JP7447680B2 - Ultrasonic diagnostic device, control program for the ultrasonic diagnostic device, and method for controlling the ultrasonic diagnostic device - Google Patents

Description

The present disclosure relates to an ultrasound diagnostic device, a control program for the ultrasound diagnostic device, and a method for controlling the ultrasound diagnostic device.

2. Description of the Related Art Ultrasonic diagnostic apparatuses that use an ultrasound probe to image tissue within a subject are known.

In this type of ultrasonic diagnostic equipment, an ultrasonic probe is brought into contact with the surface of the subject, an ultrasonic beam generated by the probe is made to enter the subject, and the reflected waves are received. This method measures the distribution of reflection coefficients in the depth direction, and creates a two-dimensional image of the tomographic plane by scanning the inside of the subject in a fan-shape, for example, along the tomographic plane with an ultrasound beam. (hereinafter referred to as an "ultrasound image"). In an ultrasonic diagnostic apparatus, this scan is usually repeated to obtain ultrasonic images one after another in real time.

Conventionally, in this type of ultrasound diagnostic equipment, noise generated in the ultrasound image generated based on the received signal acquired from the ultrasound probe (e.g., thermal noise of electronic circuits, In order to reduce acoustic noise caused by scattering, multiple reflections, reverberation, etc., the ultrasound image may be subjected to frame averaging processing as shown in equation (1) below, and then output for display. known (for example, see Patent Document 1).
Qn=α×Do+(1-α)×Dn...Formula (1)

In equation (1), Qn is the frame data output by frame averaging processing, Dn is the currently input new frame data (i.e., the ultrasound image generated based on the received signal acquired from the ultrasound probe), Do is old frame data that was displayed and output one frame ago (that is, frame data that was generated one frame ago by frame averaging processing). Further, α is a weighting coefficient, and has a value in the range of 0<α≦1. When you want to observe a fast-moving image with good tracking performance, set α = 0 and do not perform frame averaging processing.On the other hand, when you want to sufficiently reduce noise with an image that does not move much, set α to 0. Increase the coefficient α.

Japanese Patent Application Publication No. 5-220138

A fundamental problem with such frame averaging processing is that there is a trade-off relationship between noise removal and tracking ability for moving tissue structures. In order to effectively remove noise, you can increase the weighting coefficient α, but this will include more of the previous frame image, so areas with movement will be displayed and output as blurred images, and areas with movement will be displayed as blurred images. The ability to follow tissue structures deteriorates. On the other hand, if the weighting coefficient α is made smaller so as to reduce blur, noise cannot be effectively removed this time.

From this point of view, for example, Patent Document 1 discloses that the difference between old frame data and new frame data is determined for each pixel, a different weighting coefficient α is set for each pixel, and then frame averaging processing is performed. Are listed. According to the prior art according to Patent Document 1, the weighting coefficient α can be set small for a tissue structure that moves, so it is possible to obtain a certain degree of effect in ensuring followability. .

However, the conventional technique disclosed in Patent Document 1 has a problem in that when the tissue structure moves, noise superimposed on the tissue structure cannot be reduced completely. In particular, in the conventional technique disclosed in Patent Document 1, noise superimposed on high-brightness areas such as membrane tissues and blood vessel walls remains, causing flickering in the ultrasound image.

The present disclosure has been made in view of the above-mentioned problems, and includes an ultrasonic diagnostic apparatus that can effectively remove noise and improve tracking ability for moving tissue structures when outputting an ultrasonic image; An object of the present invention is to provide a control program for an ultrasonic diagnostic device and a method for controlling the ultrasonic diagnostic device.

The main disclosure that solves the above-mentioned problems is:
a transmitter/receiver unit that receives a reception signal related to an ultrasound echo from the ultrasound probe;
a signal processing unit that generates frame data constituting an ultrasound image based on the received signal;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. a frame averaging processing unit;
An ultrasonic diagnostic device comprising:
The frame averaging processing unit weights and adds the first frame data and the second frame data so that different weighting is performed for each spatial frequency band,
In the frame averaging processing unit, the weight of the first frame data set for a tissue structure with a low spatial frequency is the weight of the first frame data set for a tissue structure with a high spatial frequency. greater than,
It is an ultrasound diagnostic device.

Also, in other situations,
to the computer,
a first process of receiving a reception signal related to an ultrasound echo from an ultrasound probe;
a second process of generating frame data constituting an ultrasound image based on the received signal;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. Third processing;
A control program for an ultrasonic diagnostic device that executes the
In the third process, the first frame data and the second frame data are weighted and added so that different weighting is performed for each spatial frequency band,
In the third process, the weight of the first frame data set for a tissue structure with a low spatial frequency is greater than the weight of the first frame data set for a tissue structure with a high spatial frequency. big,
This is a control program for an ultrasound diagnostic device.

Also, in other situations,
a first process of receiving a reception signal related to an ultrasound echo from an ultrasound probe;
a second process of generating frame data constituting an ultrasound image based on the received signal;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. Third processing;
A method of controlling an ultrasonic diagnostic apparatus comprising:
In the third process, the first frame data and the second frame data are weighted and added so that different weighting is performed for each spatial frequency band,
In the third process, the weight of the first frame data set for a tissue structure with a low spatial frequency is greater than the weight of the first frame data set for a tissue structure with a high spatial frequency. big,
This is a method of controlling an ultrasonic diagnostic device.

According to the ultrasonic diagnostic apparatus according to the present disclosure, when outputting an ultrasonic image, it is possible to effectively remove noise and improve followability for a moving tissue structure.

A diagram showing the configuration of an ultrasound diagnostic apparatus according to the first embodiment A diagram showing the configuration of a frame averaging processing unit according to the first embodiment Flowchart showing the operation of the frame averaging processing unit according to the first embodiment A diagram showing the configuration of a frame averaging processing unit according to the second embodiment A diagram showing the configuration of a frame averaging processing unit according to the third embodiment A diagram showing a frequency band in an ultrasound image extracted by a wideband filter and a frequency band in an ultrasound image extracted by a narrowband filter in the signal processing unit according to the third embodiment. A diagram showing the configuration of a frame averaging processing unit according to the fourth embodiment A diagram showing the configuration of an ultrasound diagnostic apparatus according to a fifth embodiment

Preferred embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. Note that in this specification and the drawings, components having substantially the same functions are designated by the same reference numerals and redundant explanation will be omitted.

(First embodiment)
[Configuration of ultrasound diagnostic equipment]
Hereinafter, with reference to FIG. 1, the configuration of an ultrasonic diagnostic apparatus according to a first embodiment of the present invention will be described. As described above, the ultrasonic diagnostic apparatus is used to visualize the shape, properties, or dynamics inside a subject as an ultrasonic image and perform image diagnosis.

FIG. 1 is a diagram showing the configuration of an ultrasonic diagnostic apparatus A according to this embodiment.

The ultrasound diagnostic apparatus A includes an ultrasound probe 1, a transmitting/receiving section 2, a signal processing section 3, a frame averaging processing section 4, a frame memory 5, and a display 6.

The ultrasonic probe 1 transmits an ultrasonic beam (here, approximately 1 to 30 MHz) into a subject (for example, a human body), and also transmits ultrasonic waves reflected within the subject from among the transmitted ultrasonic beams. It functions as an acoustic sensor that receives echoes and converts them into electrical signals. The ultrasonic probe 1 is typically an ultrasonic diagnostic apparatus equipped with a transmitter/receiver 2, a signal processor 3, a frame averaging processor 4, a frame memory 5, and a display 6 via a cable. It is connected to the main body of A. During an ultrasound examination, the ultrasound probe 1 is held by a user and transmits and receives ultrasound waves with the transmission and reception surface of the ultrasound probe 1 in contact with the subject.

The ultrasonic probe 1 includes, for example, a plurality of transducers (e.g., piezoelectric elements) arranged in a matrix, and turns on and off the driving states of the plurality of transducers individually or in units of blocks (i.e., in units of channels). It is configured to include a channel switching unit (for example, a multiplexer) for controlling switching. Each transducer of the ultrasound probe 1 converts the voltage pulse generated by the transmitter 2a into an ultrasound beam, transmits it into the subject, receives the ultrasound echo reflected inside the subject, and generates an electrical signal ( (hereinafter referred to as a "received signal") and output to the receiver 2b. Then, the transducers to be driven by the ultrasound probe 1 are sequentially switched along the scanning direction, thereby performing ultrasound scanning within the subject.

The transmitter/receiver unit 2 is a drive circuit that causes each transducer of the ultrasound probe 1 to transmit and receive ultrasound, and includes a transmitter 2a and a receiver 2b.

The transmitter 2a is a transmitter that sends a voltage pulse, which is a drive signal, to the ultrasound probe 1. The transmitter 2a includes, for example, a high-frequency pulse oscillator, a pulse setting section, and the like. The transmitter 2a adjusts the voltage pulse generated by the high-frequency pulse oscillator to the voltage amplitude, pulse width, and sending timing set by the pulse setting section, and sends it to the ultrasound probe 1.

The receiver 2b is a receiver that receives and processes a received signal related to an ultrasound echo generated by the ultrasound probe 1. The receiver 2b includes a preamplifier, an AD converter, and a reception beamformer. The receiver 2b amplifies a received signal related to a weak ultrasonic echo for each channel using a preamplifier and an AD converter provided for each channel, and converts the received signal into a digital signal. Then, the receiver 2b uses a receiving beamformer to phase and add the received signals of each channel, thereby combining the received signals of the plurality of channels into one signal and converting it into acoustic line data.

Note that the transmitting/receiving unit 2 causes the ultrasound probe 1 to repeatedly perform ultrasound scanning within the subject, and continuously generates frame data constituting an ultrasound image.

The signal processing unit 3 acquires the received signal from the transmitting/receiving unit 2 and sequentially generates ultrasound images inside the subject. For example, when the ultrasound probe 1 transmits a pulsed ultrasound beam in the depth direction, the signal processing unit 3 sequentially stores in a line memory the signal intensities of ultrasound echoes detected thereafter. Then, as the ultrasound probe 1 performs ultrasound scanning inside the subject, the signal processing unit 3 sequentially accumulates the signal intensity of ultrasound echoes at each scanning position in a line memory, and constructs an ultrasound image. Generate frame data. Then, the signal processing unit 3 generates an ultrasound image by converting the signal intensity of ultrasound echoes detected at each position inside the subject into brightness values.

Note that the signal processing section 3 may include an AD conversion section, a gain adjustment section, a quadrature detection section, a filter processing section, a Log compression processing section, a dynamic range adjustment processing section, an enhancement processing section, and the like.

The frame averaging processing unit 4 generates frame data (hereinafter also referred to as "old frame data Do") (hereinafter also referred to as "old frame data Do") (" corresponding to the "second frame data") and frame data (hereinafter also referred to as "new frame data Dn") related to the ultrasound image generated by the signal processing unit 3 at the current time (corresponding to the "first frame data Dn" of the present invention); frame data (hereinafter also referred to as "output frame data Qn") related to the ultrasound image to be displayed and output at the next time is generated by weighted addition of Store. Here, the old frame data Do is frame data generated by the frame averaging processing section 4 one time ago and stored in the frame memory 5 (that is, the output frame data Qn one time ago). Note that the details of the processing by the frame averaging processing section 4 will be described later.

The frame memory 5 stores frame data for one frame to be displayed and output at the next time output from the frame averaging processing section 4. The frame data stored in the frame memory 5 is read out every time the frame averaging processing section 4 performs weighted addition of the old frame data Do and the new frame data Dn, and the frame data generated by the processing is Updated.

Note that, in addition to the output frame data Qn, the frame memory 5 stores first composite image data Qn1 generated when generating the output frame data Qn, as reference information for the calculation processing of the frame averaging processing section 4. and second composite image data Qn2 may be stored (described later with reference to FIG. 2).

The display device 6 is a display that displays the frame data stored in the frame memory 5, and is composed of, for example, a liquid crystal display.

[Detailed configuration of frame averaging processing unit]
FIG. 2 is a diagram showing the configuration of the frame averaging processing section 4 according to this embodiment.

The frame averaging processing unit 4 weights and adds the old frame data Do and the new frame data Dn so that different weighting is performed for each spatial frequency band of the tissue structure shown in the ultrasound image. At this time, in the frame averaging processing unit 4, the weight of the new frame data Dn set for the tissue structure with a low spatial frequency is greater than the weight of the new frame data Dn set for the tissue structure with a high spatial frequency. is also set large. In other words, in the frame averaging processing unit 4, the weight of the new frame data Dn when performing the weighted addition of the general tissue structure (for example, the outline of each tissue) is different from that of the fine tissue structure (for example, the structure of connective tissue). The weight of the new frame data Dn is set to be greater than the weight of the new frame data Dn when weighted addition is performed.

Such a method requires rough tissue structure information (e.g., tissue This is based on the new knowledge of the inventors of the present invention that it is sufficient to use only the contours of each contour, and that in the high frequency region, giving priority to noise removal improves visibility for the user.

The spatial frequency that serves as a reference for the frame averaging processing unit 4 to vary the weighting may be appropriately set in consideration of the balance between the degree of suppression of noise removal and the size of fine tissue structures that sacrifice trackability.

The frame averaging processing section 4 includes a composition processing section 4a and a separation processing section 4b.

The separation processing unit 4b converts the frame data generated by the signal processing unit 3 into rough structure image data in which high frequency components of the tissue structure appearing in the ultrasound image have been cut, and high frequency components of the tissue structure appearing in the ultrasound image. Separate into fine structure image data containing. The separation processing unit 4b generates coarse structure image data by, for example, performing smoothing processing on the frame data generated by the signal processing unit 3, and extracts the coarse structure from the frame data (i.e., the original image). Fine structure image data is generated by subtracting the image data.

In this embodiment, the separation processing section 4b is configured to perform the above separation processing on each of the new frame data Dn obtained from the signal processing section 3 and the old frame data Do obtained from the frame memory 5. .

Specifically, the separation processing unit 4b acquires new frame data Dn from the signal processing unit 3, and each time new frame data Dn is generated in the signal processing unit 3, based on the new frame data Dn, Coarse structure image data (hereinafter referred to as "first coarse structure image data") Dn2 obtained by cutting high frequency components of the tissue structure seen in the ultrasound image, and fine structure image data including the high frequency components of the tissue structure seen in the ultrasound image Dn1 (hereinafter referred to as "first fine structure image data") is generated. Further, the separation processing unit 4b reads the old frame data Do from the frame memory 5, and generates coarse structure image data (hereinafter referred to as rough structure image data) in which high frequency components of the tissue structure appearing in the ultrasound image are cut based on the old frame data Do. , Do2 (hereinafter referred to as "second coarse structure image data") and fine structure image data (hereinafter referred to as "second fine structure image data") Do1 including high frequency components of the tissue structure reflected in the ultrasound image. do.

Note that performing smoothing processing on an image is equivalent to performing low-pass filter processing on the image to extract only low frequency components of the original image. Further, the process of subtracting the smoothed image from the original image is equivalent to extracting only the high frequency components of the original image.

The method of smoothing processing in the separation processing unit 4b may be any known method, but is preferably smoothing processing using an edge preserving filter (for example, a bilateral filter). By using the nonlinear diffusion filter, it is possible to preserve edge portions representing the outline of the tissue structure in the images after the smoothing process (i.e., the first coarse structure image data Dn2 and the second coarse structure image data Do2). be. As a result, the outline of a moving tissue structure can be clearly expressed in the output frame data after image synthesis, and it is possible to better follow the moving tissue structure.

In this embodiment, the second fine structure image data Do1 and the second coarse structure image data Do2 are generated from the old frame data Do in the separation processing unit 4b, but more preferably, the second fine structure image data Do1 and the second coarse structure image data Do2 are generated from the old frame data Do. As the image data Do1 and the second coarse structure image data Do2, the first composite image data Qn1 and the second composite image data Qn2 generated when calculating the output frame data Qn one time ago are used as they are. This eliminates the need for processing by the separation processing unit 4b to separately generate the second fine structure image data Do1 and the second coarse structure image data Do2, and it is possible to reduce calculation processing. In this case, in addition to the frame data generated by the frame averaging processing section 4 to be displayed and output at the next time, the frame memory 5 stores the frame data generated when the frame averaging processing section 4 calculates the frame data. It may be configured to store the first composite image data Qn1 and the second composite image data Qn2.

The synthesis processing unit 4a acquires the first coarse structure image data Dn2 and the first fine structure image data Dn1, and also acquires the second coarse structure image data Do2 and the second fine structure image data Do1. Then, the composition processing unit 4a generates the first composite image data Qn1 by weighting and adding the first fine structure image data Dn1 and the second fine structure image data Do1 at the first ratio, and also generates the first composite image data Qn1 at the second ratio. The coarse structure image data Dn2 and the second coarse structure image data Do2 are weighted and added to generate second composite image data Qn2. Then, the composition processing unit 4a generates output frame data Qn by adding the first composite image data Qn1 and the second composite image data Qn2, and stores the output frame data Qn in the frame memory 5.

Specifically, the synthesis processing unit 4a multiplies the pixel value of each pixel of the first fine structure image data Dn1 by a weighting coefficient (1-α1), as shown in equation (2) below, and First composite image data Qn1 is generated by multiplying the pixel value of each pixel of image data Do1 by weighting coefficient α1, making the pixel positions of both correspond, and adding these.
Qn1=Do1×α1+Dn1×(1−α1) …Formula (2)
(However, Qn1: first composite image data, Dn1: first fine structure image data, Do1: second fine structure image data, α1: weighting coefficient)

Further, the synthesis processing unit 4a multiplies the pixel value of each pixel of the first coarse structure image data Dn2 by a weighting coefficient (1-α2) as shown in the following equation (3), and also multiplies the pixel value of each pixel of the first coarse structure image data Dn2, and The second composite image data Qn2 is generated by multiplying the pixel value of each pixel by a weighting coefficient α2, making the pixel positions of the two correspond, and adding them.
Qn2=Do2×α2+Dn2×(1−α2) …Formula (3)
(However, Qn2: second composite image data, Dn2: first coarse structure image data Dn2, Do2: second coarse structure image data Do2, α2: weighting coefficient)

However, in the synthesis processing unit 4a, the weight of the first coarse structure image data Dn2 at the second ratio (that is, the weight for the rough tissue structure of the new frame data Dn) is equal to the weight of the first fine structure image data Dn1 at the first ratio. (ie, the weight for the fine tissue structure of the new frame data Dn). That is, in equations (2) and (3), the weighting coefficient α1 is set larger than the weighting coefficient α2 (α1>α2). Note that the weighting coefficient α1 is set, for example, to a value greater than or equal to 0.6 and less than 1, and the weighting coefficient α2 is set, for example, to a value greater than 0 and less than or equal to 0.4.

Next, the composition processing unit 4a adds the first composite image data Qn1 and the second composite image data Qn2 with their pixel positions corresponding to each other, as shown in Equation (4) below, thereby creating an output frame. Generate data Qn.
Qn=Qn1+Qn2...Formula (4)
(However, Qn: output frame data, Qn1: first composite image data, Qn2: second composite image data)

Note that, when adding the first composite image data Qn1 and the second composite image data Qn2, the composition processing unit 4a may set the weight of one of them to be larger.

FIG. 3 is a flowchart showing the operation of the frame averaging processing section 4 according to this embodiment. The flowchart shown in FIG. 3 is, for example, a process that is repeatedly executed by the frame averaging processing unit 4 according to a computer program every time frame data of an ultrasound image is generated in the signal processing unit 3.

First, the frame averaging processing section 4 obtains new frame data Dn from the signal processing section 3 (step S1). Next, the frame averaging processing unit 4 generates first coarse structure image data Dn2 and first fine structure image data Dn1 from the new frame data Dn (step S2). Next, the frame averaging processing unit 4 generates second fine structure image data Do1 and second coarse structure image data Do2 from the old frame data Do (step S3). Next, the frame averaging processing unit 4 performs weighted addition of the first fine structure image data Dn1 and the second fine structure image data Do1 to generate first composite image data Qn1 (step S4). Next, the frame averaging processing unit 4 performs weighted addition of the first coarse structure image data Dn2 and the second coarse structure image data Do2 to generate second composite image data Qn2 (step S5). Next, the frame averaging processing unit 4 adds the first composite image data Qn1 and the second composite image data Qn2 to generate output frame data Qn (step S6).

The frame averaging processing unit 4 repeatedly executes the above processing every time the signal processing unit 3 generates an ultrasound image, and sequentially generates output frame data Qn to be displayed on the display 6.

[effect]
As described above, in the frame averaging processing unit 4 of the ultrasound diagnostic apparatus A according to the present embodiment, tissue structure information with a low spatial frequency (i.e., approximate tissue structure information) and tissue structure information with a high spatial frequency ( That is, the old frame data Do and the new frame data Dn are weighted so that different weighting is performed for each spatial frequency band of the tissue structure reflected in the ultrasound image. to add. At this time, the weight of the new frame data Dn set for the tissue structure with a low spatial frequency is set so that it is larger than the weight of the new frame data Dn set for the tissue structure with a high spatial frequency. Ru.

As a result, when displaying and outputting an ultrasound image, it is possible to improve the followability of the movement of each tissue while also suppressing noise superimposed on the tissue.

In particular, the frame averaging processing unit 4 of the ultrasound diagnostic apparatus A according to the present embodiment converts the ultrasound image into rough tissue structure information (i.e., first coarse structure image data Dn2, second coarse structure image data Do2). The process of separating the microstructure information into the microstructure information (ie, the first microstructure image data Dn1 and the second microstructure image data Do1) is realized only by smoothing processing and subtraction processing. Therefore, the ultrasonic diagnostic apparatus A according to this embodiment is also useful in that high-speed calculation and low-load calculation are possible.

(Second embodiment)
FIG. 4 is a diagram showing the configuration of the frame averaging processing section 4 of the ultrasound diagnostic apparatus A according to the second embodiment.

The frame averaging processing unit 4 (separation processing unit 4c) according to the present embodiment realizes the process of separating an ultrasound image into rough tissue structure information and fine tissue structure information using multi-resolution decomposition processing. This is different from the frame averaging processing section 4 according to the first embodiment. Note that descriptions of configurations common to the first embodiment will be omitted (hereinafter, the same applies to other embodiments).

The multi-resolution decomposition process is a process of forming a plurality of resolution images with stepwise resolution reductions from an input image, and in this embodiment, wavelet decomposition is used as an example of the multi-resolution decomposition process. Multi-resolution decomposition processing is more suitable than the separation method of the first embodiment in that it enables more detailed processing by separating spatial frequency elementary components included in an ultrasound image into multiple layers. Note that the wavelet decomposition process itself is similar to a known method (for example, see Japanese Patent Application Laid-Open No. 2015-203952).

However, the multi-resolution decomposition process may be realized by the Laplacian pyramid method, downsampling process, etc. instead of wavelet decomposition.

The separation processing unit 4c according to the present embodiment performs multi-resolution decomposition processing on the new frame data Dn to generate image data of a plurality of resolutions in which the resolution is lowered in stages. Furthermore, the separation processing unit 4c generates image data of a plurality of resolutions in which the resolution is lowered stepwise by performing multi-resolution decomposition processing on the old frame data Do. Then, the synthesis processing unit 4a synthesizes the image data of a plurality of resolutions generated from the new frame data Dn and the image data of a plurality of resolutions generated from the old frame data Do, and also combines them for each resolution. It is reconfigured to generate output frame data Qn.

In this embodiment, the image data of a plurality of resolutions generated from the new frame data Dn corresponds to the "first coarse structure image data" and "first fine structure image data" of the present invention, and the image data of the old frame The image data of a plurality of resolutions generated from the data Do corresponds to "second coarse structure image data" and "second fine structure image data" of the present invention.

Specifically, the separation processing unit 4c performs wavelet decomposition on the new frame data Dn to obtain first-order low frequency component image data LL having low frequencies in the horizontal and vertical directions as spatial low frequency band components. (1), first-order high-frequency component image data LH(1) of horizontal direction low frequency and vertical direction high frequency, first-order high frequency component image data HL(1) of horizontal direction high frequency and vertical direction low frequency, horizontal direction and First-order high-frequency component image data HH(1) of high frequency in the vertical direction is generated (hereinafter referred to as "image data Dn3 generated by first-order spatial wavelet decomposition of new frame data Dn").

Subsequently, the separation processing unit 4c performs further wavelet decomposition on the image data LL(1) of the first-order low-frequency component, and generates image data of the second-order low-frequency component with low frequencies in the horizontal and vertical directions. LL(2), image data LH(2) of second order high frequency components of horizontal direction low frequency and vertical direction high frequency, image data HL(2) of second order high frequency components of horizontal direction high frequency and vertical direction low frequency, horizontal direction and Image data HH(2) of a second order high frequency component of a high frequency in the vertical direction is generated (hereinafter referred to as "image data Dn4 generated by second order spatial wavelet decomposition of the new frame data Dn").

Furthermore, the separation processing unit 4c performs further wavelet decomposition on the image data LL(2) of the second-order low-frequency component, and generates image data LL(2) of the third-order low-frequency component with low frequencies in the horizontal and vertical directions. 3), image data LH(3) of the third-order high frequency component of the horizontal low frequency and vertical high frequency, image data HL(3) of the third-order high frequency component of the horizontal high frequency and the vertical low frequency, and the horizontal Image data HH(3) of a third-order high-frequency component of high frequency in the direction and the vertical direction is generated (hereinafter referred to as "image data Dn5 generated by third-order spatial wavelet decomposition of the new frame data Dn").

Similarly, the separation processing unit 4c performs wavelet decomposition on the old frame data Do, and generates the image data LL( 1), Image data LH (1) of the first-order high-frequency component of the horizontal low frequency and vertical high frequency, Image data HL (1) of the first-order high frequency component of the horizontal high frequency and vertical low frequency, horizontal and vertical directions Image data HH(1) of the first-order high-frequency component of the high frequency is generated (hereinafter referred to as "image data Do3 generated by first-order spatial wavelet decomposition of the old frame data Do").

Subsequently, the separation processing unit 4c performs further wavelet decomposition on the image data LL(1) of the first-order low-frequency component, and generates image data of the second-order low-frequency component with low frequencies in the horizontal and vertical directions. LL(2), image data LH(2) of the second order high frequency component of the horizontal direction low frequency and vertical direction high frequency, image data HL(2) of the second order high frequency component of the horizontal direction high frequency and the vertical direction low frequency, the horizontal direction and Image data HH(2) of a second order high frequency component of a high frequency in the vertical direction is generated (hereinafter referred to as "image data Do4 generated by second order spatial wavelet decomposition of the old frame data Do").

Furthermore, the separation processing unit 4c performs further wavelet decomposition on the image data LL(2) of the second-order low-frequency component, and generates image data LL(2) of the third-order low-frequency component with low frequencies in the horizontal and vertical directions. 3), image data LH(3) of the third-order high frequency component of the horizontal low frequency and vertical high frequency, image data HL(3) of the third-order high frequency component of the horizontal high frequency and the vertical low frequency, and the horizontal Image data HH(3) of a third-order high-frequency component of high frequency in the direction and the vertical direction is generated (hereinafter referred to as "image data Do5 generated by third-order spatial wavelet decomposition of the old frame data Do").

Note that in multi-resolution decomposition processing using wavelet decomposition, the spatial frequency of image data decreases each time wavelet decomposition of image data is performed.

The synthesis processing unit 4a weights and adds the old frame data Do and the new frame data Dn for each layer as shown in the following equations (5), (6), and (7). At this time, the synthesis processing unit 4a generates horizontally and vertically low-frequency image data, horizontally low-frequency and vertically high-frequency image data, horizontally high-frequency and vertically low-frequency image data, and horizontally low-frequency and vertically high-frequency image data. The addition process is performed by associating pixel positions with each image data of high-frequency image data in the direction and the vertical direction.
Qn3=Do3×α3+Dn3×(1−α3)…Formula (5)
(However, Qn3: 1st layer composite image data, Do3: Image data generated by 1st order spatial wavelet decomposition of old frame data Do, Dn3: Image data generated by 1st order spatial wavelet decomposition of new frame data Dn) , α3: weighting coefficient)
Qn4=Do4×α4+Dn4×(1−α4) …Formula (6)
(However, Qn4: second-layer composite image data, Do4: image data generated by second-order spatial wavelet decomposition of old frame data Do, Dn4: image data generated by second-order spatial wavelet decomposition of new frame data Dn) , α4: weighting coefficient)
Qn5=Do5×α5+Dn5×(1−α5) …Formula (7)
(However, Qn5: 3rd layer composite image data, Do5: Image data generated by 3rd order spatial wavelet decomposition of old frame data Do, Dn5: Image data generated by 3rd order spatial wavelet decomposition of new frame data Dn) , α5: weighting coefficient)

However, here, weighting coefficients α3, α4, α5 are set so that the new frame data Dn has a larger weight for rough tissue structure information, and the old frame data Do has a larger weight for fine tissue structure information. are set so that weighting coefficient α3>weighting coefficient α4>weighting coefficient α5.

The synthesis processing unit 4a then performs spatial wavelet reconstruction (i.e., inverse wavelet decomposition) on the synthesized image data Qn3, Qn4, and Qn5 generated using equations (5), (6), and (7). As a result, output frame data Qn is generated.

As described above, in the ultrasound diagnostic apparatus A according to the present embodiment, when displaying and outputting an ultrasound image, noise superimposed on the tissue is suppressed while improving tracking of the movement of each tissue. It is possible to do so.

In particular, in the frame averaging processing unit 4 of the ultrasound diagnostic apparatus A according to the present embodiment, the process of separating an ultrasound image into rough tissue structure information and fine tissue structure information is realized by multi-resolution decomposition processing. are doing. Therefore, in the ultrasound diagnostic apparatus A according to the present embodiment, more detailed processing can be performed for each frequency band included in an ultrasound image, and further flicker suppression and tracking performance can be achieved.

(Third embodiment)
FIG. 5 is a diagram showing the configuration of the frame averaging processing section 4 of the ultrasonic diagnostic apparatus A according to the third embodiment.

The frame averaging processing section 4 according to the present embodiment uses an ultrasound image (hereinafter referred to as "narrowband image data") generated using a narrowband filter in the signal processing section 3 and a wideband An ultrasound image generated using a filter (hereinafter referred to as "broadband image data") is acquired, and using these narrowband image data and wideband image data, the approximate tissue contained in the ultrasound image is determined. This differs from the frame averaging processing unit 4 according to the first embodiment in that structural information and fine tissue structure information are grasped separately.

In other words, when the frame averaging processing unit 4 according to the present embodiment performs image synthesis of the new frame data Dn and the old frame data Do, as in the first embodiment, the frame averaging processing unit 4 calculates the high frequency of the tissue structure reflected in the ultrasound image, as in the first embodiment. Narrowband image data and wideband image data are used instead of using coarse structure image data whose components have been cut and fine structure image data including high frequency components of the tissue structure seen in the ultrasound image.

The signal processing unit 3 according to the present embodiment subjects the received signal output from the receiver 2b to filter processing using a narrowband filter (for example, an FIR bandpass filter) to obtain narrowband image data. a signal processing unit that generates broadband image data; and a signal processing unit that subjects the received signal output from the receiver 2b to filter processing using a wideband filter (for example, an FIR type bandpass filter) to generate wideband image data. , are arranged in parallel (not shown). Note that the filter processing of the signal processing unit 3 is generally executed for each scanning line during ultrasonic scanning.

The frame averaging processing section 4 according to this embodiment includes a composition processing section 4a and an acquisition section 4d.

The acquisition unit 4d extracts narrowband image data (hereinafter referred to as “first narrowband image data”) Dn7 output from the signal processing unit 3 as new frame data Dn and wideband image data (hereinafter referred to as “first wideband image data”). Dn6 (referred to as "data") is obtained.

The acquisition unit 4d also acquires from the frame memory 5 the first composite image data Qn6 and the second composite image data Qn7 that were generated when calculating the output frame data Qn one time ago. Here, the first composite image data Qn6 generated when calculating the output frame data Qn one time ago is converted into the wideband image data Do6 of the old frame data Do (hereinafter referred to as "second wideband image data"). Correspondingly, the second composite image data Qn7 generated when calculating the output frame data one time ago is the narrowband image data (hereinafter referred to as "second narrowband image data") Do7 of the old frame data Do. corresponds to

Note that the frame memory 5 according to the present embodiment is configured such that in addition to the frame data to be displayed and output at the next time generated by the frame averaging processing section 4, the frame averaging processing section 4 calculates the frame data. It is configured to store the first composite image data Qn6 and second composite image data Qn7 generated at the time.

FIG. 6 is a diagram showing a frequency band f1 in an ultrasound image extracted by a wideband filter and a frequency band f2 in an ultrasound image extracted by a narrowband filter in the signal processing unit 3 according to the present embodiment.

Generally, the frequency band included in the received signal sent out from the receiver 2b has a certain degree of spread from the center frequency of the transmitted ultrasonic wave to a low frequency side and a high frequency side. This frequency band varies depending on measurement conditions such as the frequency of the transmitted ultrasound, the type of ultrasound probe 1, and the depth of the detection target region within the subject. When a wideband signal with a center frequency of 10 MHz is used as the transmitted ultrasound, the frequency band included in the received signal is, for example, from 4 MHz to 18 MHz. The reason why the frequency band included in the received signal is broader than the frequency band of the transmitted ultrasound is mainly because when ultrasound propagates inside a living body that has nonlinear characteristics, distortion occurs in the waveform. .

Here, in the signal processing unit 3, the frequency band to be extracted by the wideband filter and the frequency band to be extracted by the narrowband filter are determined based on the center frequency of the transmitted ultrasound, respectively. The frequency band is set to be narrower than the frequency band to be extracted by the wideband filter. For example, when a wideband signal with a center frequency of 10 MHz is used as the transmitted ultrasound, the wideband filter can extract a frequency band with an upper limit of 18 MHz and a lower limit of 4 MHz from the received signal sent from the receiver 2b. The narrow band filter is configured to be able to extract a frequency band having an upper limit of 12 MHz and a lower limit of 7 MHz from the received signal sent from the receiver 2b.

In other words, among the frequency bands included in the received signal sent from the receiver 2b, the narrow band filter only applies to the tissue structure in the frequency band near the center frequency of the transmitted ultrasound, which is suitable for extracting the outline of each tissue. It is configured to extract high frequency bands that may appear as noise after imaging. On the other hand, the wideband filter is configured to extract the entire frequency band included in the received signal sent from the receiver 2b so that even minute tissue structures can be expressed in the ultrasonic image.

The configuration of the combination processing section 4a according to this embodiment is similar to the configuration of the combination processing section 4a according to the first embodiment.

Specifically, the synthesis processing unit 4a multiplies the pixel value of each pixel of the first wideband image data Dn6 by a weighting coefficient (1-α6) as shown in equation (8) below, and also multiplies the pixel value of each pixel of the first wideband image data Dn6, and The first composite image data Qn6 is generated by multiplying the pixel value of each pixel in Do6 by a weighting coefficient α6, making the pixel positions of both correspond, and adding them.
Qn6=Do6×α6+Dn6×(1−α6) …Formula (8)
(However, Qn1: first composite image data, Dn6: first wideband image data, Do6: second wideband image data, α6: weighting coefficient)

In addition, the synthesis processing unit 4a multiplies the pixel value of each pixel of the first narrowband image data Dn7 by a weighting coefficient (1-α7), as shown in the following equation (9), and also multiplies the pixel value of each pixel of the first narrowband image data Dn7, and The second composite image data Qn2 is generated by multiplying the pixel value of each pixel by a weighting coefficient α7, making the pixel positions of the two correspond, and adding them.
Qn7=Do7×α7+Dn7×(1-α7) …Formula (9)
(However, Qn7: second composite image data, Dn7: first narrowband image data, Do7: second narrowband image data, α7: weighting coefficient)

However, in equations (8) and (9), the weighting coefficient α6 is larger than the weighting coefficient α7 (α6>α7).

Next, the composition processing unit 4a adds the first composite image data Qn6 and the second composite image data Qn7 with their pixel positions corresponding to each other, as shown in Equation (10) below, thereby creating an output frame. Generate data Qn.
Qn=Qn6+Qn7...Formula (10)
(However, Qn: output frame data, Qn6: first composite image data, Qn7: second composite image data)

As described above, in the ultrasound diagnostic apparatus A according to the present embodiment, when displaying and outputting an ultrasound image, noise superimposed on the tissue is suppressed while improving tracking of the movement of each tissue. It is possible to do so.

In particular, in the frame averaging processing unit 4 of the ultrasound diagnostic apparatus A according to the present embodiment, the general structure within the subject is determined using frame data generated by the signal processing unit 3 using a narrowband filter and a wideband filter. It is configured to grasp structural information and fine tissue structure information. In this way, by separating the frequency components before imaging, the narrowband image becomes an image with less noise and a high S/N ratio. At the time of image synthesis, output frame data is generated so as to mainly reflect this narrowband image, so it is possible to provide an image with less flickering and high followability.

(Fourth embodiment)
FIG. 7 is a diagram showing the configuration of the frame averaging processing section 4 of the ultrasound diagnostic apparatus A according to the fourth embodiment.

The frame averaging processing unit 4 according to the present embodiment is similar to the frame averaging processing according to the third embodiment in terms of a processing method for separating an ultrasound image into rough tissue structure information and fine tissue structure information. It is different from part 4.

The frame averaging processing section 4 according to this embodiment includes a composition processing section 4a, an acquisition section 4d, and a separation processing section 4e.

Similar to the third embodiment, the acquisition unit 4d according to the present embodiment acquires the first narrowband image data Dn7 and the first wideband image data Dn6, which are output as new frame data Dn from the signal processing unit 3. At the same time, second narrowband image data Do7 and second wideband image data Do6 are acquired from the frame memory 5.

Further, the separation processing unit 4e according to the present embodiment generates the first difference image data Dn8 by subtracting the first narrowband image data Dn7 from the first wideband image data Dn6, and also generates the second wideband image data Do6. The second difference image data Do8 is generated by subtracting the second narrowband image data Do7 from the second narrowband image data Do7. That is, in this embodiment, the first narrowband image data Dn7 and the second narrowband image data Do7 are used as image data from which rough tissue structure information is selectively extracted, and the first difference image data Dn8 and the second narrowband image data Do7 are used as image data from which rough tissue structure information is selectively extracted. The 2-difference image data Do8 is used as image data from which minute tissue structure information has been selectively extracted.

The composition of the composition processing section 4a according to this embodiment is similar to the composition of the composition processing section 4a according to the first embodiment.

Specifically, the synthesis processing unit 4a multiplies the pixel value of each pixel of the first difference image data Dn8 by a weighting coefficient (1-α8) as shown in the following equation (11), and also multiplies the pixel value of each pixel of the first difference image data Dn8, and First composite image data Qn8 is generated by multiplying the pixel value of each pixel in Do8 by a weighting coefficient α8, making the pixel positions of both correspond, and adding them.
Qn8=Do8×α8+Dn8×(1−α8) …Formula (11)
(However, Qn8: first composite image data, Dn8: first difference image data, Do8: second difference image data, α8: weighting coefficient)

Further, the synthesis processing unit 4a multiplies the pixel value of each pixel of the first narrowband image data Dn7 by a weighting coefficient (1-α9) as shown in the following equation (12), and also multiplies the pixel value of each pixel of the first narrowband image data Dn7, and The second composite image data Qn9 is generated by multiplying the pixel value of each pixel by a weighting coefficient α9, making the pixel positions of the two correspond, and adding them.
Qn9=Do7×α9+Dn7×(1-α9) …Formula (12)
(However, Qn9: second composite image data, Dn7: first narrowband image data, Do7: second narrowband image data, α9: weighting coefficient)

However, in equations (11) and (12), the weighting coefficient α8 is larger than the weighting coefficient α9 (α8>α9).

Next, the composition processing unit 4a adds the first composite image data Qn8 and the second composite image data Qn9 with their pixel positions corresponding to each other, as shown in Equation (13) below, thereby creating an output frame. Generate data Qn.
Qn=Qn8+Qn9...Formula (13)
(However, Qn: output frame data, Qn8: first composite image data, Qn9: second composite image data)

As described above, in the ultrasound diagnostic apparatus A according to the present embodiment, when displaying and outputting an ultrasound image, noise superimposed on the tissue is suppressed while improving tracking of the movement of each tissue. It is possible to do so.

In particular, in the frame averaging processing unit 4 of the ultrasound diagnostic apparatus A according to the present embodiment, the first narrowband image data Dn7 and the second narrowband image data Do7, which selectively extract rough tissue structure information, and the fine Output frame data Qn is generated by image-compositing the first difference image data Dn8 and the second difference image data Do8 from which tissue structure information is selectively extracted. As a result, it is possible to generate an image in which the outline of the tissue structure extracted by the narrow band filter is particularly emphasized while maintaining the ability to follow a moving tissue structure. This makes it possible to further reduce flickering compared to the aspect of the third embodiment.

(Fifth embodiment)
FIG. 8 is a diagram showing the configuration of an ultrasound diagnostic apparatus A according to the fifth embodiment.

The frame averaging processing unit 4 according to the present embodiment uses frame data related to an ultrasound image generated in the signal processing unit 3 one time ago and the current frame data as target frame data when performing frame averaging processing. This embodiment differs from the first embodiment in that frame data related to an ultrasound image generated by the signal processing unit 3 at the time is used.

For convenience of explanation, in this embodiment, the frame data related to the ultrasound image generated by the signal processing unit 3 one time ago is referred to as "old frame data Do", and the frame data related to the ultrasound image generated by the signal processing unit 3 at the current time is referred to as "old frame data Do". The frame data related to the ultrasonic image thus obtained is referred to as "new frame data Dn."

The ultrasonic diagnostic apparatus A according to this embodiment includes a second frame memory 7 that temporarily stores frame data generated by the signal processing section 3. Then, each time frame data is newly generated by the signal processing section 3, the second frame memory 7 stores the frame data. In other words, the signal processing section 3 outputs frame data to the frame averaging processing section 4 and the second frame memory 7 every time it generates frame data.

When the frame averaging processing section 4 according to the present embodiment acquires the new frame data Dn from the signal processing section 3, the frame averaging processing section 4 acquires the old frame data generated in the signal processing section 3 one time before from the second frame memory 7. Get Do. Then, the frame averaging processing unit 4 performs weighted addition of the new frame data Dn and the old frame data Do to generate output frame data to be displayed and output, and outputs it to the frame memory 5.

The method of weighted addition of the new frame data Dn and the old frame data Do in the frame averaging processing unit 4 according to this embodiment is the same as in the first to fourth embodiments. For example, the frame averaging processing unit 4 generates first fine structure image data Dn1 and first coarse structure image data Dn2 based on the new frame data Dn, and generates second fine structure image data Dn1 and first coarse structure image data Dn2 based on the old frame data Do. Image data Do1 and second rough structure image data Do2 are generated. Then, the frame averaging processing unit 4 generates the first composite image data Qn1 by weighted addition of the first fine structure image data Dn1 and the second fine structure image data Do1, for example, as in the above equation (2). At the same time, the second composite image data Qn2 is generated by weighted addition of the first coarse structure image data Dn2 and the second coarse structure image data Do2, as shown in equation (3) above. Then, the composition processing unit 4a generates the output frame data Qn by adding the first composite image data Qn1 and the second composite image data Qn2, for example, as in the above equation (4).

As described above, in the ultrasound diagnostic apparatus A according to the present embodiment, when displaying and outputting an ultrasound image, noise superimposed on the tissue is suppressed while improving tracking of the movement of each tissue. It is possible to do so. However, in the averaging processing method according to the present embodiment, frame data different from the frame data displayed and output one time ago is used, so in terms of noise suppression, the first to fourth embodiments It is more preferable to use a method of averaging processing based on the morphology. This is because in the averaging processing methods according to the first to fourth embodiments, the old frame data includes information for a longer period of time.

(Other embodiments)
The present invention is not limited to the above-described embodiments, and various modifications are possible.

In the above embodiment, as an example of the frame averaging processing unit 4, frame data Do that was displayed and output one time ago (or generated by the signal processing unit 3) and frame data Do that was generated by the signal processing unit 3 at the current time are used. A mode has been shown in which only frame data Dn is weighted and added to generate output frame data Qn. However, in the present invention, in addition to the above frame data, the frame averaging processing unit 4 also displays frames that were output two times ago (i.e., two frames ago) or three times ago (i.e., three frames ago). The output frame data Qn may be generated by referring to the data and performing weighted addition.

Further, in the above embodiment, as an example of the frame averaging processing section 4, when performing weighted addition of the frame data Do that was displayed and output one time ago and the frame data Dn that was generated by the signal processing section 3 at the current time. A configuration is shown in which the weighting coefficient of is set to a specified value at all pixel positions. However, the method for setting such weighting coefficients can be modified in various ways. For example, the pixel value of the frame data Do that was displayed and output one time ago and the pixel value of the frame data Dn that was generated by the signal processing unit 3 at the current time are compared pixel by pixel, and the difference between the pixel values is calculated. The weighting factor may be dynamically changed based on the . Further, the setting of the weighting coefficient may be changed based on the frame rate at which the signal processing unit 3 generates frame data related to an ultrasound image.

Although specific examples of the present invention have been described in detail above, these are merely illustrative and do not limit the scope of the claims. The techniques described in the claims include various modifications and changes to the specific examples illustrated above.

According to the ultrasonic diagnostic apparatus according to the present disclosure, when displaying and outputting an ultrasonic image, it is possible to effectively remove noise and improve followability for a moving tissue structure.

A Ultrasonic diagnostic device 1 Ultrasonic probe 2 Transmission/reception unit 2a Transmitter 2b Receiver 3 Signal processing unit 4 Frame averaging processing unit 4a Combination processing unit 4b, 4c, 4e Separation processing unit 4d Acquisition unit 5 Frame memory 6 Display unit 7 2nd frame memory Dn New frame data (first frame data)
Do Old frame data (second frame data)
Qn output frame data

Claims (8)

a transmitter/receiver unit that receives a reception signal related to an ultrasound echo from the ultrasound probe;
a signal processing unit that generates frame data constituting an ultrasound image based on the received signal;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. a frame averaging processing unit;
An ultrasonic diagnostic device comprising:
The frame averaging processing unit includes:
an acquisition unit that acquires narrowband image data generated using a narrowband filter and wideband image data generated using a wideband filter from the signal processing unit;
The broadband image data of the first frame data and the broadband image data of the second frame data are weighted and added at a first ratio to generate first composite image data, and The narrowband image data of one frame data and the narrowband image data of the second frame data are weighted and added to generate second composite image data, and the first composite image data and the second composite image a synthesis processing unit that generates the output frame data based on the data;
has
The weight of the first frame data in the second ratio is greater than the weight of the first frame data in the first ratio.
Ultrasound diagnostic equipment. a transmitter/receiver unit that receives a reception signal related to an ultrasound echo from the ultrasound probe;
a signal processing unit that generates frame data constituting an ultrasound image based on the received signal;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. a frame averaging processing unit;
An ultrasonic diagnostic device comprising:
The frame averaging processing unit includes:
an acquisition unit that acquires narrowband image data generated using a narrowband filter and wideband image data generated using a wideband filter from the signal processing unit;
a separation processing unit that generates difference image data by subtracting the narrowband image data from the wideband image data;
At a first ratio, the difference image data of the first frame data and the difference image data of the second frame data are weighted and added to generate first composite image data, and at the same time, the The narrowband image data of one frame data and the narrowband image data of the second frame data are weighted and added to generate second composite image data, and the first composite image data and the second composite image a synthesis processing unit that generates the output frame data based on the data;
has
The weight of the first frame data in the second ratio is greater than the weight of the first frame data in the first ratio.
Ultrasound diagnostic equipment. The second frame data is output frame data generated by the frame averaging processing unit one time ago.
The ultrasonic diagnostic apparatus according to claim 1 or 2 . The second frame data is frame data generated by the signal processing unit one time ago.
The ultrasonic diagnostic apparatus according to claim 1 or 2 . to the computer,
a first process of receiving a reception signal related to an ultrasound echo from an ultrasound probe;
a second process of generating frame data constituting an ultrasound image based on the received signal in a signal processing unit ;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. Third processing;
A control program for an ultrasonic diagnostic device that executes the
The third process is
A process of acquiring narrowband image data generated using a narrowband filter and wideband image data generated using a wideband filter from the signal processing unit;
The broadband image data of the first frame data and the broadband image data of the second frame data are weighted and added at a first ratio to generate first composite image data, and The narrowband image data of one frame data and the narrowband image data of the second frame data are weighted and added to generate second composite image data, and the first composite image data and the second composite image a process of generating the output frame data based on the data;
has
The weight of the first frame data in the second ratio is greater than the weight of the first frame data in the first ratio.
Control program for ultrasonic diagnostic equipment. to the computer,
a first process of receiving a reception signal related to an ultrasound echo from an ultrasound probe;
a second process of generating frame data constituting an ultrasound image based on the received signal in a signal processing unit ;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. Third processing;
A control program for an ultrasonic diagnostic device that executes the
The third process is
A process of acquiring narrowband image data generated using a narrowband filter and wideband image data generated using a wideband filter from the signal processing unit;
a process of generating difference image data by subtracting the narrowband image data from the wideband image data;
At a first ratio, the difference image data of the first frame data and the difference image data of the second frame data are weighted and added to generate first composite image data, and at the same time, the The narrowband image data of one frame data and the narrowband image data of the second frame data are weighted and added to generate second composite image data, and the first composite image data and the second composite image a process of generating the output frame data based on the data;
has
The weight of the first frame data in the second ratio is greater than the weight of the first frame data in the first ratio.
Control program for ultrasonic diagnostic equipment. a first process of receiving a reception signal related to an ultrasound echo from an ultrasound probe;
a second process of generating frame data constituting an ultrasound image based on the received signal in a signal processing unit ;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. Third processing;
A method of controlling an ultrasonic diagnostic apparatus comprising:
The third process is
A process of acquiring narrowband image data generated using a narrowband filter and wideband image data generated using a wideband filter from the signal processing unit;
The broadband image data of the first frame data and the broadband image data of the second frame data are weighted and added at a first ratio to generate first composite image data, and The narrowband image data of one frame data and the narrowband image data of the second frame data are weighted and added to generate second composite image data, and the first composite image data and the second composite image a process of generating the output frame data based on the data;
has
The weight of the first frame data in the second ratio is greater than the weight of the first frame data in the first ratio.
A method of controlling an ultrasonic diagnostic device. a first process of receiving a reception signal related to an ultrasound echo from an ultrasound probe;
a second process of generating frame data constituting an ultrasound image based on the received signal in a signal processing unit ;
Output frame data is generated by weighted addition of first frame data generated by the signal processing unit and second frame data generated at a time earlier than the first frame data. Third processing;
A method of controlling an ultrasonic diagnostic apparatus comprising:
The third process is
A process of acquiring narrowband image data generated using a narrowband filter and wideband image data generated using a wideband filter from the signal processing unit;
a process of generating difference image data by subtracting the narrowband image data from the wideband image data;
At a first ratio, the difference image data of the first frame data and the difference image data of the second frame data are weighted and added to generate first composite image data, and at the same time, the The narrowband image data of one frame data and the narrowband image data of the second frame data are weighted and added to generate second composite image data, and the first composite image data and the second composite image a process of generating the output frame data based on the data;
has
The weight of the first frame data in the second ratio is greater than the weight of the first frame data in the first ratio.
A method of controlling an ultrasonic diagnostic device.