ULTRASOUND DIAGNOSIS APPARATUS AND ULTRASOUND SIGNAL GENERATION METHOD

An ultrasound diagnosis apparatus of an embodiment includes storage circuitry and processing circuitry. The storage circuitry stores therein a trained model trained using a first ultrasound signal containing a saturated signal as input data and a second ultrasound signal in which effect of saturation is reduced from the first ultrasound signal, as target data. The processing circuitry inputs a third ultrasound signal containing a saturated signal to the trained model and acquires a fourth ultrasound signal that is output from the trained model and in which effect of saturation is reduced from the third ultrasound signal, to generate the fourth ultrasound signal.

FIELD

Embodiments described herein relate generally to ultrasound diagnosis apparatuses and ultrasound signal generation methods.

BACKGROUND

To acquire ultrasound image data having fewer artifacts, tissue harmonic imaging (THI) using a harmonic component (nonlinear signal) produced in the process of ultrasound propagation is widely used. The second harmonic component is typically used; however, the application of the third harmonic component has also been proposed. Note that an Nth (N is an integer of 2 or greater) harmonic component is also referred to simply as an Nth component or Nth harmonic.

Analog circuitry of an ultrasound diagnosis apparatus has a limited dynamic range of input. To protect the analog circuitry, if the signal value of an input signal is equal to or greater than a certain magnitude, clamping circuitry works on the input signal to clip the waveform so that the signal value of the input signal is a certain value. This saturates the input signal. Then, an odd-multiple harmonic component is superimposed on the signal. Thus, if visualization is performed with the third harmonic component, the band of visualization and the band of harmonics produced by saturation overlap, resulting in image quality degradation.

A configuration of a prefilter and the like or an algorithm restraining such effect of saturation has also been proposed. Unfortunately, this may cause an increase in the circuitry size, signal processing to be required in an earlier stage, or lacking in robustness.

DETAILED DESCRIPTION

A problem to be solved by the embodiments disclosed in this specification and the drawings is to acquire an ultrasound signal in which effect of saturation is robustly reduced and degradation in image quality is restrained. However, problems to be solved by the embodiments disclosed in this specification and the drawings are not limited to the aforementioned problem. A problem corresponding to each effect of each configuration indicated by the embodiments described below can also be positioned as another problem.

An ultrasound diagnosis apparatus of an embodiment includes storage circuitry and processing circuitry. The storage circuitry stores therein a trained model trained using a first ultrasound signal containing a saturated signal as input data and a second ultrasound signal in which effect of saturation is reduced from the first ultrasound signal, as target data. The processing circuitry inputs a third ultrasound signal containing a saturated signal to the trained model and acquires a fourth ultrasound signal that is output from the trained model and in which effect of saturation is reduced from the third ultrasound signal, to generate the fourth ultrasound signal.

An ultrasound diagnosis apparatus and an ultrasound signal generation method according to each embodiment and each modification will be described below with reference to the drawings.

First Embodiment

FIG.1is a block diagram illustrating an example configuration of an ultrasound diagnosis apparatus1according to a first embodiment. As exemplified inFIG.1, the ultrasound diagnosis apparatus1of the first embodiment includes an apparatus body100, an ultrasound probe101, an input device102, and a display103.

The ultrasound probe101includes, for example, a plurality of elements (piezoelectric transducer elements, piezoelectric elements). These elements produce ultrasound on the basis of a driving signal supplied from transmitting circuitry111of transmitting/receiving circuitry110of the apparatus body100. In specific, by applying voltage (transmission driving voltage) by the transmitting circuitry111, the elements produce ultrasound having a waveform in accordance with the transmission driving voltage. The waveform of the transmission driving voltage indicated by the driving signal is the waveform of the voltage applied to the elements. That is, the ultrasound probe101transmits ultrasound in accordance with the magnitude of the applied transmission driving voltage. Furthermore, the ultrasound probe101receives a reflected wave from a subject P, converts the received reflected wave into a reflected wave signal being an electric signal, and outputs the reflected wave signal to the apparatus body100. The reflected wave signal is an example ultrasound signal. The ultrasound probe101also includes, for example, a matching layer provided on the elements, a backing material preventing backward propagation of ultrasound from the elements, and the like. Note that the ultrasound probe101is detachably connected to the apparatus body100.

When the ultrasound probe101transmits ultrasound to the subject P, the transmitted ultrasound is successively reflected off surfaces of discontinuity of acoustic impedance in body tissues of the subject P and is received by the elements of the ultrasound probe101as a reflected wave. The amplitude of the received reflected wave depends on the difference in the acoustic impedance at the discontinuity surfaces reflecting the ultrasound. Note that when the transmitted ultrasound pulse is reflected off a surface of a moving object, such as a moving blood flow and a cardiac wall, the reflected wave undergoes frequency shift depending on the velocity component relative to the ultrasound transmitting direction of the moving object because of the Doppler effect. The ultrasound probe101then outputs the reflected wave signal to receiving circuitry112, described later, of the transmitting/receiving circuitry110.

The ultrasound probe101is provided so as to be detachable from the apparatus body100. When a two-dimensional region in the subject P is scanned (two-dimensional scanning), an operator connects, for example, a 1D array probe, in which a plurality of elements are arranged in one row, to the apparatus body100as the ultrasound probe101. Types of 1D array probe include linear ultrasound probes, convex ultrasound probes, sector ultrasound probes, and the like. When a three-dimensional region in the subject P is scanned (three-dimensional scanning), the operator connects, for example, a mechanical 4D probe or a 2D array probe to the apparatus body100as the ultrasound probe101. The mechanical 4D probe can perform two-dimensional scanning using a plurality of elements arranged in one row like 1D array probes and can also perform three-dimensional scanning by oscillating the elements at a predetermined angle (oscillation angle). The 2D array probe can perform three-dimensional scanning with a plurality of elements arranged in a matrix and can also perform two-dimensional scanning by transmitting ultrasound in a converged manner.

The input device102is implemented by input means, such as a mouse, a keyboard, a button, a panel switch, a touch command screen, a foot switch, a trackball, and a joystick. The input device102receives various setting requests from the operator of the ultrasound diagnosis apparatus1and transfers the received various setting requests to the apparatus body100.

The display103displays, for example, a graphical user interface (GUI) for the operator of the ultrasound diagnosis apparatus1to input various setting requests using the input device102, an ultrasound image based on ultrasound image data generated in the apparatus body100, and the like. The display103is implemented by a liquid crystal monitor, an organic light emitting diode (OLED) monitor, or the like. The display103is an example display unit.

The apparatus body100generates ultrasound image data on the basis of the reflected wave signal transmitted from the ultrasound probe101. Note that the ultrasound image data is an example ultrasound signal and is also example image data. The apparatus body100can generate two-dimensional ultrasound image data on the basis of the reflected wave signal transmitted from the ultrasound probe101and corresponding to a two-dimensional region of the subject P. The apparatus body100can also generate three-dimensional ultrasound image data on the basis of the reflected wave signal transmitted from the ultrasound probe101and corresponding to a three-dimensional region of the subject P. As illustrated inFIG.1, the apparatus body100includes the transmitting/receiving circuitry110, a buffer memory120, B-mode processing circuitry130, Doppler processing circuitry140, image generation circuitry150, an image memory160, storage circuitry170, and control circuitry180.

The transmitting/receiving circuitry110causes the ultrasound probe101to transmit ultrasound and to receive the reflected wave of the ultrasound under control of the control circuitry180. That is, the transmitting/receiving circuitry110performs scanning through the ultrasound probe101. Note that scanning is also referred to as ultrasound scanning. The transmitting/receiving circuitry110is an example transmitting/receiving unit. The transmitting/receiving circuitry110includes the transmitting circuitry111and the receiving circuitry112. The transmitting circuitry111is an example transmitting unit, and the receiving circuitry112is an example receiving unit.

The transmitting circuitry111supplies a driving signal to the ultrasound probe101to cause the ultrasound probe101to transmit ultrasound under control of the control circuitry180. The transmitting circuitry111includes rate pulser production circuitry, transmission delay circuitry, and a transmission pulser. When a two-dimensional region in the subject P is scanned, the transmitting circuitry111causes the ultrasound probe101to transmit an ultrasound beam for scanning the two-dimensional region. When a three-dimensional region in the subject P is scanned, the transmitting circuitry111causes the ultrasound probe101to transmit an ultrasound beam for scanning the three-dimensional region.

The rate pulser production circuitry repeatedly produces a rate pulse for forming transmission ultrasound (transmission beam) at a predetermined pulse repetition frequency (PRF) under control of the control circuitry180. The rate pulse passes through the transmission delay circuitry, so that voltage is applied to the transmission pulser while having different transmission delay time. For example, the transmission delay circuitry provides, to each rate pulse produced by the rate pulser production circuitry, transmission delay time for each element necessary for determining transmission directivity with the ultrasound produced from the ultrasound probe101converged into a beam. The transmission pulser supplies the driving signal (driving pulse) to the ultrasound probe101at timing based on the rate pulse. That is, the transmission pulser applies, to the ultrasound probe101, voltage (transmission driving voltage) of a waveform indicated by the driving signal at the timing based on the rate pulse. Note that the transmission delay circuitry varies the transmission delay time provided to each rate pulse to arbitrarily adjust the transmitting direction of the ultrasound from the element surface.

The driving pulse is transmitted from the transmission pulser via a cable to the elements in the ultrasound probe101and is then converted from an electric signal into mechanical oscillation in the elements. That is, voltage application to the elements mechanically oscillates the elements. Ultrasound produced by this mechanical oscillation is transmitted inside a living body (inside the subject P). Here, the ultrasound having the transmission delay time different between the elements is converged and propagates in a predetermined direction.

Note that the transmitting circuitry111has a function capable of instantaneously varying the transmission frequency, transmission driving voltage, and the like to execute a predetermined scanning sequence under control of the control circuitry180. In particular, varying of the transmission driving voltage is implemented by sending circuitry of the linear amplifier type capable of instantaneously switching the value of the transmission driving voltage or a mechanism electrically switching a plurality of power source units. Note that the transmission frequency is, for example, the center frequency of the transmitted ultrasound.

The reflected wave of the ultrasound transmitted by the ultrasound probe101reaches the elements in the ultrasound probe101and is then converted from the mechanical oscillation into an electrical signal (reflected wave signal), and the reflected wave signal is input to the receiving circuitry112.

The receiving circuitry112performs various types of processing to the reflected wave signal transmitted from the ultrasound probe101to generate reflected wave data. The receiving circuitry112then stores the generated reflected wave data in the buffer memory120. Note that the reflected wave data is an example ultrasound signal.

FIG.2is a diagram illustrating an example configuration of the receiving circuitry112according to the first embodiment. As illustrated inFIG.2, the receiving circuitry112includes an analog front end113, analog-to-digital (A/D) conversion circuitry (A/D converter)114, a beam former115, and saturation reduction processing circuitry116.

To the analog front end113, the reflected wave signal is input from the ultrasound probe101. The analog front end113is analog circuitry performing known analog processing (analog signal processing) on the input reflected wave signal and outputting the reflected wave signal being an analog signal subjected to the analog processing to the A/D conversion circuitry114. For example, to describe a portion of the processing executed by the analog front end113, the analog front end113includes, for example, a preamplifier, and the preamplifier amplifies the reflected wave signal for each channel and performs gain adjustment (gain correction).

The analog front end113also includes clamping circuitry113a.FIG.3is a diagram illustrating example operation of the clamping circuitry113aaccording to the first embodiment. For example, as illustrated inFIG.3, the clamping circuitry113aconverts a reflected wave signal113binto a reflected wave signal113dso that the amplitude of the reflected wave signal113binput to the preamplifier falls within a predetermined tolerance range113cand inputs the reflected wave signal113dto the preamplifier. For example, the clamping circuitry113aclips (fixes) the amplitude of the reflected wave signal113bequal to or greater than a certain value to the certain value to generate the reflected wave signal113d. The clamping circuitry113athen outputs the reflected wave signal113dtoward the preamplifier. This protects the preamplifier being circuitry in the analog front end113from an excessive high-voltage pulse of the reflected wave signal.

In this way, the clamping circuitry113aexecutes clamping processing restraining the signal value, equal to or greater than the certain value, of the reflected wave signal113bacquired by transmitting and receiving ultrasound to and from the subject P, to the certain value. The clamping processing yields the reflected wave signal113d. Such clamping processing is example processing included in the analog processing.

Here, clipping of the amplitude of the reflected wave signal113bequal to or greater than a certain value to a certain value is equivalent to convolution of a rectangular wave. Thus, an odd-order harmonic component (such as the third harmonic component and the fifth harmonic component) is superimposed on the reflected wave signal113d. That is, let f0represent the center frequency (frequency of the fundamental) of the reflected wave signal113b, the reflected wave signal113dcontains an odd-order harmonic component (such as the third harmonic component corresponding to a frequency3f0and the fifth harmonic component corresponding to a frequency5f0).

Thus, if visualization is performed with the third harmonic on the basis of this reflected wave signal113d, the band of visualization and the band of harmonics produced by saturation overlap, resulting in image quality degradation. That is, the reflected wave signal113dis affected by saturation, so that image quality of ultrasound image data based on the reflected wave signal113dis degraded. Therefore, the ultrasound diagnosis apparatus1of the first embodiment is configured to be capable of generating an ultrasound signal that does not degrade image quality even if visualization is performed with the third harmonic, as described below.

Returning to description ofFIG.2, to the A/D conversion circuitry114, the reflected wave signal output from the analog front end113is input. The A/D conversion circuitry114converts the reflected wave signal into a digital signal through A/D conversion of the reflected wave signal and outputs the reflected wave signal converted into the digital signal to the beam former115.

To the beam former115, the reflected wave signal output from the A/D conversion circuitry114is input. The beam former115applies phasing addition processing to the input reflected wave signal. For example, the beam former115provides reception delay time necessary for determining reception directivity, to the reflected wave signal being the digital signal. The beam former115then performs addition processing to the reflected wave signal provided with the reception delay time. The addition processing of the beam former115emphasizes the reflection component from a direction corresponding to the reception directivity of the reflected wave signal.

The beam former115then converts the reflected wave signal subjected to the phasing addition processing into an in-phase signal (I signal) and a quadrature-phase signal (Q signal) in the baseband. The beam former115then stores the I signal and Q signal (IQ signal) in the buffer memory120as reflected wave data. The beam former115is implemented by, for example, processing circuitry including a processor.

The saturation reduction processing circuitry116is processing circuitry that operates when input data and target data are generated to be used in generation of a trained model170aat a learning apparatus200described later, that is, at the time of training. To the saturation reduction processing circuitry116, the reflected wave data output from the B-mode processing circuitry130via the beam former115is input at the time of training. The reflected wave data input to the saturation reduction processing circuitry116at this time is signal data containing the third harmonic component described later. The saturation reduction processing circuitry116generates reflected wave data in which effect of saturation is reduced in comparison with the input reflected wave data and transmits the generated reflected wave data to the learning apparatus200, described later, as target data. Processing executed by the saturation reduction processing circuitry116will be described in detail later.

Returning to description ofFIG.1, the receiving circuitry112generates two-dimensional reflected wave data from a two-dimensional reflected wave signal transmitted from the ultrasound probe101. The receiving circuitry112also generates three-dimensional reflected wave data from a three-dimensional reflected wave signal transmitted from the ultrasound probe101.

In this embodiment, the ultrasound diagnosis apparatus1can perform various types of processing in real time. For example, the ultrasound probe101successively transmits reflected wave signals for one frame to the receiving circuitry112. Each time the receiving circuitry112receives the reflected wave signals for one frame transmitted from the ultrasound probe101, the receiving circuitry112generates reflected wave data for one frame from the reflected wave signals for one frame. Each time the receiving circuitry112generates the reflected wave data for one frame, the receiving circuitry112stores the reflected wave data for one frame in the buffer memory120.

The buffer memory120is a memory that temporarily stores therein the reflected wave data generated by the transmitting/receiving circuitry110. For example, the buffer memory120is configured to be capable of storing therein the reflected wave data for a predetermined number of frames. If the receiving circuitry112newly generates reflected wave data for one frame while the buffer memory120is storing therein the reflected wave data for the predetermined number of frames, the buffer memory120discards the reflected wave data for the oldest frame generated and stores therein the reflected wave data for the newly generated frame under control of the receiving circuitry112. For example, the buffer memory120is implemented by a semiconductor memory device, such as a random access memory (RAM) and a flash memory.

The B-mode processing circuitry130reads out the reflected wave data from the buffer memory120, applies various types of signal processing to the read-out reflected wave data, and outputs the reflected wave data subjected to the various types of signal processing to the image generation circuitry150as B-mode data. The B-mode processing circuitry130is implemented by, for example, a processor. The B-mode processing circuitry130is an example B-mode processing unit. The B-mode data is an example ultrasound signal.

For example, each time reflected wave data for one frame is newly stored in the buffer memory120, the B-mode processing circuitry130reads out the reflected wave data for one frame newly stored in the buffer memory120. The B-mode processing circuitry130then applies the various types of signal processing to the read-out reflected wave data for one frame to newly generate B-mode data for one frame. Each time the B-mode processing circuitry130generates B-mode data for one frame, the B-mode processing circuitry130outputs the newly generated B-mode data for one frame to the image generation circuitry150. An example of the various types of signal processing executed by the B-mode processing circuitry130will be described below.

For example, the B-mode processing circuitry130performs quadrature detection on and applies envelope detection and logarithmic compression processing and the like to the reflected wave data read out from the buffer memory120to generate B-mode data in which the signal strength (amplitude strength) at each sample point is represented by brightness. The B-mode processing circuitry130then outputs the generated B-mode data to the image generation circuitry150.

Here, using a function of the B-mode processing circuitry130, the ultrasound diagnosis apparatus1can extract the third harmonic component from the reflected wave data (received signal) and generate B-mode image data based on the extracted third harmonic component. For example, the ultrasound diagnosis apparatus1uses the technique described in Japanese Patent Application Laid-open No. 2016-112400 to extract the third harmonic component from the reflected wave data. For example, the transmitting circuitry111causes the ultrasound probe101to execute three transmissions of ultrasound having phases (phases of the center frequency components contained in the ultrasound to be transmitted) differing by 120 degrees from each other. The receiving circuitry112generates three pieces of reflected wave data relating to a common reception scanning line on the basis of a plurality of reflected wave signals acquired through the three ultrasound transmissions. The B-mode processing circuitry130executes processing including phase rotation processing on two or more pieces of reflected wave data among the three pieces of reflected wave data to extract the second harmonic component, adds up the three pieces of reflected wave data, and extracts the third harmonic component. For example, the transmitting circuitry111causes the ultrasound probe101to transmit ultrasound in a first phase, to transmit ultrasound in a second phase in which the phase is advanced 120 degrees from the first phase, and to transmit ultrasound in a third phase in which the phase is advanced 240 degrees from the first phase. In other words, the transmitting circuitry111causes the ultrasound probe to transmit first ultrasound having a single center frequency component in the first phase, to transmit second ultrasound having a single center frequency component in the second phase in which the phase is substantially advanced 120 degrees from the first phase, and to transmit third ultrasound having a single center frequency component in the third phase in which the phase is substantially advanced 240 degrees from the first phase. Here, “substantially” indicates any of the following: (1) allowing for an error; (2) allowing for advancing of the phase in the negative direction (for example, including a case where the ultrasound probe101transmits the first ultrasound in the first phase, transmits the second ultrasound in a second phase in which the phase is delayed 120 degrees from the first phase, and transmits the third ultrasound having a phase delayed 240 degrees from the first phase); and (3) allowing phase rotation of N degrees and phase rotation of N+360 degrees to be considered the same (for example, allowing phase rotation of 120 degrees, phase rotation of 480 degrees, and phase rotation of −240 degrees).

Then, for example, the receiving circuitry112generates first reflected wave data corresponding to the ultrasound transmission in the first phase, second reflected wave data corresponding to the ultrasound transmission in the second phase, and third reflected wave data corresponding to the ultrasound transmission in the third phase. The B-mode processing circuitry130adds up the first reflected wave data, reflected wave data having a phase advanced 120 degrees from that of the second reflected wave data, and reflected wave data having a phase advanced 240 degrees from that of the third reflected wave data and extracts the second harmonic component. Furthermore, the B-mode processing circuitry130adds up the first reflected wave data, the second reflected wave data, and the third reflected wave data, and extracts the third harmonic component. In other words, the B-mode processing circuitry130adds up the first reflected wave data, the second reflected wave data, and the third reflected wave data in which the phases of the second harmonic components are substantially aligned and extracts the second harmonic component. Furthermore, the B-mode processing circuitry130adds up the first reflected wave data, the second reflected wave data, and the third reflected wave data in which the phases of the third harmonic components are substantially aligned and extracts the third harmonic component. Here, for example, “substantially aligned” indicates allowing for a slight error.

Here, the third harmonic component extracted by the B-mode processing circuitry130is reflected wave data used as input data described later, which will be described in detail later. The B-mode processing circuitry130then applies a trained model170adescribed later to this input data to acquire reflected wave data in which effect of saturation is reduced. That is, the B-mode processing circuitry130extracts the third harmonic component in which effect of saturation is reduced from the input data. Note that the B-mode processing circuitry130may extract the third harmonic component by subtracting fourth reflected wave data acquired by transmitting ultrasound in a fourth phase in which the phase is reversed from the first phase, from the first reflected wave data acquired by transmitting ultrasound in the first phase. The third harmonic component extracted in this way may be used as input data described later. Alternatively, the third harmonic component may be extracted by applying a trained model170adescribed later to the reflected wave data generated by the beam former115.

The B-mode processing circuitry130uses the above-described method to extract the second harmonic component and the third harmonic component. It can be said that the B-mode processing circuitry130having the function to extract the second harmonic component and the third harmonic component is an example extracting unit.

The B-mode processing circuitry130then generates B-mode data based on the extracted second harmonic component and outputs the generated B-mode data to the image generation circuitry150. The B-mode processing circuitry130also generates B-mode data based on the extracted third harmonic component and outputs the generated B-mode data to the image generation circuitry150.

The Doppler processing circuitry140reads out the reflected wave data from the buffer memory120, applies various types of signal processing to the read-out reflected wave data, and outputs the reflected wave data subjected to the various types of signal processing to the image generation circuitry150as Doppler data. The Doppler processing circuitry140is implemented by, for example, a processor. The Doppler processing circuitry140is an example Doppler processing unit.

For example, each time reflected wave data for one frame is newly stored in the buffer memory120, the Doppler processing circuitry140reads out the reflected wave data for one frame newly stored in the buffer memory120. The Doppler processing circuitry140then applies the various types of signal processing to the read-out reflected wave data for one frame to newly generate Doppler data for one frame. Each time the Doppler processing circuitry140generates Doppler data for one frame, the Doppler processing circuitry140outputs the newly generated Doppler data for one frame to the image generation circuitry150. An example of the various types of signal processing executed by the Doppler processing circuitry140will be described below.

For example, the Doppler processing circuitry140performs frequency analysis on the reflected wave data read out from the buffer memory120to extract movement information of a moving object (such as a blood flow, tissues, and a contrast agent echo component) based on the Doppler effect from the reflected wave data and generates Doppler data indicating the extracted movement information. For example, the Doppler processing circuitry140extracts the average speed, average dispersion values, average power values, and the like at multiple points as the movement information of the moving object and generates the Doppler data indicating the extracted movement information of the moving object. The Doppler processing circuitry140outputs the generated Doppler data to the image generation circuitry150.

The ultrasound diagnosis apparatus1can use the above-described function of the Doppler processing circuitry140to execute the color Doppler method, also referred to as color flow mapping (CFM). In color flow mapping, ultrasound is transmitted and received on a plurality of scanning lines a plurality of times. In color flow mapping, a moving target indicator (MTI) filter is applied to a data string in the same position to restrain a signal (clutter signal) derived from a stationary tissue or a slow-moving tissue and to extract a signal derived from a blood flow (blood flow signal) from the data string in the same position. In color flow mapping, blood flow information, such as the blood flow speed (average speed), blood flow dispersion (average dispersion value), and blood flow power (average power value), is estimated from the blood flow signal. The Doppler processing circuitry140outputs color Doppler data indicating the blood flow information estimated by color flow mapping to the image generation circuitry150. Note that the color Doppler data is example Doppler data.

The B-mode processing circuitry130and the Doppler processing circuitry140can process both two-dimensional reflected wave data and three-dimensional reflected wave data.

The image generation circuitry150generates various pieces of ultrasound image data from the B-mode data, the second harmonic component, and the third harmonic component output from the B-mode processing circuitry130and the Doppler data output from the Doppler processing circuitry140. The image generation circuitry150is implemented by a processor.

For example, the image generation circuitry150generates two-dimensional B-mode image data in which the intensity of the reflected wave is represented by brightness, from two-dimensional B-mode data generated by the B-mode processing circuitry130. Furthermore, the image generation circuitry150generates two-dimensional Doppler image data or two-dimensional color image data in which the movement information or the blood flow information is visualized, from two-dimensional Doppler data or color Doppler data generated by the Doppler processing circuitry140. Note that the two-dimensional Doppler image data in which the movement information is visualized and the two-dimensional color image data in which the blood flow information is visualized are speed image data, dispersion image data, power image data, or a combination of these pieces of image data.

Here, the image generation circuitry150typically converts (scan-converts) a scanning line signal string of ultrasound scanning into a scanning line signal string in a video format typified by television and the like and generates ultrasound image data for display. For example, the image generation circuitry150performs coordinate transformation on the data output from the B-mode processing circuitry130and the Doppler processing circuitry140in accordance with the mode of ultrasound scanning by the ultrasound probe101to generate ultrasound image data for display. The image generation circuitry150may also perform, for example, image processing (smoothing processing) regenerating an average value image of brightness using a plurality of image frames after scan conversion, image processing (edge enhancement processing) using a differential filter in an image, or the like, as various types of image processing other than the scan conversion. The image generation circuitry150may composite the ultrasound image data with textual information of various parameters, a scale, a body mark, and the like.

Furthermore, the image generation circuitry150performs coordinate transformation on three-dimensional B-mode data generated by the B-mode processing circuitry130to generate three-dimensional B-mode image data. The image generation circuitry150also performs coordinate transformation on three-dimensional Doppler data generated by the Doppler processing circuitry140to generate three-dimensional Doppler image data. That is, the image generation circuitry150generates the “three-dimensional B-mode image data and three-dimensional Doppler image data” as “three-dimensional ultrasound image data (volume data)”. The image generation circuitry150then performs various types of rendering processing on the volume data to generate various pieces of two-dimensional image data to display the volume data on the display103.

The rendering processing performed by the image generation circuitry150includes, for example, processing using multi planer reconstruction (MPR) to generate MPR image data from the volume data. The rendering processing performed by the image generation circuitry150includes, for example, volume rendering (VR) processing generating two-dimensional image data in which three-dimensional information is reflected. The image generation circuitry150is an example image generation unit.

The B-mode data and Doppler data are ultrasound image data before the scan conversion processing, and the data generated by the image generation circuitry150is ultrasound image data for display after the scan conversion processing. Note that the B-mode data and Doppler data are also referred to as raw data.

If receiving B-mode data based on the second harmonic component from the B-mode processing circuitry130, the image generation circuitry150generates B-mode image data on the basis of the B-mode data based on the second harmonic component. Similarly, if receiving B-mode data based on the third harmonic component from the B-mode processing circuitry130, the image generation circuitry150generates B-mode image data on the basis of the B-mode data based on the third harmonic component.

The image memory160is a memory storing therein various pieces of image data generated by the image generation circuitry150. The image memory160also stores therein the data generated by the B-mode processing circuitry130and the Doppler processing circuitry140. The B-mode data and Doppler data stored in the image memory160can be called by the operator after diagnosis, for example, and is turned into the ultrasound image data for display via the image generation circuitry150. For example, the image memory160is implemented by a semiconductor memory device, such as a random access memory (RAM) and a flash memory, a hard disk, or an optical disk.

The storage circuitry170stores therein a control computer program for performing scanning (ultrasound transmission and reception), image processing, and display processing, diagnosis information (such as a patient ID and doctor's findings), and various pieces of data, such as diagnosis protocols and various body marks. The storage circuitry170is also used for storing data stored by the image memory160and the like as necessary. For example, the storage circuitry170is implemented by a semiconductor memory device, such as a flash memory, a hard disk, or an optical disk.

The storage circuitry170of this embodiment also stores a trained model170atherein. The storage circuitry170may store a trained model170aat the time of delivery of the ultrasound diagnosis apparatus1or may store a trained model170aacquired from an external device or the like after delivery of the ultrasound diagnosis apparatus1. The trained model170awill be described later.

The control circuitry180controls the overall processing of the ultrasound diagnosis apparatus1. In specific, the control circuitry180controls processing of the transmitting circuitry111, the receiving circuitry112, the B-mode processing circuitry130, the Doppler processing circuitry140, and the image generation circuitry150on the basis of various setting requests input by the operator via the input device102and various control computer programs and various pieces of data read from the storage circuitry170. The control circuitry180also controls the display103so that an ultrasound image based on the ultrasound image data for display stored in the image memory160is displayed. For example, the control circuitry180controls the display103so that a B-mode image based on the B-mode image data or a color image based on the color image data is displayed. The control circuitry180also controls the display103so that a B-mode image with a color image superimposed thereon is displayed.

Furthermore, the control circuitry180generates a composite image by compositing a B-mode image based on the B-mode image data generated on the basis of the B-mode data based on the second harmonic component and a B-mode image based on the B-mode image data generated on the basis of the B-mode data based on the third harmonic component. The control circuitry180then controls the display103so that the generated composite image is displayed.

The control circuitry180is an example display control unit or control unit. The control circuitry180is implemented by, for example, a processor.

The control circuitry180also controls ultrasound scanning by controlling the ultrasound probe101via the transmitting/receiving circuitry110.

Note that the term “processor” used in the description indicates, for example, circuitry, such as a central processing unit (CPU), a graphics processing unit (GPU), an application specific integrated circuit (ASIC), or a programmable logic device (such as a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), or a field programmable gate array (FPGA)). The processor achieves the function by reading out the computer program stored in the storage circuitry170and executing the read-out computer program. Note that instead of storing the computer program in the storage circuitry170, the computer program may be incorporated directly into the circuitry of the processor. In this case, the processor reads out and executes the computer program incorporated into the circuitry to achieve the function. Note that each processor of this embodiment is not limited to being configured as single circuitry for each processor and may be configured as a single processor by combining a plurality of pieces of independent circuitry to achieve the function. Furthermore, the plural pieces of circuitry (for example, the B-mode processing circuitry130, the Doppler processing circuitry140, the image generation circuitry150, and the control circuitry180) inFIG.1may be integrated into a single processor to achieve the function. That is, the B-mode processing circuitry130, the Doppler processing circuitry140, the image generation circuitry150, and the control circuitry180may be integrated into a single piece of processing circuitry implemented by a processor. Note that the transmitting/receiving circuitry110, the B-mode processing circuitry130, the Doppler processing circuitry140, the image generation circuitry150, and the control circuitry180may be integrated into a single pieces of processing circuitry including a processor.

The overall configuration of the ultrasound diagnosis apparatus1of the first embodiment has been described. With the above-described configuration, the ultrasound diagnosis apparatus1executes processing described below so as to acquire an ultrasound signal in which effect of saturation is robustly reduced and degradation in image quality is restrained.

FIG.4is a diagram for describing an example method of generating the trained model170aaccording to the first embodiment. The trained model170ais a trained machine learning model acquired by subjecting a machine learning model to machine learning in accordance with a model learning computer program on the basis of the input data and target data. The trained model170ais generated by the learning apparatus200.

The learning apparatus200includes a machine learning model, such as a convolution neural network (CNN). The learning apparatus200performs training (supervised training) based on the input data and target data relating to an ultrasonic examination of the same position (the same section, the same site) of a subject to generate the trained model170a. The trained model170afunctions to output data corresponding to the target data (output data) when data corresponding to the input data is input at the time of inference. Note that the ultrasound diagnosis apparatus1may have a function similar to the function of the learning apparatus200and generate the trained model170ainstead of the learning apparatus200.

A case where the machine learning model is a CNN will be described. In this case, in the learning apparatus200, input data is input to the CNN being the machine learning model. The learning apparatus200applies the CNN to the input data to generate output data. The output data is then output from the CNN. In the learning apparatus200, the output data is input to an evaluation function. In the learning apparatus200, target data is also input to the evaluation function. The learning apparatus200evaluates the output data generated by the CNN on the basis of the input data and the target data with the evaluation function. The evaluation function, for example, compares the generated output data with the target data and modifies a coefficient (network parameter, such as weight and bias) of the CNN through error backpropagation. The evaluation by the evaluation function is fed back to the CNN. The learning apparatus200repeats such a series of supervised training based on the input data and target data acquired for the same position of the subject until, for example, a difference between the output data and the target data is equal to or smaller than a predetermined threshold. The learning apparatus200can output the trained machine learning model as a trained model.

For example, in the CNN, when input data and target data are provided, such a coefficient is generated that conversion into target data is performed from the characteristics of the input data. The greater the number of the input data and target data used for the machine learning, the better. For example, several thousands or more pieces of data are desirable.

A method of generating the input data and target data used for the machine learning at the learning apparatus200will be described with reference toFIG.5.FIG.5is a diagram for describing an example input data and target data generation method according to the first embodiment. Note that the B-mode processing circuitry130connected to the subsequent stage of the beam former115is omitted inFIG.5. As illustrated inFIG.5, the reflected wave signal acquired by scanning a predetermined position of the subject P by the ultrasound probe101passes through the analog front end113and the A/D conversion circuitry114and is turned into reflected wave data by the beam former115. Then, as described above, the B-mode processing circuitry130adds up the first reflected wave data, the second reflected wave data, and the third reflected wave data to acquire the third harmonic component. The third harmonic component (data after subjected to the phasing addition processing) as the reflected wave data is the input data. Furthermore, the saturation reduction processing circuitry116applies saturation reduction processing reducing effect of saturation on the reflected wave data being the input data.

Example saturation reduction processing executed by the saturation reduction processing circuitry116of the first embodiment will be described. For example, the saturation reduction processing circuitry116executes the saturation reduction processing applying a negative gain to a signal (portion) that is contained in the reflected wave data (input data) after the phasing addition processing and that is affected by saturation, thereby reducing the amplitude value of the signal affected by saturation.

In the reflected wave data subjected to the saturation reduction processing, effect of saturation is reduced in comparison with the reflected wave data as the input data. The reflected wave data subjected to this saturation reduction processing is the target data. That is, the saturation reduction processing circuitry116executes the saturation reduction processing to generate the target data.

The ultrasound diagnosis apparatus1then transmits the input data and target data generated in this way to the learning apparatus200.

Note that the input data and target data are not limited to the above-described reflected wave data. For example, the reflected wave data output from the beam former115is turned into the B-mode data by the B-mode processing circuitry130. This B-mode data may be the input data. For example, the input data is B-mode data based on the third harmonic component. In this case, the saturation reduction processing circuitry116applies the saturation reduction processing to the reflected wave data being the source of the input data. The reflected wave data subjected to the saturation reduction processing is turned into B-mode data by the B-mode processing circuitry130. In this B-mode data based on the reflected wave data subjected to the saturation reduction processing, effect of saturation is reduced in comparison with the B-mode data as the input data. The B-mode data based on the reflected wave data acquired by being subjected to this saturation reduction processing is the target data. For example, the reflected wave data output from the beam former115passes through the B-mode processing circuitry130and is turned into the B-mode image data by the image generation circuitry150. This B-mode image data may be the input data. For example, the input data is B-mode image data based on the third harmonic component. In this case, the saturation reduction processing circuitry116applies the saturation reduction processing to the reflected wave data being the source of the input data. The reflected wave data subjected to the saturation reduction processing then passes through the B-mode processing circuitry130and is turned into B-mode image data by the image generation circuitry150. In this B-mode image data based on the reflected wave data subjected to the saturation reduction processing, effect of saturation is reduced in comparison with the B-mode image data as the input data. The B-mode image data based on the reflected wave data acquired by being subjected to this saturation reduction processing is the target data.

The reflected wave data, B-mode data, and B-mode image data being the input data are examples of a first ultrasound signal containing a saturated signal. The reflected wave data, B-mode data, and B-mode image data being the target data are examples of a second ultrasound signal in which effect of saturation is reduced from the input data.

The learning apparatus200uses the input data and target data generated by the above-described method to train a learning model, thereby generating the trained model170a. At this time, the learning apparatus200generates the trained model170afor each site to be scanned. The ultrasound diagnosis apparatus1then acquires the trained model170agenerated for each site from the learning apparatus200and stores the acquired trained model170afor each site in the storage circuitry170.

FIG.6is a diagram illustrating example input data and target data according to the first embodiment. An input data20contains a signal (saturated signal)20aaffected by saturation. On the other hand, reduction of a signal value of the saturated signal20ain the input data20yields target data21. The signal value of a signal21ain the target data21is smaller than the signal value of the saturated signal20a.

FIG.7is a diagram for describing example processing executed by the ultrasound diagnosis apparatus1at the time of inference using a trained model, according to the first embodiment. At the time of inference, the ultrasound diagnosis apparatus1acquires a trained model170acorresponding to a site to be scanned from the storage circuitry170, uses the acquired trained model170ato infer output data corresponding to input data, and outputs the inferred output data.

As illustrated inFIG.7, for example, the ultrasound diagnosis apparatus1generates input data used at the time of inference in a manner similar to that for the input data used at the time of training. The input data used at the time of inference is data after subjected to the phasing addition processing and is an example third ultrasound signal containing a saturated signal.

When the input data used at the time of inference is input, the trained model170agenerates output data corresponding to the input data and outputs the generated output data. The output data is, for example, data in which effect of saturation is reduced in comparison with the input data used at the time of inference. That is, the output data is data in which the effect of saturation is reduced from the input data used at the time of inference. The output data is an example fourth ultrasound signal.

Here, the input data used at the time of inference is the reflected wave data, B-mode data, or B-mode image data as described above, and a case where the input data used at the time of inference is the reflected wave data will be described below.

In this case, the B-mode processing circuitry130acquires a trained model170acorresponding to a site to be scanned among the trained models170afor individual sites stored in the storage circuitry170. The B-mode processing circuitry130then inputs the input data used at the time of inference to the acquired trained model170a. For example, as described above, the B-mode processing circuitry130adds up three pieces of reflected wave data acquired through three ultrasound transmissions to extract the third harmonic component and inputs the extracted third harmonic component to the trained model170aas the input data.

The B-mode processing circuitry130then acquires output data output from the trained model170a. Here, the output data output from the trained model170ais signal data containing the third harmonic component in which effect of saturation is reduced. Then, the B-mode processing circuitry130generates B-mode data on the basis of the output data, and the image generation circuitry150generates B-mode image data from the B-mode data as ultrasound image data.

Thus, the ultrasound diagnosis apparatus1of the first embodiment can acquire ultrasound image data in which effect of saturation is robustly reduced and degradation in image quality is restrained.

Note that if the input data used at the time of inference is the B-mode data, the B-mode processing circuitry130performs similar processing. In specific, the B-mode processing circuitry130inputs the B-mode data to the trained model170aas the input data. The B-mode processing circuitry130then acquires output data output from the trained model170a. Here, the output data output from the trained model170ais B-mode data in which effect of saturation is reduced. The B-mode processing circuitry130then transmits the acquired output data (B-mode data in which the effect of saturation is reduced) to the image generation circuitry150. The image generation circuitry150generates B-mode image data in which effect of saturation is reduced from the B-mode data in which the effect of saturation is reduced, as ultrasound image data.

If the input data used at the time of inference is the B-mode image data, the image generation circuitry150performs similar processing. In specific, the image generation circuitry150inputs the B-mode image data to the trained model170aas the input data. The image generation circuitry150then acquires output data output from the trained model170a. Here, the output data output from the trained model170ais B-mode image data in which effect of saturation is reduced. In this way, the image generation circuitry150uses the trained model170ato generate the B-mode image data in which effect of saturation is reduced, from the input data.

FIG.8is a flowchart illustrating an example flow of processing executed by the ultrasound diagnosis apparatus1according to the first embodiment. The processing illustrated inFIG.8is processing in which the ultrasound diagnosis apparatus1extracts the third harmonic component, generates B-mode image data based on the third harmonic component, and displays a B-mode image based on the generated B-mode image data.

As illustrated inFIG.8, the ultrasound diagnosis apparatus1uses a trained model170ato generate B-mode image data in which effect of saturation is robustly reduced and degradation in image quality is restrained (Step S101).

The ultrasound diagnosis apparatus1then displays a B-mode image based on the B-mode image data on the display103(Step S102).

The control circuitry180of the ultrasound diagnosis apparatus1then determines whether scanning is to be continued (Step S103). If scanning is to be continued (Yes at Step S103), the ultrasound diagnosis apparatus1returns to Step S101and executes each process at Steps S101to S103again. Note that each process at Steps S101to S103is executed for each frame of the B-mode image displayed on the display103. This enables the B-mode image to be displayed on the display103as a moving image.

If scanning is not to be continued (No at Step S103), the ultrasound diagnosis apparatus1ends the processing illustrated inFIG.8.

FIG.9Ais a diagram illustrating an example B-mode image based on B-mode image data acquired from input data used at the time of training according to the first embodiment.FIG.9Bis a diagram illustrating an example B-mode image based on B-mode image data acquired from target data used at the time of training according to the first embodiment.FIG.9Cis a diagram illustrating an example B-mode image based on B-mode image data acquired from output data output from the trained model170aat the time of inference according to the first embodiment.

Portions (saturated regions) indicated by the arrows in a B-mode image22based on the input data used at the time of training, illustrated inFIG.9A, are affected by saturation. Excessive contrast is provided to the saturated regions in comparison with the surroundings of the saturated regions.

In a B-mode image23based on the target data used at the time of training, illustrated inFIG.9B, brightness of the regions corresponding to the saturated regions inFIG.9Ais decreased, resulting in reduction in a visual offense to the eye.

In a B-mode image24based on the output data output from the trained model170aat the time of inference, illustrated inFIG.9C, similar to the B-mode image23, effect of saturation is reduced.

The ultrasound diagnosis apparatus1of the first embodiment has been described. As described above, the ultrasound diagnosis apparatus1can acquire ultrasound image data in which effect of saturation is robustly reduced and degradation in image quality is restrained.

Second Embodiment

Next, an ultrasound diagnosis apparatus1of a second embodiment will be described. In description of the ultrasound diagnosis apparatus1of the second embodiment, points different from the ultrasound diagnosis apparatus1of the first embodiment are mainly described, and description of constituents similar to those of the ultrasound diagnosis apparatus1of the first embodiment may be omitted.

A method of generating input data and target data used for machine learning at the learning apparatus200in the second embodiment will be described with reference toFIG.10.FIG.10is a diagram for describing an example input data and target data generation method according to the second embodiment. Note that the B-mode processing circuitry130connected to the subsequent stage of the beam former115is omitted inFIG.10.

As illustrated inFIG.10, the method of generating the input data used at the time of training in the second embodiment is similar to the method of generating the input data used at the time of training in the first embodiment.

On the other hand, the method of generating the target data used at the time of training in the second embodiment differs from the method of generating the target data used at the time of training in the first embodiment. This point will be described specifically.

For example, as illustrated inFIG.10, a reflected wave signal acquired by scanning a predetermined position of the subject P by the ultrasound probe101passes through the analog front end113and is turned into a digital signal by the A/D conversion circuitry114. The saturation reduction processing circuitry116then applies saturation reduction processing reducing effect of saturation on this digital reflected wave signal. The reflected wave signal in which effect of saturation is reduced passes through the beam former115and the B-mode processing circuitry130and is subjected to processing similar to the processing acquiring the third harmonic component in the above-described first embodiment, thereby acquiring the third harmonic component. In the second embodiment, reflected wave data based on this third harmonic component, B-mode data based on the third harmonic component, or B-mode image data based on the third harmonic component is used as the target data. That is, the target data is acquired by reducing effect of saturation on the reflected wave signal after converted into a digital signal and before subjected to phasing addition processing.

Example saturation reduction processing executed by the saturation reduction processing circuitry116of the second embodiment will be described. For example, the saturation reduction processing circuitry116uses a technique similar to the technique described in Japanese Patent Application Laid-open No. 2017-55845 to reduce effect of saturation on the reflected wave signal. For example, the saturation reduction processing circuitry116determines whether the reflected wave signal is saturated for each channel. To provide description with a specific example, the saturation reduction processing circuitry116detects saturation using a state where the value of the reflected wave signal output from the A/D conversion circuitry114is at a positive upper or negative lower digital limit. Note that the saturation reduction processing circuitry116may determine that the reflected wave signal is saturated if the value of the reflected wave signal is equal to or greater than a predetermined threshold, and determine that the reflected wave signal is not saturated if the value of the reflected wave signal is smaller than the predetermined threshold. The saturation reduction processing circuitry116then multiplies the value of the reflected wave signal of a channel determined to be saturated by a coefficient smaller than 1 and outputs the reflected wave signal (reflected wave signal of the channel determined to be saturated) acquired as a result of the multiplication to the beam former115. On the other hand, the saturation reduction processing circuitry116outputs the reflected wave signal of a channel determined not to be saturated to the beam former115as it is. Thus, the target data is acquired by determining whether the reflected wave signal is saturated for each channel and by adding weight to the reflected wave signal for each channel while using the coefficient for each channel in accordance with the determination result as the weight.

Furthermore, the saturation reduction processing circuitry116may apply another saturation reduction processing to the reflected wave signal. For example, the saturation reduction processing circuitry116determines whether the reflected wave signal is saturated for each channel. The saturation reduction processing circuitry116then estimates a value of the reflected wave signal of a channel determined to be saturated through interpolation processing using the value of the reflected wave signal of a channel determined not to be saturated. The saturation reduction processing circuitry116then replaces the value of the reflected wave signal of the channel determined to be saturated with the estimated reflected wave signal value. The saturation reduction processing circuitry116then outputs the value, after the replacement, of the reflected wave signal of the channel determined to be saturated, to the beam former115. On the other hand, the saturation reduction processing circuitry116outputs the reflected wave signal of a channel determined not to be saturated to the beam former115as it is. Thus, the target data is acquired by determining whether the reflected wave signal is saturated for each channel and by replacing the value of the reflected wave signal of a channel determined to be saturated with a reflected wave signal value estimated using the value of the reflected wave signal of a channel determined not to be saturated.

In the reflected wave signal subjected to the saturation reduction processing, effect of saturation is reduced in comparison with the reflected wave signal that is not subjected to the saturation reduction processing. The target data based on the reflected wave signal subjected to such saturation reduction processing is an example second ultrasound signal.

The ultrasound diagnosis apparatus1then transmits the input data and target data generated in this way to the learning apparatus200.

The learning apparatus200uses the input data and target data generated by the above-described method to train a training model, thereby generating a trained model170b(seeFIG.12). At this time, the learning apparatus200generates the trained model170bfor each site to be scanned. The ultrasound diagnosis apparatus1then acquires the trained model170bgenerated for each site from the learning apparatus200and stores the acquired trained model170bfor each site in the storage circuitry170.

FIG.11is a diagram illustrating example input data and target data according to the second embodiment. Input data25acontains a signal (saturated signal)25caffected by saturation. A reflected wave signal25being the source of the input data25acontains a saturated signal corresponding to the saturated signal25c.

On the other hand, reduction of a signal value of the saturated signal in the reflected wave signal25yields target data26b. In specific, reduction of the signal value of the saturated signal in the reflected wave signal25generates a reflected wave signal26. In a signal26aof the reflected wave signal26corresponding to the saturated signal of the reflected wave signal25, effect of saturation is reduced. Thus, the signal value of a signal26cin the target data26bis reduced from the signal value of the saturated signal25c.

FIG.12is a diagram for describing example processing executed by the ultrasound diagnosis apparatus1at the time of inference of the trained model170b, according to the second embodiment. At the time of inference, the ultrasound diagnosis apparatus1acquires a trained model170bcorresponding to a site to be scanned from the storage circuitry170, uses the acquired trained model170bto infer output data corresponding to input data, and outputs the inferred output data.

As illustrated inFIG.12, for example, the ultrasound diagnosis apparatus1generates input data used at the time of inference in a manner similar to that for the input data used at the time of training.

When the input data used at the time of inference is input, the trained model170bgenerates output data corresponding to the input data and outputs the generated output data. The output data is, for example, data in which effect of saturation is reduced in comparison with the input data used at the time of inference. That is, the output data is data in which the effect of saturation is reduced from the input data used at the time of inference. The output data is an example fourth ultrasound signal.

At the time of inference, the ultrasound diagnosis apparatus1of the second embodiment executes processing similar to the processing executed by the ultrasound diagnosis apparatus1of the first embodiment.

Thus, similar to the first embodiment, the ultrasound diagnosis apparatus1of the second embodiment can acquire ultrasound image data in which effect of saturation is robustly reduced and degradation in image quality is retrained.

Third Embodiment

Next, an ultrasound diagnosis apparatus1of a third embodiment will be described. In description of the ultrasound diagnosis apparatus1of the third embodiment, points different from the ultrasound diagnosis apparatus1of each of the above-described embodiments are mainly described, and description of constituents similar to those of the ultrasound diagnosis apparatus1of each of the above-described embodiments may be omitted.

A method of generating input data and target data used for machine learning at the learning apparatus200in the third embodiment will be described with reference toFIG.13.FIG.13is a diagram for describing an example input data and target data generation method according to the third embodiment.

As illustrated inFIG.13, the method of generating the input data used at the time of training in the third embodiment is similar to the method of generating the input data used at the time of training in the first embodiment.

On the other hand, the method of generating the target data used at the time of training in the third embodiment differs from the method of generating the target data used at the time of training in the first embodiment. This point will be described specifically.

For example, as illustrated inFIG.13, a reflected wave signal acquired by scanning a predetermined position of the subject P by the ultrasound probe101is subjected to various types of analog processing by the analog front end113. The saturation reduction processing circuitry116then applies saturation reduction processing reducing effect of saturation on the reflected wave signal being an analog signal subjected to the various types of analog processing.

Example saturation reduction processing executed by the saturation reduction processing circuitry116of the third embodiment will be described. For example, the saturation reduction processing circuitry116uses a known analog filter, such as a prefilter, to reduce effect of saturation on the reflected wave signal. For example, the saturation reduction processing circuitry116uses the prefilter to execute processing restraining a signal component (saturation-derived component) contained in the reflected wave signal and caused by saturation, as saturation reduction processing. The saturation reduction processing circuitry116then outputs the reflected wave signal subjected to the saturation reduction processing to the A/D conversion circuitry114.

Furthermore, the saturation reduction processing circuitry116may apply another saturation reduction processing to the reflected wave signal. For example, the saturation reduction processing circuitry116determines whether the reflected wave signal is saturated. The saturation reduction processing circuitry116then applies an analog gain to the reflected wave signal determined to be saturated to reduce the amplitude value of the reflected wave signal. The saturation reduction processing circuitry116then outputs the reflected wave signal applied with the analog gain to the A/D conversion circuitry114. On the other hand, the saturation reduction processing circuitry116outputs the reflected wave signal determined not to be saturated to the A/D conversion circuitry114as it is.

To the A/D conversion circuitry114, the reflected wave signal output from the saturation reduction processing circuitry116is input. The A/D conversion circuitry114converts the input reflected wave signal into a digital signal and outputs the digital reflected wave signal in which effect of saturation is reduced, to the beam former115.

The digital reflected wave signal in which effect of saturation is reduced then passes through the beam former115and the B-mode processing circuitry130and is subjected to processing similar to the processing acquiring the third harmonic component in the above-described first embodiment, thereby acquiring the third harmonic component. In the third embodiment, reflected wave data based on this third harmonic component, B-mode data based on the third harmonic component, or B-mode image data based on the third harmonic component is used as the target data.

This target data is an example second ultrasound signal. In this way, the target data is data after conversion of the reflected wave signal being an analog signal subjected to the saturation reduction processing reducing effect of saturation, into a digital signal. Furthermore, the target data is data after conversion of the reflected wave signal subjected to the saturation reduction processing applying an analog gain in accordance with a result of the determination of saturation of the reflected wave signal, into a digital signal.

The ultrasound diagnosis apparatus1then transmits the input data and target data generated in this way to the learning apparatus200.

The learning apparatus200uses the input data and target data generated by the above-described method to train a training model, thereby generating a trained model170c(seeFIG.15). At this time, the learning apparatus200generates the trained model170cfor each site to be scanned. The ultrasound diagnosis apparatus1then acquires the trained model170cgenerated for each site from the learning apparatus200and stores the acquired trained model170cfor each site in the storage circuitry170.

FIG.14is a diagram illustrating example input data and target data according to the third embodiment. As illustrated inFIG.14, the analog front end113clips the amplitude of a reflected wave signal27equal to or greater than a certain value to the certain value to generate a reflected wave signal27a. The A/D conversion circuitry114then converts the reflected wave signal27abeing an analog signal into a reflected wave signal27bbeing a digital signal. The ultrasound diagnosis apparatus1then generates input data27cfrom the reflected wave signal27b.

The input data27ccontains a signal (saturated signal)27daffected by saturation.

On the other hand, the saturation reduction processing circuitry116uses the prefilter to execute the saturation reduction processing restraining a signal component contained in the reflected wave signal27aand caused by saturation. This generates a reflected wave signal28subjected to the saturation reduction processing. The A/D conversion circuitry114then converts the reflected wave signal28being an analog signal into a reflected wave signal28abeing a digital signal. The ultrasound diagnosis apparatus1then generates target data28bfrom the reflected wave signal28a. The signal value of a signal28cin the target data28bis reduced from the signal value of the signal27d, corresponding to the signal28c, in the input data27c.

FIG.15is a diagram for describing example processing executed by the ultrasound diagnosis apparatus1at the time of inference of the trained model170c, according to the third embodiment. At the time of inference, the ultrasound diagnosis apparatus1acquires a trained model170ccorresponding to a site to be scanned from the storage circuitry170, uses the acquired trained model170cto infer output data corresponding to input data, and outputs the inferred output data.

As illustrated inFIG.15, for example, the ultrasound diagnosis apparatus1generates input data used at the time of inference in a manner similar to that for the input data used at the time of training.

When the input data used at the time of inference is input, the trained model170cgenerates output data corresponding to the input data and outputs the generated output data. The output data is, for example, data in which effect of saturation is reduced in comparison with the input data used at the time of inference. That is, the output data is data in which the effect of saturation is reduced from the input data used at the time of inference. The output data is an example fourth ultrasound signal.

At the time of inference, the ultrasound diagnosis apparatus1of the third embodiment executes processing similar to the processing executed by the ultrasound diagnosis apparatus1of the first embodiment.

Thus, similar to the first embodiment and the like, the ultrasound diagnosis apparatus1of the third embodiment can acquire ultrasound image data in which effect of saturation is robustly reduced and degradation in image quality is retrained.

Fourth Embodiment

Next, an ultrasound diagnosis apparatus1of a fourth embodiment will be described. In description of the ultrasound diagnosis apparatus1of the fourth embodiment, points different from the ultrasound diagnosis apparatus1of each of the above-described embodiments are mainly described, and description of constituents similar to those of the ultrasound diagnosis apparatus1of each of the above-described embodiments may be omitted.

A method of generating input data and target data used for machine learning at the learning apparatus200in the fourth embodiment will be described with reference toFIG.16.FIG.16is a diagram for describing an example input data and target data generation method according to the fourth embodiment.

As illustrated inFIG.16, a reflected wave signal acquired by scanning a predetermined position of the subject P by the ultrasound probe101passes through the analog front end113and is converted into a digital signal by the A/D conversion circuitry114. A reflected wave signal of this digital signal is the input data. This reflected wave signal being the input data is an example first ultrasound signal containing a saturated signal. Furthermore, the reflected wave data being the input data is data after converted into a digital signal and before subjected to phasing addition processing.

Furthermore, the saturation reduction processing circuitry116applies saturation reduction processing reducing effect of saturation on the digital reflected wave signal being the input data. The saturation reduction processing circuitry116of the fourth embodiment applies saturation reduction processing similar to the saturation reduction processing executed by the saturation reduction processing circuitry116of the second embodiment, to the reflected wave signal.

In the reflected wave signal subjected to the saturation reduction processing, effect of saturation is reduced in comparison with the reflected wave signal as the input data. The reflected wave signal subjected to this saturation reduction processing is the target data. The reflected wave signal subjected to the saturation reduction processing is an example second ultrasound signal in which effect of saturation is reduced from the input data.

The ultrasound diagnosis apparatus1then transmits the input data and target data generated in this way to the learning apparatus200.

The learning apparatus200uses the input data and target data generated by the above-described method to train a training model, thereby generating a trained model170d(seeFIG.18). At this time, the learning apparatus200generates the trained model170dfor each site to be scanned. The ultrasound diagnosis apparatus1then acquires the trained model170dgenerated for each site from the learning apparatus200and stores the acquired trained model170dfor each site in the storage circuitry170.

FIG.17is a diagram illustrating example input data and target data according to the fourth embodiment. Input data29contains a saturated signal affected by saturation.

On the other hand, reduction of a signal value of the saturated signal in the input data29yields target data30. In a signal30aof the target data30corresponding to the saturated signal of the input data29, effect of saturation is reduced. Thus, the signal value of the signal30aof the target data30is reduced from the signal value of the saturated signal of the input data29.

FIG.18is a diagram for describing example processing executed by the ultrasound diagnosis apparatus1at the time of inference of the trained model170d, according to the fourth embodiment. At the time of inference, the ultrasound diagnosis apparatus1acquires a trained model170dcorresponding to a site to be scanned from the storage circuitry170, uses the acquired trained model170dto infer output data corresponding to input data, and outputs the inferred output data.

As illustrated inFIG.18, for example, the ultrasound diagnosis apparatus1generates input data used at the time of inference in a manner similar to that for the input data used at the time of training. Here, the input data is generated for each channel. The input data used at the time of inference is an example third ultrasound signal containing a saturated signal. Furthermore, the input data is data after converted into a digital signal and before subjected to phasing addition processing.

When the input data used at the time of inference is input, the trained model170dgenerates output data corresponding to the input data and outputs the generated output data. The output data is, for example, data in which effect of saturation is reduced in comparison with the input data used at the time of inference. That is, the output data is data in which the effect of saturation is reduced from the input data used at the time of inference. The output data is an example fourth ultrasound signal.

The A/D conversion circuitry114acquires a trained model170dcorresponding to a site to be scanned among the trained models170dfor individual sites stored in the storage circuitry170. The A/D conversion circuitry114then inputs the input data used at the time of inference to the acquired trained model170dfor each channel.

The A/D conversion circuitry114acquires the output data output from the trained model170dto generate the output data as a reflected wave signal for each channel. The A/D conversion circuitry114then outputs the generated reflected wave signal to the beam former115. The beam former115applies phasing addition processing to the input reflected wave signal to generate reflected wave data.

When the ultrasound diagnosis apparatus1extracts the third harmonic component, the receiving circuitry112uses the above-described method using the trained model170dto generate three pieces of reflected wave data relating to a common reception scanning line on the basis of a plurality of reflected wave signals acquired through three ultrasound transmissions. The B-mode processing circuitry130then adds up the three pieces of reflected wave data to extract the third harmonic component. That is, the B-mode processing circuitry130extracts the third harmonic component as a high-frequency component of a multiple order of 3 from the reflected wave data based on the output data output from the trained model170d.

Here, the three pieces of reflected wave data used for extracting the third harmonic component are data in which effect of saturation is reduced. Thus, similar to the first embodiment and the like, the ultrasound diagnosis apparatus1of the fourth embodiment can acquire ultrasound image data in which effect of saturation is robustly reduced and degradation in image quality is restrained.

Fifth Embodiment

Next, an ultrasound diagnosis apparatus1of a fifth embodiment will be described. In description of the ultrasound diagnosis apparatus1of the fifth embodiment, points different from the ultrasound diagnosis apparatus1of each of the above-described embodiments are mainly described, and description of constituents similar to those of the ultrasound diagnosis apparatus1of each of the above-described embodiments may be omitted.

A method of generating input data and target data used for machine learning at the learning apparatus200in the fifth embodiment will be described with reference toFIG.19.FIG.19is a diagram for describing an example input data and target data generation method according to the fifth embodiment.

As illustrated inFIG.19, the method of generating the input data used at the time of training in the fifth embodiment is similar to the method of generating the input data used at the time of training in the fourth embodiment. The method of generating the target data used at the time of training in the fifth embodiment will be described. For example, as illustrated inFIG.19, a reflected wave signal acquired by scanning a predetermined position of the subject P by the ultrasound probe101is subjected to various types of analog processing by the analog front end113. The saturation reduction processing circuitry116then applies saturation reduction processing reducing effect of saturation on the reflected wave signal being an analog signal subjected to the various types of analog processing.

Example saturation reduction processing executed by the saturation reduction processing circuitry116of the fifth embodiment will be described. For example, the saturation reduction processing circuitry116applies saturation reduction processing similar to the saturation reduction processing executed by the saturation reduction processing circuitry116of the third embodiment, to the reflected wave signal. The saturation reduction processing circuitry116then outputs the reflected wave signal subjected to the saturation reduction processing to the A/D conversion circuitry114.

To the A/D conversion circuitry114, the reflected wave signal output from the saturation reduction processing circuitry116is input. The A/D conversion circuitry114converts the input reflected wave signal into a digital signal.

In the reflected wave signal being the digital signal subjected to the saturation reduction processing, effect of saturation is reduced in comparison with the reflected wave signal as the input data. The reflected wave signal being the digital signal subjected to this saturation reduction processing is the target data. This reflected wave signal being the target data is an example second ultrasound signal. In this way, the target data is a reflected wave signal being an analog signal subjected to the saturation reduction processing reducing effect of saturation. Furthermore, the target data is a reflected wave signal subjected to the saturation reduction processing applying an analog gain in accordance with a result of the determination of saturation of the reflected wave signal.

The ultrasound diagnosis apparatus1then transmits the input data and target data generated in this way to the learning apparatus200.

The learning apparatus200uses the input data and target data generated by the above-described method to train a training model, thereby generating a trained model170e(seeFIG.21). At this time, the learning apparatus200generates the trained model170efor each site to be scanned. The ultrasound diagnosis apparatus1then acquires the trained model170egenerated for each site from the learning apparatus200and stores the acquired trained model170efor each site in the storage circuitry170.

FIG.20is a diagram illustrating example input data and target data according to the fifth embodiment. As illustrated inFIG.20, the analog front end113clips the amplitude of a reflected wave signal31equal to or greater than a certain value to the certain value to generate a reflected wave signal31a. The A/D conversion circuitry114then converts the reflected wave signal31abeing an analog signal into a reflected wave signal31bbeing a digital signal. This reflected wave signal31bis the input data. The input data contains a saturated signal affected by saturation.

On the other hand, the saturation reduction processing circuitry116uses the prefilter to execute the saturation reduction processing restraining a signal component contained in the reflected wave signal31aand caused by saturation. This generates a reflected wave signal32subjected to the saturation reduction processing. The A/D conversion circuitry114then converts the reflected wave signal32being an analog signal into a reflected wave signal32abeing a digital signal. This reflected wave signal32ais the target data.

The signal value of a signal (signal corresponding to the saturated signal of the reflected wave signal31b) of the reflected wave signal32abeing the target data is reduced from the signal value of the saturated signal of the reflected wave signal31bbeing the input data.

FIG.21is a diagram for describing example processing executed by the ultrasound diagnosis apparatus1at the time of inference of the trained model170e, according to the fifth embodiment. At the time of inference, the ultrasound diagnosis apparatus1acquires a trained model170ecorresponding to a site to be scanned from the storage circuitry170, uses the acquired trained model170eto infer output data corresponding to input data, and outputs the inferred output data.

As illustrated inFIG.21, for example, the ultrasound diagnosis apparatus1generates input data used at the time of inference in a manner similar to that for the input data used at the time of training.

When the input data used at the time of inference is input, the trained model170egenerates output data corresponding to the input data and outputs the generated output data. The output data is, for example, data in which effect of saturation is reduced in comparison with the input data used at the time of inference. That is, the output data is data in which the effect of saturation is reduced from the input data used at the time of inference. The output data is an example fourth ultrasound signal.

The A/D conversion circuitry114acquires a trained model170ecorresponding to a site to be scanned among the trained models170efor individual sites stored in the storage circuitry170. The A/D conversion circuitry114then inputs the input data used at the time of inference to the acquired trained model170efor each channel.

The A/D conversion circuitry114acquires the output data output from the trained model170eto generate the output data as a reflected wave signal for each channel. The A/D conversion circuitry114then outputs the generated reflected wave signal to the beam former115. The beam former115applies phasing addition processing to the input reflected wave signal to generate reflected wave data.

When the ultrasound diagnosis apparatus1extracts the third harmonic component, the receiving circuitry112uses the above-described method using the trained model170eto generate three pieces of reflected wave data relating to a common reception scanning line on the basis of a plurality of reflected wave signals acquired through three ultrasound transmissions. The B-mode processing circuitry130then adds up the three pieces of reflected wave data to extract the third harmonic component. That is, the B-mode processing circuitry130extracts the third harmonic component as a high-frequency component of a multiple order of 3 from the reflected wave data based on the output data output from the trained model170e.

Here, the three pieces of reflected wave data used for extracting the third harmonic component are data in which effect of saturation is reduced. Thus, similar to the first embodiment and the like, the ultrasound diagnosis apparatus1of the fifth embodiment can acquire ultrasound image data in which effect of saturation is robustly reduced and degradation in image quality is restrained.

Modification

Next, an ultrasound diagnosis apparatus1of a modification will be described.FIG.22is a flowchart illustrating an example flow of processing executed by the ultrasound diagnosis apparatus1according to the modification. In each of the above-described embodiments, as illustrated inFIG.22, when the third harmonic component is extracted, the control circuitry180of the ultrasound diagnosis apparatus1determines whether input data used at the time of inference is affected by saturation (Step S201). If it is determined that the input data used at the time of inference is affected by saturation (Yes at Step S201), the ultrasound diagnosis apparatus1may execute the above-described processes at Steps S101to S103. For example, at Step S101, the ultrasound diagnosis apparatus1performs the above-described process using a trained model (trained model170a,170b,170c,170d,170e) to extract the third harmonic component and generates B-mode image data based on the extracted third harmonic component.

On the other hand, if it is determined that the input data used at the time of inference is not affected by saturation (No at Step S201), the ultrasound diagnosis apparatus1extracts the third harmonic component with no trained model used and generates B-mode image data based on the extracted third harmonic component (Step S202). For example, at Step S202, three pieces of reflected wave data used when the B-mode processing circuitry130extracts the third harmonic component are reflected wave data generated by the beam former115with no trained model used. Then, the ultrasound diagnosis apparatus1proceeds to Step S102.

Note that the computer program executed by the processor is provided while being incorporated in a read only memory (ROM), the storage circuitry, or the like in advance. Note that the computer program may be provided as a file in a format installable or executable for these devices while being recorded in a computer-readable non-transitory storage medium, such as a compact disc (CD)-ROM, a flexible disk (FD), a CD-Recordable (R), and a digital versatile disc (DVD). Alternatively, the computer program may be provided or distributed by being stored in a computer connected to a network, such as the Internet, and downloaded via the network. For example, the computer program is composed of a module including each of the above-described processing functions. As actual hardware, a CPU reads out the computer program from the recording medium, such as a ROM, and executes the computer program to load and generate each module on a main storage device.

According to at least one embodiment or at least one modification described above, an ultrasound signal can be acquired in which effect of saturation is robustly reduced and degradation in image quality is restrained.

While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions.