the image component representing the object, for example, if the pixel value of the position of interest is greater than or equal to the pixel values ​​of positions adjacent to the position of interest in multiple directions among the directions exemplified above.

[0149] Further, although the embodiment has been described with respect to the application of a 3×1 kernel, the kernel size is not limited to this, and the processing circuit 110 may use the extraction function 1110g to apply a kernel of another size, for example a 5×1 kernel, a 7×1 kernel, or the like, to extract the image component at the position of interest as the image component representing the target object.

[0150] In this case, the processing circuit 110 may extract the image component of the attention position as the image component representing the object, for example, if the pixel value of the attention position is greater than or equal to the pixel values ​​of all positions extending in one direction among the pixels within the application range of the kernel from the attention position. As another example, the processing circuit 110 may extract the image component of the attention position as the image component representing the object, if the number of pixels that are greater than or equal to the pixel value of the attention position among the pixels within the application range of the kernel from the attention position and extending in one direction exceeds a predetermined threshold.

[0151] In the above embodiment, a signal is extracted when the pixel value of the target position is greater than or equal to the pixel value of the adjacent position, but the embodiment is not limited to this, and a signal may be extracted when the pixel value of the target position is smaller than or equal to the pixel value of the adjacent position depending on the type and format of data. That is, the processing circuit 110 may extract the image component of the target position as the image component representing the object by the extraction function 1110g, for example, if the pixel value of the target position is smaller than or equal to the pixel value of the position adjacent to the target position in one direction.

[0152] In addition, the embodiment is not limited to this, and signal extraction may not be performed when the pixel value of the target position is equal to the pixel value of the adjacent position. In this case, the processing circuit 110 uses the extraction function 1110g to extract the image component of the target position as the image component representing the object only when the pixel value of the target position is greater than the pixel value of the adjacent position in one direction relative to the target position.

[0153] As another example, the processing circuit 110 may use the extraction function 1110g so that the extraction unit compares the pixel value of each of the multiple positions of interest included in the first ultrasound image data with the pixel value of the position of interest for each direction of interest relative to the position of interest, and weights the image components of the position of interest based on the comparison results for each direction of interest.

[0154] As an example, consider a case where the processing circuit 110 performs signal extraction using four kernels, 1040, 1041, 1042, and 1043, shown in Fig. 14. In this case, the processing circuit 110, for example, sets different weights for the diagonal kernels 1040 and 1041 and the horizontal kernels 1042 and 1043. As an example, the processing circuit 110 uses the extraction function 1110g to set the weights for the diagonal kernels 1040 and 1041 to "0.3" and the weights for the horizontal kernels 1042 and 1043 to "0.2."

[0155] Next, the processing circuit 110 uses the extraction function 1110g to compare the pixel value of the position of interest with the pixel value of the adjacent position for each direction of interest, and obtains a comparison result for each direction of interest. For example, the processing circuit 110 uses the extraction function 1110g to obtain "1" if the pixel value of the position of interest and the pixel value of the adjacent position in the direction of interest satisfy a predetermined condition, and obtains "0" if the predetermined condition is not satisfied. After that, the processing circuit 110 performs weighted addition of the results obtained for each direction of interest by the extraction function 1110g. For example, when the processing circuit 110 uses the extraction function 1110g to obtain an evaluation value "1" for the directions of the kernels 1040 and 1043 and an evaluation value "0" for the directions of the kernels 1041 and 1042, the processing circuit 110 performs weighted addition of the evaluation values, and obtains a weighted addition value of 1×0.3+0×0.3+0×0.2+1×0.2=0.5.

[0156] Finally, the processing circuit 110 uses the extraction function 1110g to compare the acquired weighted sum with a threshold, and if the weighted sum is equal to or greater than the threshold, extracts the signal as a high signal point. For example, if the threshold is "0.5", the processing circuit 110 uses the extraction function 1110g to extract the signal as a high signal point.

[0157] As another example, the processing circuit 110 may use the extraction function 1110g to compare the pixel value of each of the multiple positions of interest included in the first ultrasound image data with the pixel values ​​of the positions of interest for each direction of interest relative to the position of interest, and weight the image components of the position of interest for each direction of interest.

[0158] Note that the embodiment is not limited to the above example, and the processing circuitry 110 may extract the second ultrasound image data from the first ultrasound image data using a trained model using AI (Artificial Intelligence) or the like by the extraction function 1110g. That is, the processing circuitry 110 may input the first ultrasound image data to a trained model that continuously extracts image components representing an object included in the ultrasound image data by inputting the ultrasound image data, and obtain the continuously extracted image components representing the object from the trained model.

[0159] As an example, the processing circuitry 110 extracts second ultrasound image data from the first ultrasound image data using a neural network with the extraction function 1110g. As an example, the processing circuitry 110 performs learning of the neural network using, for example, image data before blood vessel extraction as input data and image data subjected to blood vessel extraction processing by another method as output data. As another example, the processing circuitry 110 extracts image data subjected to blood vessel extraction processing from image data before blood vessel extraction as second ultrasound image data by machine learning using a clustering algorithm.

[0160] 12, the processing circuitry 110 applies the above-mentioned extraction process to each frame by the extraction function 1110g. That is, the processing circuitry 110 uses the extraction function 1110g to apply a kernel that extracts high signal points to each of the multiple frames to extract second ultrasound image data.

[0161] 12, in step S1500, the processing circuitry 110 generates third ultrasound image data using the output function 1110h based on the first ultrasound image data generated in step S1300 and the second ultrasound image data extracted in step S1400. As an example, the processing circuitry 110 uses the output function 1110h to synthesize the first ultrasound image data and the second ultrasound image data to generate third ultrasound image data. As an example, the processing circuitry 110 may output, as the second ultrasound image data, synthesized image data obtained by synthesizing the image components representing the continuously extracted object and the first ultrasound image data using the output function 1110h.

[0162] Specifically, the processing circuitry 110 generates third ultrasonic image data by performing weighted addition of the first ultrasonic image data and the second ultrasonic image data using the output function 1110h. For example, the processing circuitry 110 generates third ultrasonic image data by performing weighted addition between the first ultrasonic image data and the second ultrasonic image data, setting the weight of the first ultrasonic image data to 0.8 and the weight of the second ultrasonic image data to 0.2 using the output function 1110h. In addition, when the processing circuitry 110 extracts the second ultrasonic image data in a plurality of directions in step S1400, for example, the processing circuitry 110 may perform weighted addition while giving different weights depending on the direction of the extracted second ultrasonic image data, thereby generating third ultrasonic image data.

[0163] In step S1500, the processing circuitry 110 may use the output function 1110h to normalize the first ultrasonic image data and the second ultrasonic image data, and then combine them to generate the third ultrasonic image data. In other words, the processing circuitry 110 may use the output function 1110h to perform signal processing on each signal data so that the maximum or average signal values ​​of the first ultrasonic image data and the second ultrasonic image data are approximately equal, and then combine them to generate the third ultrasonic image data.

[0164] As another example, the processing circuitry 110 may correct the first ultrasonic image data using the second ultrasonic image data through the output function 1110h to generate third ultrasonic image data by correcting the first ultrasonic image data. That is, the processing circuitry 110 may output, through the output function 1110h, corrected image data obtained by performing correction processing on the first ultrasonic image data based on image components representing the continuously extracted object as second ultrasonic image data.

[0165] As an example, the processing circuit 110 may generate third ultrasound image data by correcting the first ultrasound image data by replacing data of high signal points in the first ultrasound image data, where second ultrasound image data exists, with the second ultrasound image data, using the output function 1110h.

[0166] Note that the embodiment is not limited to the above example, and the processing circuitry 110 may additionally perform various processes on the second ultrasound image data or the third ultrasound image data using the output function 1110h.

[0167] As an example, the processing circuitry 110 may perform spatial filtering such as noise removal on the second ultrasound image data generated in step S1400 by the output function 1110h, or apply a smoothing filter in the spatial or temporal direction, and then generate third ultrasound image data in step S1500 using signal data on which spatial filtering has been performed or on which a smoothing filter has been applied in the spatial or temporal direction. As another example, the processing circuitry 110 may perform frame-wise processing on the second ultrasound image data generated in step S1400 by the output function 1110h, for example, replacing the signal data with a moving average value of a predetermined number of frames, and then generate third ultrasound image data in step S1500 using the signal data after spatial filtering. The processing circuitry 110 may perform these spatial filtering processes or frame-wise processes using AI by the output function 1110h. As an example, the processing circuit 110 may perform spatial filtering processing on the second ultrasound image data using the output function 1110h based on a neural network that has been trained using low-quality images as input data and high-quality images as output data.

[0168] As another example, the spatial filtering process and the frame direction process may be performed on the generated third ultrasound image data. That is, the processing circuitry 110 may perform a spatial filtering process such as noise removal or a frame direction process, for example, an operation of replacing signal data with a moving average value of a predetermined number of frames, on the third ultrasound image data generated in step S1400 by the output function 1110h. The processing circuitry 110 may perform the spatial filtering process or the frame direction process on the third ultrasound image data by the output function 1110h using AI.

[0169] As another example, the processing circuit 110 may output image data including image components representing the continuously extracted object as second ultrasound image data via the output function 1110h.

[0170] The processing circuitry 110 causes the display 135 to display an ultrasound image based on the generated third ultrasound image data by the display control function 114. The processing circuitry 110 may also cause the display 135 to display the second ultrasound image data by the display control function 114.

[0171] 12, the processing circuit 110 performs the process of extracting high signal points for each frame by the extraction function 1110g in step S1400. However, the embodiment is not limited to this. That is, the processing circuit 110 may perform the kernel application process in step S1400 on data after the frame addition process has been performed in advance by the extraction function 1110g.

[0172] A flowchart of the embodiment is shown in Fig. 15. Note that the process flow shown in Fig. 15 is similar to that in Fig. 12 except for the addition of step S1350, so that repeated explanation of the processes other than step S1350 will be omitted.

[0173] In step S1350, the processing circuitry 110 acquires, as first ultrasound image data, summed image data obtained by summing a plurality of time-sequential frame data obtained by performing the collected ultrasound scan, using the acquisition function 110f. In step S1400, the processing circuitry 110 performs, using the extraction function 1110g, a process of applying the above-mentioned kernel to the first ultrasound image data, which is the data that has been summed, and thereafter performs similar processes. As a result, even when the signal strength of each frame is not sufficient, the image quality of the output image can be improved by increasing the signal strength by performing frame summation.

[0174] An ultrasound image 29 output by the method according to the embodiment will be described with reference to Figs. 16A to 17C. Figs. 16A and 17A are ultrasound images obtained by using the SMI (superb micro-vascular imaging) method as a first comparative example. Figs. 16B and 17B are ultrasound images obtained by using the super-resolution imaging method described in Fig. 11 as a second comparative example. Figs. 16C and 17C are ultrasound images output by the method according to the embodiment. Compared with the SMI method as the first comparative example, the method according to the embodiment can visualize blood flow with high resolution, and compared with the second comparative example, can visualize peripheral blood flow in detail and with continuity.

[0175] As described above, the image processing device 100 according to the embodiment can improve the visibility of an object, for example by emphasizing finer blood flows.

[0176] However, the embodiment is not limited to this.

[0177] As the kernel for peak detection according to the embodiment, a case where a kernel extending in a predetermined direction of 3×1 is used has been described, but the embodiment is not limited to the above example. As the kernel for peak detection, for example, as shown in the kernel 1061 of FIG. 18, a filter that extracts only the 1st, 3rd, and 5th squares from the left of the 5×1 squares may be used as the kernel, and the extracted signal may be compared with adjacent signal values ​​to perform signal extraction. That is, as the kernel for peak detection according to the embodiment, a kernel that acts on pixels other than adjacent pixels may be used. When such a kernel 1061 is applied to the pre-extraction signal 1060, for example, a signal with a signal value of "10" is extracted as shown in FIG. 18. Also, when a kernel 1062 obtained by shifting such a kernel 1061 is applied to the pre-extraction signal 1060, a signal with a signal value of "8" is extracted. Therefore, by using such a kernel, a signal with a signal value of "8" and a signal with a signal value of "10" can be extracted, and peak extraction can be performed more flexibly compared to the conventional method. In other words, in the conventional method, image components representing an object are extracted discretely, whereas in the method of the embodiment, image components representing an object are extracted continuously.

[0178] Also, the type of data of the first ultrasonic image data acquired by the processing circuit 110 using the acquisition function 110f in step S1300 can be various data other than Doppler image data. As an example, in step S1300, the processing circuit may acquire B-mode image data as the first ultrasonic image data using the acquisition function 110f. Since B-mode image data has a characteristic that the signal value is large at the peripheral portion of an organ, the peripheral portion of the organ can be highlighted and depicted by acquiring and processing the B-mode image data as the first ultrasonic image data. Also, in the embodiment, the case where the frame data acquired by the processing circuit 110 using the acquisition function 110f is a blood flow image has been described, but the embodiment is not limited to this. The frame data acquired by the processing circuit 110 using the acquisition function 110f may be a received image, a measurement image after DAS, or a blood flow image after clutter removal. In this case, the processing circuit 110 may acquire a blood flow image obtained by adding a plurality of frames of received images / measurement images, etc., as the first ultrasonic image data using the acquisition function 110f.

[0179] In addition, in step S1100, the processing circuitry 110 may acquire data for each frequency, instead of data for each frame, by the acquisition function 110f. In this case, in step S1200, the processing circuitry 110 acquires first ultrasound image data by adding data for each frequency, instead of performing addition processing for the frame, by the acquisition function 110f.

[0180] The first ultrasound data may be data to which a smoothing filter has been applied. That is, the processing circuit 110 may acquire, as the first ultrasound image data, by using the acquisition function 110f, data of a plurality of frames successive in the time direction obtained based on the result of an ultrasound scan of the subject, by applying a smoothing filter in the spatial direction or the time direction.

[0181] (Fourth embodiment) Next, a fourth embodiment will be described. The configuration of the ultrasound diagnostic apparatus 10 according to the fourth embodiment is similar to the configuration of the third embodiment shown in FIG. 9 except for the processing circuit 110, so that repeated description will be omitted.

[0182] 19 shows the configuration of an image generating function 111 included in the processing circuit 110 in the fourth embodiment. More specifically, the image generating function 111 includes an acquisition function 110f, an extraction processing function 1110g, and an output function 1110h. More specifically, the acquisition function 110f includes a received signal storage function 1110a, a delay-and-sum processing function 1110b, a signal storage function 1110c, a B-mode processing function 1110d, a displacement amount correction function 1110e, a Doppler processing function 1110i, and the like. The extraction processing function 1110g includes a division function 1110g1, an extraction function 1110g2, a restoration processing function 1110g3, and an accumulation processing function 1110g4.

[0183] In the embodiment, the processing functions and learned models performed by the received signal storage function 1110a, the phasing addition processing function 1110b, the signal storage function 1110c, the B-mode processing function 1110d, the displacement amount correction function 1110e, the acquisition function 110f, the extraction processing function 1110g, the division function 1110g1, the extraction function 1110g2, the restoration processing function 1110g3, the integration processing function 1110g4, the output function 1110h, the Doppler processing function 1110i, the image generation function 111, the image processing function 112, the control function 113, the display control function 114, etc. are stored in the memory 132 in the form of a program executable by a computer. The processing circuitry 110 is a processor that realizes a function corresponding to each program by reading and executing the program from the memory 132. In other words, the processing circuitry 110 in a state in which each program has been read has each function shown in the processing circuitry 110 in FIG. 9 or the image generation function 111 in FIG. 19.

[0184] 9 and 19, the image generation function 111, the image processing function 112, the control function 113, the display control function 114, the acquisition function 110f, the extraction processing function 1110g, the division function 1110g1, the extraction function 1110g2, the restoration processing function 1110g3, the accumulation processing function 1110g4, and the output function 1110h are examples of the image generation unit, the processing unit, the control unit, the display control unit, the acquisition unit, the extraction processing unit, the division unit, the extraction unit, the restoration processing unit, the accumulation processing unit, and the output unit, respectively.

[0185] (Configuration of the receiving signal processing block) 19 is a block diagram showing an example of the image generating function 111. The image generating function 111 is composed of an acquisition function 110f, an extraction processing function 1110g, and an output function 1110h. The acquisition function 110f is composed of a received signal storage function 1110a, a phasing and summing processing function 1110b, a signal storage function 1110c, a B-mode processing function 1110d, a displacement amount correction function 1110e, and a Doppler processing function 1110i. The extraction processing function 1110g is composed of a division function 1110g1, an extraction function 1110g2, a restoration processing function 1110g3, and an accumulation processing function 1110g4. The received signal storage function 1110a stores the received signal received by the receiving circuit 11. Depending on the device configuration and the type of received signal, the received signal storage function 1110a may not store the received signal received by the receiving circuit 11, but may store the signal in the signal storage function 1110c after the phasing and summing function 1110b described later. The received signal storage function 1110a may be composed of a block common to the signal storage function 1110c described later, and may store the received signal from the receiving circuit 11 and the received signal after the phasing and summing function 1110b.

[0186] The delay and sum processing function 1110b performs delay and sum processing and quadrature detection processing on the reception signal obtained by the reception circuit 11, and the processed reception signal is stored by the signal storage function 1110c. The delay and sum processing is a process of forming a reception ultrasonic beam by changing the delay time and weight for each transducer 101 and adding up the reception signals of multiple transducers 101, and is also called delay and sum (DAS) beamforming. The quadrature detection processing is a process of converting the reception signal into an in-phase signal (I signal) and a quadrature signal (Q signal) of the baseband. The delay and sum processing and quadrature detection processing are performed based on the element arrangement and various conditions for image generation (aperture control, signal filter) input by the control function 113. The reception signal after the delay and sum processing and quadrature detection processing is stored by the signal storage function 1110c. Here, a typical example of DAS beamforming is shown, but any process that forms a reception ultrasonic beam, such as adaptive beamforming, model-based processing, and processing using machine learning, may be used.

[0187] The reception signal (digital data) obtained by the reception circuit 11 is also called RAW data. The reception signal (digital data) obtained by the phasing and summing processing function 1110b is also called RF data. The RAW data and RF data are examples of measurement data acquired based on the reception signal of the ultrasound reflected inside the living body.

[0188] The B-mode processing function 1110d performs envelope detection processing, logarithmic compression processing, etc. on the received signals for generating B-mode images stored by the signal storage function 1110c to generate image data in which the signal intensity at each point in the observation region is expressed as luminance intensity. The B-mode processing function 1110d may also perform B-mode processing on the received signals whose displacement has been corrected by the displacement correction function 1110e.

[0189] The displacement amount correction function 1110e calculates the amount of tissue displacement caused by body movement between frames from the received signals acquired over multiple frames. This is generally calculated by a block matching calculation called a speckle tracking method. A region of interest is set within a frame, and the region of interest between frames is tracked by correlation to calculate the displacement amount of the region of interest. A plurality of regions of interest are set within a frame to calculate the displacement amount of the entire frame. Here, an example of a method using correlation between frames is shown, but any method may be used as long as it can calculate the displacement amount of the region of interest. In the case of an ultrasonic signal, it is called speckle tracking because it tracks speckles, which are scattered images of ultrasonic waves reflected from scatterers in the body tissue. The correlation calculation of the region of interest between frames may be performed on the received signal after any of delay and sum processing, quadrature detection processing, and envelope detection processing. In addition, the correlation calculation may be performed on the time waveform of the received signal, or may be performed on frequency space data obtained by performing a discrete Fourier transform on the received signal. The displacement amount correction function 1110e corrects the displacement amount by moving the received signal with respect to a reference frame using the calculated displacement amount. The amount of displacement to be corrected may be a uniform value for the entire frame, such as the average value of the amount of displacement for each region of interest, or may be changed within the frame, such as for each region of interest. The amount of displacement for the entire frame calculated for each region of interest may be interpolated in the time direction within the frame and in the data strings of multiple frames, using linear interpolation, spline interpolation, or the like. When correcting the amount of displacement, the received signal may be similarly interpolated and then moved to allow for more fine correction.

[0190] The Doppler processing function 1110i extracts blood flow data from the reception signals for generating a blood flow image stored by the signal storage function 1110c. The Doppler processing function 1110i may also perform Doppler processing on the reception signals whose displacement has been corrected by the displacement correction function 1110e. The Doppler processing function 1110i extracts blood flow data based on the Doppler effect of the object within the scanning range by frequency analyzing the reception signals for generating a blood flow image stored by the signal storage function 1110c.

[0191] In generating blood flow data by the Doppler method, a series of received signal data of multiple frames is acquired in the time direction for the same measurement position. The Doppler processing function 1110i applies an MTI (Moving Target Indicator) filter to the received signal data series. This reduces information (clutter image components) derived from tissues that are stationary between frames or tissues with little movement, and extracts information derived from blood flow (blood flow image components). The processing circuit 110 calculates blood flow data such as blood flow velocity, variance, and power from the blood flow image components using the Doppler processing function 1110i.

[0192] The MTI filter may be a filter with fixed filter coefficients, such as a Butterworth type IIR (infinite impulse response) filter or a polynomial regression filter. The MTI filter may be an adaptive filter that changes coefficients according to an input signal using eigenvalue decomposition or singular value decomposition. Alternatively, the processing circuit 110 may use the Doppler processing function 1110i to decompose the received signal into one or more bases using eigenvalue decomposition or singular value decomposition, extract only a specific base, and remove clutter image components. The processing circuit 110 may also use the Doppler processing function 1110i to obtain a velocity vector for each coordinate in the image and obtain a blood flow vector representing the magnitude and direction of the blood flow by using a method such as a vector Doppler method, a speckle tracking method, or a vector flow mapping method. In addition to the methods exemplified here, any method may be used as long as it can extract or emphasize information derived from blood flow contained in the received signal (measurement data), or can remove or reduce information derived from tissue.

[0193] The processing circuit 110 acquires, by the acquisition function 110f, data of a plurality of frames consecutive in the time direction obtained based on the result of an ultrasound scan on the subject as the first ultrasound image data. As another example, the processing circuit 110 acquires, by the acquisition function 110f, a plurality of frames of blood flow images (here, power Doppler images) generated by the Doppler processing function 1110i, and acquires, by adding these, added image data obtained as the first ultrasound image data. Note that the received image or the measured image may be treated as frame data, and a blood flow image obtained by adding the plurality of frames may be used as the first ultrasound image data.

[0194] The processing circuitry 110 also performs a process of continuously extracting image components representing an object from the first ultrasonic image data using an extraction processing function 1110g. The details of the extraction processing function 1110g will be described later. The processing circuitry 110 also performs a process of outputting second ultrasonic image data based on the image components representing the object continuously extracted from the first ultrasonic image data using an output function 1110h.

[0195] The image data output after processing by the B-mode processing function 1110d, the Doppler processing function 1110i, and the extraction processing function 1110g is processed by the image generation function 111 shown in Figure 9, and then finally displayed on the display 135.

[0196] The processing circuit 110 having the image generating function 111 may be configured with one or more processors and a memory. In that case, each function shown in FIG. 19 is realized by a computer program. For example, each function can be provided by a CPU reading and executing a program stored in the memory. The processing circuit 110 having the image generating function 111 may include a processor (GPU, FPGA, etc.) in charge of the calculation of the B-mode processing function 1110d, the displacement amount correction function 1110e, the Doppler processing function 1110i, and the extraction processing function 1110g in addition to the CPU. The memory may include a memory for non-temporarily storing a program, a memory for temporarily storing data such as a received signal, a working memory used by the CPU, etc.

[0197] Next, the background of the fourth embodiment will be described. As already described in the third embodiment, one of the super-resolution techniques for blood flow signals without using a contrast agent is a method of extracting a high signal area that occurs with a low frequency for each frame from a blood flow signal after passing through a wall filter, generating a signal with a higher resolution than the resolution limit of ultrasound, and accumulating this between frames to obtain a blood flow signal with a higher resolution than a conventional blood flow signal.

[0198] However, with this method, blood flow may become discontinuous or may not be depicted smoothly.

[0199] In view of this background, the image processing device 100 as a medical information processing device according to the embodiment includes a processing circuit 110. The processing circuit 110 divides first ultrasonic image data into a plurality of second ultrasonic image data by a division function 1110g1. The processing circuit 110 extracts third ultrasonic image data by performing peak extraction from each of the second ultrasonic image data by an extraction function 1110g2. The processing circuit 110 generates fourth ultrasonic image data by allocating the third ultrasonic image data to a corresponding position on the first ultrasonic image data by a restoration processing function 1110g3. The processing circuit 110 integrates the fourth ultrasonic image data to generate fifth ultrasonic image data by an integration processing function 1110g4.

[0200] Moreover, the ultrasound diagnostic device 10 according to the embodiment includes a transmission / reception circuit (transmission circuit 9 and reception circuit 11) as an execution unit, and a processing circuit 110. The execution unit causes the ultrasound probe 5 to execute an ultrasound scan on the subject. The processing circuit 110 divides the first ultrasound image data into a plurality of second ultrasound image data by a division function 1110g1. The processing circuit 110 extracts third ultrasound image data by performing peak extraction from each of the second ultrasound image data by an extraction function 1110g2. The processing circuit 110 generates fourth ultrasound image data by allocating the third ultrasound image data to a corresponding position on the first ultrasound image data by a restoration processing function 1110g3. The processing circuit 110 integrates the fourth ultrasound image data by an accumulation processing function 1110g4 to generate fifth ultrasound image data.

[0201] In addition, the program according to the embodiment causes a computer to execute a process of dividing first ultrasonic image data into a plurality of second ultrasonic image data, extracting third ultrasonic image data by performing peak extraction from each of the second ultrasonic image data, assigning the third ultrasonic image data to corresponding positions on the first ultrasonic image data to generate fourth ultrasonic image data, and integrating the fourth ultrasonic image data to generate fifth ultrasonic image data.

[0202] This makes it possible to extract continuous objects, enabling imaging that emphasizes objects such as blood flow.

[0203] The processing performed by the image processing device 100 as the medical information processing device according to the embodiment will be described with reference to Fig. 20 to Fig. 24. Fig. 20 is a flowchart illustrating the flow of the processing performed by the image processing device 100 according to the embodiment.

[0204] Note that, unlike FIG. 28 in which continuous components are extracted after addition processing is performed between frames, FIG. 20 performs extraction processing for each frame to extract continuous components.

[0205] First, in step S2100, the processing circuitry 110 collects multiple frames of data to be processed. That is, the processing circuitry 110 uses the acquisition function 110f to acquire multiple frames of frame data by performing a scan on a subject by the ultrasound diagnostic device 10. That is, the processing circuitry 110 uses the acquisition function 110f to acquire multiple frames of frame data that are continuous in the time direction and obtained by performing an ultrasound scan.

[0206] In other words, the processing circuit 110 uses the acquisition function 110f to set a measurement position so as to include a region in which blood flow information is to be observed, and repeats ultrasonic transmission and reception while fixed at the same measurement position to acquire a reception signal including a data string of multiple frames in the time direction. The number of frames of the reception signal when generating a super-resolution blood flow image according to this embodiment is generally greater than that when generating a normal Doppler image. For example, the number of frames (number of packets) of the reception signal when generating a normal Doppler image is about 5 to 20, whereas the number of frames of the reception signal when generating a super-resolution blood flow image is at least 100 frames or more, preferably several hundred to tens of thousands.

[0207] Here, the frame rate of the ultrasound diagnostic device 10 is about several hundred Hz to several thousand Hz, depending on the model and the measurement method. Therefore, the measurement time of the received signal to generate a super-resolution blood flow image is about several hundred msec to several tens of sec. The received signal including a data string of multiple frames is subjected to phasing addition and quadrature detection processing by the phasing addition processing function 1110b, and is stored by the signal storage function 1110c.

[0208] Furthermore, one frame in the data sequence may be a received signal obtained by transmitting and receiving ultrasound once to include the observation area, or may be a sum of received signals transmitted and received multiple times to include the observation area. For example, a plane wave or diverging wave is transmitted to include the observation area, and multiple received signals with different transmission angles are added together to obtain one frame of data.

[0209] Next, in step S2200, the processing circuitry 110 uses the displacement amount correction function 1110e to calculate the amount of tissue displacement between frames due to body movement, etc., from the received signal including data strings of multiple frames. Then, the processing circuitry 110 uses the calculated displacement amount to correct the displacement amount by moving the received signal so that its position is aligned within the frame where the integration process described later is performed, using the displacement amount correction function 1110e.

[0210] Here, the reference frame for calculating the displacement may be only one frame in the entire data sequence, the reference frame may be changed depending on the time direction position (i.e., multiple reference frames may be provided), or the previous frame in the adjacent frames may be used as the reference frame. The reference frame may be selected arbitrarily from the data sequence, and for example, any of the first frame, the middle frame, and the last frame may be used as the reference frame.

[0211] Next, in step S2300, the processing circuit 110 uses the Doppler processing function 1110i to apply an MTI filter to the received signal including the data sequence of multiple frames corrected for the displacement amount, thereby reducing clutter image components and extracting image components derived from blood flow to generate blood flow images of multiple frames. At this time, a part of the data sequence may be extracted and used to design the MTI filter, or the entire data sequence may be used.

[0212] Furthermore, it is preferable that the parameters of the MTI filter (cutoff frequency, number of packets / overlap of frames to be extracted, etc.) can be adjusted automatically or by the user according to the properties of the received signal, the subject to be measured, etc. In this way, the processing circuitry 110 generates first ultrasound image data. In other words, by the processes of steps S2100 to S2300, the processing circuitry 110 acquires the first ultrasound image data by the acquisition function 110f based on data of multiple frames that are continuous in the time direction and obtained based on the results of an ultrasound scan on the subject.

[0213] Next, in step S2400, the processing circuitry 110 uses the extraction processing function 1110g to extract fifth ultrasound image data by extracting continuous components in a direction representing the object from the first ultrasound image data obtained based on the result of the ultrasound scan of the subject obtained in the processing up to step S2300. In an embodiment in which the fifth ultrasound image data is extracted by applying extraction processing of high signal points for each frame as shown in Fig. 20, the processing circuitry 110 uses the extraction processing function 1110g to extract the fifth ultrasound image data by applying a kernel that extracts high signal points for each of a plurality of frames.

[0214] In other words, the processing circuit 110 uses the extraction processing function 1110g to extract image components of the positions of interest included in the first ultrasound image data for each of the multiple frames as image components representing the object. Here, the object refers to a structure of interest, and includes at least one of blood, body tissue, and contrast agent. In addition, the direction representing the object means, for example, the direction of blood flow when the object is blood. That is, the processing circuit 110 uses the extraction processing function 1110g to generate fifth ultrasound image data by extracting components that are continuous in the direction of blood flow from the first ultrasound image data. This makes it possible to depict the structure of the object, for example, the structure of a blood vessel, with higher image quality.

[0215] This process will be described with reference to Figures 21 and 22. Figure 21 is a diagram illustrating the process of step S2400 in Figure 20 in more detail. Also, Figure 22 is a diagram illustrating the flow of the process of step S2400.

[0216] 22, image data 2020 indicates the first ultrasound image data to be processed in step S2400. Pixels 2020a, 2020b, 2020c, 2020d, 2020e, 2020f, 2020g, 2020h, 2020i, 2020j, 2020k, and 2020l indicate each pixel of the image data 2020.

[0217] First, in step S2410, the processing circuitry 110 divides the first ultrasonic image data into a plurality of second ultrasonic image data by the division function 1110g1. As an example, the processing circuitry 110 divides the image data 2020, which is the first ultrasonic image data, into four sets of second ultrasonic image data by performing data division processing while thinning out the data at equal intervals by the division function 1110g1. As an example, the processing circuit 110 uses the division function 110g1 to perform data division processing on image data 2020, which is the first ultrasound image data, by skipping one piece of data vertically and horizontally, and divides the data into, for example, image data 2021a including pixels 2020a, 2020c, 2020e, 2020g, etc., image data 2021b including pixels 2020b, 2020d, 2020f, 2020h, etc., image data 2021c including pixels 2020i, 2020k, etc., and image data 2021d including pixels 2020j, 2020l, etc., as shown in the figure. That is, the processing circuit 110 uses the division function 1110g1 to divide the image data 2020, which is the first ultrasound image data, into two parts vertically and horizontally, forming a 2x2 division, and divides it into four multiple second ultrasound image data items, image data 2021a, 2021b, 2021c, and 2021d.

[0218] In the above example, the processing circuitry 110 divides the image data 2020 into two vertically and horizontally into 2×2 pieces by the division function 1110g1, and divides the image data into four pieces of second ultrasound image data. However, the embodiment is not limited to this, and the processing circuitry 110 may divide the image data into three vertically and horizontally into 3×3 pieces by the division function 1110g1, and divide the image data into nine pieces of second ultrasound image data, or may divide the image data into four vertically and horizontally into 4×4 pieces by the division function 1110g1, and divide the image data into 16 pieces of second ultrasound image data. In addition, the embodiment is not limited to this, and the processing circuitry 110 may divide the image data into two vertically only into 2×1 pieces by the division function 1110g1, and divide the image data into two pieces of second ultrasound image data, or may divide the image data into two horizontally only into 1×2 pieces by the division function 1110g1.

[0219] Next, in step S2420, the processing circuitry 110 causes the extraction function 1110g2 to perform peak extraction from each of the second ultrasound image data to extract third ultrasound image data.

[0220] As an example of the peak detection process in step S2420, the processing circuit 110 uses the extraction function 1110g2 to extract a high signal point using a kernel that spreads over a total of nine signal points, for example, 3×3, including a point of interest and eight signal points adjacent to the point of interest. In this case, the processing circuit 110 uses the extraction function 1110g2 to extract the point of interest as a high signal point only when the point of interest has a higher signal value than any of the signal points in the eight adjacent squares.

[0221] As another example of the peak detection processing of step S2420, the processing circuit 110 extracts third ultrasound image data from the second ultrasound image data using a kernel extending in a particular direction, such as kernel 4 having a size of 3×1, by the extraction function 1110g2.

[0222] As another example of the peak detection process in step S2420, the processing circuit 110 extracts third ultrasound image data from the second ultrasound image data using a trained model based on machine learning through the extraction function 1110g2.

[0223] In this manner, the processing circuitry 110 extracts the image data 2022a, 2022b, 2022c, and 2022d, which are the third ultrasound image data, from the image data 2021a, 2021b, 2021c, and 2021d, which are the second ultrasound image data, by the extraction function 1110g2.

[0224] Next, in step S2430, the processing circuit 110 uses the restoration processing function 1110g3 to allocate the third ultrasonic image data to the corresponding positions on the first ultrasonic image data to generate fourth ultrasonic image data. That is, the processing circuit 110 uses the restoration processing function 1110g3 to allocate the image data 2022a, 2022b, 2022c, and 2022d, which are the third ultrasonic image data, to the corresponding positions on the first ultrasonic image data to generate image data 23, which is the fourth ultrasonic image data.

[0225] Next, in step S2440, the processing circuitry 110 uses the integration processing function 1110g4 to integrate the fourth ultrasound image data to generate fifth ultrasound image data. Next, in step S2450, the processing circuitry 110 uses the output function 1110h to output the fifth ultrasound image data.

[0226] The processing of step S2400 has been described above. In the embodiment shown in Fig. 20, the processing circuitry 110 applies the above-mentioned extraction processing to each frame by the extraction processing function 1110g. That is, the processing circuitry 110 applies a kernel that extracts high signal points to each of the multiple frames by the extraction processing function 1110g to extract fifth ultrasound image data. The processing circuitry 110 adds the fifth ultrasound image data in each frame as necessary to generate image data 24 to be output.

[0227] The effect of the high signal point extraction process in step S2400 according to the embodiment will be described with reference to Fig. 23 and Fig. 24. Fig. 23 is a conceptual diagram showing a high signal point extraction method according to a comparative example, while Fig. 24 is a conceptual diagram showing a high signal point extraction method according to the embodiment.

[0228] Fig. 23 shows a high signal point extraction method according to a comparative example, which does not perform spatial division and performs high signal point extraction. Each point in Fig. 23 represents a signal point, and a curve 2030 is a line connecting signal values. When the processing circuit 110 performs signal extraction using the extraction function 1110g2 in step S2420, the signal point 30a and the signal point 30b are extracted as high signal points.

[0229] In contrast, FIG. 24 shows a high signal point extraction method according to the embodiment, which performs spatial division to extract high signal points. Each point in FIG. 24 represents each signal point, and curves 2031 and 2032 are lines connecting signal values ​​in each image data that has been divided in step S2410. When the processing circuit 110 performs signal extraction using the extraction function 1110g2 in step S2420 for each image data that has been divided in step S2410, signal points 2031a, 2031b and signal points 2032a, 2032b are extracted as high signal points. That is, when the method according to the embodiment is used, it is possible to extract high luminance signal areas over a wider range than in the comparative example. That is, in the method according to the embodiment, image components representing the object are continuously extracted, and peak pixel values ​​can be continuously extracted. The positions of interest for peak determination are basically pixel units, but may be group units having multiple pixels. When peak determination is performed on a group basis, the pixel value of the group may be an average value or an integrated value of the pixel values ​​of the pixels included in the groups.

[0230] 20, in step S2500, the processing circuitry 110 generates ultrasound image data that is composite image data by performing a synthesis process on the first ultrasound image data generated in step S2300 and the fifth ultrasound image data extracted in step S2400 using the output function 1110h. As an example, the processing circuitry 110 outputs the synthetic image data obtained by performing a synthesis process on the first ultrasound image data and the fifth ultrasound image data using the output function 1110h.

[0231] Specifically, the processing circuit 110 generates composite image data by performing weighted addition of the first ultrasonic image data and the fifth ultrasonic image data using the output function 1110h. For example, the processing circuit 110 sets the weight of the first ultrasonic image data to 0.8 and the weight of the fifth ultrasonic image data to 0.2 using the output function 1110h, and performs weighted addition between the first ultrasonic image data and the second ultrasonic image data to generate composite image data.

[0232] In step S2500, the processing circuitry 110 may use the output function 1110h to normalize the first ultrasonic image data and the fifth ultrasonic image data, and then combine them to generate composite image data. In other words, the processing circuitry 110 may use the output function 1110h to perform signal processing on each signal data so that the maximum or average signal values ​​of the first ultrasonic image data and the fifth ultrasonic image data are approximately equal, and then combine them to generate composite image data.

[0233] As another example, the processing circuitry 110 may correct the first ultrasonic image data using the fifth ultrasonic image data by the output function 1110h to generate corrected image data by correcting the first ultrasonic image data. That is, the processing circuitry 110 may output, by the output function 1110h, the corrected image data obtained by correcting the first ultrasonic image data based on the fifth ultrasonic image data, which is an image component representing the continuously extracted object.

[0234] Note that the embodiment is not limited to the above-mentioned example, and the processing circuitry 110 may additionally perform various processes on the first ultrasound image data or the fifth ultrasound image data using the output function 1110h.

[0235] As an example, the processing circuitry 110 may perform spatial filtering such as noise removal on the fifth ultrasound image data generated in step S2400 by the output function 1110h, or apply a smoothing filter in the spatial or temporal direction, and then generate ultrasound image data in step S2500 using signal data on which spatial filtering has been performed or on which a smoothing filter has been applied in the spatial or temporal direction. As another example, the processing circuitry 110 may perform frame-wise processing on the fifth ultrasound image data generated in step S2400 by the output function 1110h, for example, replacing the signal data with a moving average value of a predetermined number of frames, and then generate ultrasound image data in step S2500 using the signal data after spatial filtering. The processing circuitry 110 may perform these spatial filtering processes or frame-wise processes using AI by the output function 1110h. As an example, the processing circuit 110 may perform spatial filtering processing on the fifth ultrasound image data using the output function 1110h based on a neural network that has been trained using low-quality images as input data and high-quality images as output data.

[0236] As another example, the spatial filtering process and the frame direction process may be performed on the generated composite ultrasound image data, etc. That is, the processing circuitry 110 may perform a spatial filtering process such as noise removal or a frame direction process, for example, an operation of replacing signal data with a moving average value of a predetermined number of frames, on the composite ultrasound image data, etc., generated in step S2500, by using the output function 1110h. The processing circuitry 110 may also perform the spatial filtering process or the frame direction process on the composite ultrasound image data by using AI by using the output function 1110h.

[0237] The processing circuitry 110 causes the display control function 114 to display the generated output ultrasound image on the display 135. The processing circuitry 110 may also cause the display control function 114 to display the fifth ultrasound image data on the display 135.

[0238] An ultrasound image 29 output by the method according to the embodiment will be described with reference to Figs. 25 to 27. Fig. 25 is a first comparative example, and is an ultrasound image obtained using the super-resolution imaging method described in Fig. 11. Fig. 26 is an ultrasound image obtained using the super-resolution imaging method using the method according to the embodiment. Fig. 27 is a second comparative example, and is an ultrasound image using the power Doppler method. In the method according to the embodiment, blood flow is depicted more smoothly compared to the first comparative example. Also, in Figs. 25 and 26, which are ultrasound images using the super-resolution imaging method, blood flow is depicted more finely and in a higher resolution image compared to Fig. 27, which is an ultrasound image of conventional blood flow imaging.

[0239] 20, the processing circuit 110 performs the process of extracting high signal points for each frame by the extraction processing function 1110g in step S2400. However, the embodiment is not limited to this. That is, the processing circuit 110 may perform the kernel application process in step S2400 on data after the frame addition process has been previously performed by the extraction processing function 1110g.

[0240] A flowchart of the embodiment is shown in Fig. 28. Note that the process flow shown in Fig. 28 is similar to that in Fig. 20 except for the addition of step S2350, so repeated explanation of the processes other than step S2350 will be omitted.

[0241] In step S2350, the processing circuitry 110 acquires, as first ultrasound image data, summed image data obtained by summing a plurality of time-sequential frame data obtained by performing the collected ultrasound scan using the acquisition function 110f. In step S2400, the processing circuitry 110 performs the above-mentioned extraction process on the first ultrasound image data, which is the data that has been subjected to the summation process, using the extraction process function 1110g, and performs similar processes thereafter. As a result, even when the signal strength of each frame is not sufficient, the image quality of the output image can be improved by increasing the signal strength by performing frame summation.

[0242] As described above, the image processing device 100 serving as a medical information processing device according to the embodiment can improve the visibility of an object, for example by emphasizing finer blood flows.

[0243] The embodiments are not limited to the above examples.

[0244] The type of data of the first ultrasonic image data acquired by the processing circuit 110 using the acquisition function 110f in step S2300 can be various data other than Doppler image data. As an example, in step S2300, the processing circuit may acquire B-mode image data as the first ultrasonic image data using the acquisition function 110f. Since B-mode image data has a characteristic that the signal value is large at the peripheral portion of an organ, the peripheral portion of the organ can be highlighted and depicted by acquiring and processing the B-mode image data as the first ultrasonic image data. In addition, in the embodiment, the case where the frame data acquired by the processing circuit 110 using the acquisition function 110f is a blood flow image has been described, but the embodiment is not limited to this. The frame data acquired by the processing circuit 110 using the acquisition function 110f may be a received image, a measurement image after DAS, or a blood flow image after clutter removal. In this case, the processing circuit 110 may acquire a blood flow image obtained by adding a plurality of frames of received images / measurement images, etc., as the first ultrasonic image data using the acquisition function 110f.

[0245] In step S2100, the processing circuitry 110 may acquire data for each frequency, instead of data for each frame, by the acquisition function 110f. In this case, in step S2200, the processing circuitry 110 acquires the first ultrasound image data 21 by adding data for each frequency, instead of performing addition processing for the frame, by the acquisition function 110f.

[0246] The first ultrasound data may be data to which a smoothing filter has been applied. That is, the processing circuit 110 may acquire, as the first ultrasound image data, by using the acquisition function 110f, data of a plurality of frames successive in the time direction obtained based on the result of an ultrasound scan of the subject, by applying a smoothing filter in the spatial direction or the time direction.

[0247] Furthermore, the extraction of the local peak position in the first to fourth embodiments and the like is not limited to the above-mentioned method, and may be performed by other methods. For example, the local peak position may be extracted by performing peak sharpening by applying a nonlinear function to the signal value in the frame. In such a case, for example, the extraction function 1110g first performs a process of resampling the first ultrasonic image data to increase the pixel density and increase the effective resolution. Here, the resampling may be, for example, replacing each pixel with a plurality of smaller pixels. Furthermore, the signal value of each pixel after replacement may be interpolated from the original signal value (signal value before replacement) by, for example, bicubic interpolation or the like.

[0248] Furthermore, the extraction function 1110g sharpens the local peaks by raising each signal value of the first ultrasound data after resampling to a power (e.g., 8th power, 12th power, etc.). The extraction function 1110g extracts local peak positions by performing, for example, threshold processing on the signal values ​​after the power. That is, the extraction function 1110g extracts identification information in which positions extracted as local peaks are represented by "1" and positions not extracted as local peaks are represented by "0". The extraction function 1110g performs the local peak sharpening process on a plurality of first ultrasound data, thereby extracting identification information from each of the first ultrasound data. Note that the target of the local peak sharpening process described above is not limited to the first ultrasound data, and may be frame data.

[0249] In addition, the first to fourth embodiments may be appropriately combined with each other. As an example, the method of performing the extraction process in step S300 in the first or second embodiment may be the method described in the third or fourth embodiment.

[0250] Regarding the above embodiment, the following supplementary notes are disclosed as one aspect and optional features of the invention.

[0251] (Appendix 1) An ultrasonic diagnostic device 10 provided in one aspect of the present invention includes a processing circuit 110. The processing circuit 110 acquires first signal data of a plurality of frames by scanning a subject with an acquisition function 110f. The processing circuit 110 extracts second signal data of a plurality of frames by extracting signals from the first signal data by nonlinear processing with a first extraction function 110g. As an example, the processing circuit 110 extracts second signal data of a plurality of frames by extracting signals whose signal values ​​correspond to a local maximum value or a predetermined range from the first signal data with the first extraction function 110g. The processing circuit 110 identifies inappropriate signal points or inappropriate frames from the second signal data with an identification function 110h. The processing circuit 110 generates third signal data based on the identification result of the inappropriate signal points or the inappropriate frames and the second signal data with a generation function 110e.

[0252] (Appendix 2) An inappropriate signal point is a signal point that is estimated not to be a blood flow signal to be observed.

[0253] (Appendix 3) An inappropriate frame is a frame that is estimated to include signal points that are not the blood flow signal of the observation target.

[0254] (Appendix 4) The processing circuit 110 may generate the third signal data by excluding the inappropriate signal points from the signal points after accumulation using the generation function 110e. The processing circuit 110 may also generate the third signal data by accumulating the second signal data while excluding the inappropriate signal points or the inappropriate frames from the accumulation target using the generation function 110e.

[0255] (Appendix 5) The processing circuit 110 may use the identification function 110h to identify, as an inappropriate signal point, a signal point at a position where the number of signal extractions is less than a reference number.

[0256] (Appendix 6) The processing circuit 110 may use the identifying function 110h to identify a frame in which the change in the number of extracted signals in the frame direction is greater than a reference value as the inappropriate frame.

[0257] (Appendix 7) The processing circuit 110 may acquire the first signal data based on signal processing for blood flow imaging using the acquisition function 110f.

[0258] (Appendix 8) Processing circuitry 110 may identify the unsuitable signal points using identification function 110h based on the signal strength at each location.

[0259] (Appendix 9) The processing circuit 110 may identify the inappropriate frames using the identification function 110h based on the number of extracted signals in the frame direction.

[0260] (Appendix 10) The processing circuit 110 may receive, via the receiving function 110d, input of criteria for identifying the inappropriate signal points or the inappropriate frames from a user.

[0261] (Appendix 11) The processing circuit 110 may cause the display control function 110c to cause the display unit to display the index value for each position or frame for the user to set the criteria.

[0262] (Appendix 12) The processing circuit 110 uses the display control function 110c to measure how many times each point has been extracted as a high signal point by the identification function 110h, and generates a table 40 indicating the number of times each point has been extracted as a high signal point. The processing circuit 110 may use the display control function 110c to display information equivalent to the table 40 indicating the number of times each point has been extracted as a signal point as an index value on the display 135 serving as a display unit.

[0263] (Appendix 13) The processing circuit 110 may use a neural network to identify improper signal points or improper frames via identification function 110h.

[0264] (Appendix 14) A medical image processing device 100, which is an image processing device provided in one aspect of the present invention, includes a processing circuit 110. The processing circuit 110 acquires first signal data of a plurality of frames by scanning a subject with an acquisition function 110f. The processing circuit 110 extracts second signal data of a plurality of frames by extracting signals from the first signal data by nonlinear processing with a first extraction function 110g. As an example, the processing circuit 110 extracts second signal data of a plurality of frames by extracting signals whose signal values ​​correspond to a local maximum value or a predetermined range from the first signal data with the first extraction function 110g. The processing circuit 110 identifies inappropriate signal points or inappropriate frames from the second signal data with an identification function 110h. The processing circuit 110 generates third signal data based on the extraction result of the inappropriate signal points or the inappropriate frames and the second signal data with a generation function 110e.

[0265] (Appendix 15) An ultrasound diagnostic method provided in one aspect of the present invention comprises: acquiring a plurality of frames of first signal data by scanning the subject; extracting second signal data of a plurality of frames from the first signal data by nonlinear processing, for example by extracting signals whose signal values ​​correspond to local maxima or a predetermined range; Identifying an improper signal point or an improper frame from the second signal data; The second signal data is accumulated while excluding the inappropriate signal points or the inappropriate frames from accumulation targets, thereby generating third signal data.

[0266] According to at least one of the embodiments described above, image quality can be improved.

[0267] Although some 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 included in the scope of the invention and its equivalents as described in the claims, as well as in the scope and spirit of the invention. [Explanation of symbols]

[0268] 110 Processing circuit 110c Display control function 110d Reception function 110e generation function 110f acquisition function 1110g Extraction processing function 1110g1 split function 1110g2 Extraction function 1110g3 recovery process function 1110g4 Accumulation processing function 110h Specific function 111 Image generation function 112 Image Processing Functions 113 Control Functions 114 Display control function 132 Memory 134 Input Devices 135 Display

Claims

1. an acquisition unit that acquires a plurality of frames of first signal data by scanning a subject; a first extraction unit that extracts a signal from the first signal data by nonlinear processing to extract second signal data of a plurality of frames; A determination unit that determines an inappropriate signal point or an inappropriate frame from the second signal data; a generation unit that generates third signal data based on the specified result of the inappropriate signal point or the inappropriate frame and the second signal data; An ultrasound diagnostic device comprising:

2. The ultrasonic diagnostic apparatus according to claim 1 , wherein the generating unit generates the third signal data by excluding the inappropriate signal points from signal points after integration.

3. The ultrasound diagnostic apparatus according to claim 1 , wherein the generating unit generates the third signal data by integrating the second signal data while excluding the inappropriate signal points or the inappropriate frames from integration targets.

4. The ultrasonic diagnostic apparatus according to claim 1 , wherein the identifying unit identifies a signal point at a position where a signal has been extracted fewer times than a reference number as the inappropriate signal point.

5. The ultrasound diagnostic apparatus according to claim 1 , wherein the identifying unit identifies a frame in which a change in the number of extracted signals in a frame direction is greater than a reference value as the inappropriate frame.

6. The ultrasonic diagnostic apparatus according to claim 1 , wherein the acquisition unit acquires the first signal data based on signal processing for blood flow imaging.

7. The ultrasonic diagnostic apparatus according to claim 1 , wherein the identifying unit identifies the inappropriate signal points based on signal strength at each position.

8. The ultrasound diagnostic apparatus according to claim 1 , wherein the identifying unit identifies the inappropriate frames based on the number of extracted signals in a frame direction.

9. a receiving unit that receives an input of a criterion for identifying the inappropriate signal point or the inappropriate frame from a user; a display control unit that causes a display unit to display the index value for each position or frame for the user to set the criterion; The ultrasonic diagnostic apparatus according to claim 1 , further comprising:

10. an acquisition unit that acquires first signal data of a plurality of frames obtained by scanning a subject; a first extraction unit that extracts a signal from the first signal data by nonlinear processing to extract second signal data of a plurality of frames; A determination unit that determines an inappropriate signal point or an inappropriate frame from the second signal data; Based on the result of identifying the improper signal point or the improper frame and the second signal data, A generator for generating third signal data; An image processing device comprising:

11. acquiring a plurality of frames of first signal data by scanning the subject; Extracting a plurality of frames of second signal data from the first signal data by nonlinear processing; Identifying an improper signal point or an improper frame from the second signal data; generating third signal data based on the identification result of the improper signal point or the improper frame and the second signal data; Ultrasound diagnostic methods.

12. A medical information processing device comprising: an extraction unit that extracts second ultrasound image data by applying a kernel that extracts continuous components in a direction of interest to first ultrasound image data obtained based on the results of an ultrasound scan of a subject.

13. The medical image processing apparatus according to claim 12 , further comprising an output unit that outputs the second ultrasound image data.

14. The medical image processing device according to claim 12 , wherein the extraction unit extracts an image component at the position of interest as an image component representing an object when a pixel value at the position of interest is greater than or equal to a pixel value at a position adjacent to the position of interest in one direction.

15. the extraction unit compares a pixel value of the position of interest with a pixel value of an adjacent position for each of a plurality of positions of interest included in the first ultrasonic image data, and weights an image component of the position of interest based on a comparison result for each direction of interest. The medical information processing device according to claim 12.

16. 13. The medical image processing device according to claim 12, wherein the extraction unit compares a pixel value of a position of interest included in the first ultrasound image data with a pixel value of an adjacent position for each direction of interest relative to the position of interest, and weights an image component of the position of interest for each direction of interest.

17. an acquisition unit that acquires the first ultrasound image data based on data of a plurality of frames that are continuous in a time direction and are obtained based on a result of an ultrasound scan of a subject; The medical image processing apparatus according to claim 12 , wherein the extracting unit applies the kernel to each of the plurality of frames to extract the second ultrasound image data.

18. The medical information processing device according to claim 12, further comprising an acquisition unit that acquires, as the first ultrasound image data, data obtained by applying a smoothing filter in a spatial direction or a temporal direction to data of a plurality of frames that are consecutive in a temporal direction and that are obtained based on a result of an ultrasound scan on a subject.

19. 13. The medical information processing device according to claim 12, further comprising an acquisition unit that acquires a plurality of frame data that are consecutive in a time direction obtained by performing the ultrasound scan, and acquires added image data obtained by adding the plurality of frame data as the first ultrasound image data.

20. an execution unit that causes an ultrasound probe to execute an ultrasound scan on a subject; an extraction unit that extracts second ultrasound image data by applying a kernel that extracts continuous components in a direction of interest to first ultrasound image data obtained based on a result of the ultrasound scan.

21. On the computer, A program that executes a process of extracting second ultrasound image data by applying a kernel that extracts continuous components in a direction of interest to first ultrasound image data obtained based on the results of an ultrasound scan of a subject.

22. A division unit that divides the first ultrasonic image data into a plurality of second ultrasonic image data; an extracting unit that extracts third ultrasonic image data by performing peak extraction from each of the second ultrasonic image data; a restoration processing unit that generates fourth ultrasound image data by allocating the third ultrasound image data to a corresponding position on the first ultrasound image data; an integration processing unit that integrates the fourth ultrasonic image data to generate fifth ultrasonic image data.

23. The medical image processing apparatus according to claim 22 , further comprising an output unit that outputs the fifth ultrasound image data.

24. The medical image processing apparatus according to claim 22 , further comprising an output unit that outputs composite image data obtained by performing a synthesis process on the first ultrasonic image data and the fifth ultrasonic image data.

25. The medical image processing apparatus according to claim 22 , further comprising an output unit that outputs corrected image data obtained by performing a correction process on the first ultrasonic image data based on the fifth ultrasonic image data.

26. The medical image processing apparatus according to claim 22 , further comprising an acquisition unit configured to acquire, as the first ultrasound image data, data of a plurality of frames that are continuous in a time direction and obtained based on a result of an ultrasound scan on a subject.

27. 23. The medical image processing device according to claim 22, further comprising an acquisition unit that acquires a plurality of frame data that are consecutive in a time direction obtained by performing the ultrasound scan, and acquires added image data obtained by adding the plurality of frame data as the first ultrasound image data.

28. an execution unit that causes an ultrasound probe to execute an ultrasound scan; A division unit that divides the first ultrasonic image data into a plurality of second ultrasonic image data; an extracting unit that extracts third ultrasonic image data by performing peak extraction from each of the second ultrasonic image data; a restoration processing unit that generates fourth ultrasound image data by allocating the third ultrasound image data to a corresponding position on the first ultrasound image data; an integration processing unit that integrates the fourth ultrasonic image data to generate fifth ultrasonic image data.

29. On the computer, Dividing the first ultrasound image data into a plurality of second ultrasound image data; extracting third ultrasonic image data by performing peak extraction from each of the second ultrasonic image data; assigning the third ultrasound image data to a corresponding position on the first ultrasound image data to generate fourth ultrasound image data; A program for executing a process of integrating the fourth ultrasonic image data to generate fifth ultrasonic image data.

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