ULTRASONIC DIAGNOSTIC APPARATUS, CONTROL METHOD FOR ULTRASONIC DIAGNOSTIC APPARATUS, AND CONTROL PROGRAM FOR ULTRASONIC DIAGNOSTIC APPARATUS

Abstract

To provide an ultrasonic diagnostic device which can automatically set appropriate MTI filter characteristics.SOLUTION: An ultrasonic diagnostic device comprises: a main component analysis execution unit which executes main component analysis to a time-series reflection wave data group to calculate a plurality of characteristic vectors; a frequency analysis unit which calculates a primary frequency component in the time direction expressed by each of the plurality of characteristic vectors; a reduction rate determination unit which determines the reduction rate of each of the plurality of characteristic vectors on the basis of the primary frequency component of each of the plurality of characteristic vectors and a clutter component reduction condition defining a reference frequency for reducing a clutter component; a filter coefficient calculation unit which calculates a filter coefficient for reducing the clutter component on the basis of the plurality of characteristic vectors and the reduction rate corresponding to each of the plurality of characteristic vectors; and an image generation unit which generates blood flow image data by applying the filter coefficient to the time-series reflection wave data group.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present disclosure relates to an ultrasound diagnostic apparatus, a control method for an ultrasound diagnostic apparatus, and a control program for an ultrasound diagnostic apparatus. [Background technology]

[0002] Ultrasound diagnosis can obtain ultrasound images of the heartbeat and fetal movement through a simple operation of placing an ultrasound probe on the body surface, and is highly safe, so the examination can be performed repeatedly. Ultrasound diagnostic devices that are used for ultrasound diagnosis and generate and display ultrasound images are known. In addition, ultrasound diagnostic devices that transmit and receive ultrasound to a subject and generate and display C (color flow (color Doppler)) mode images that display the subject's blood flow in color using the Doppler method are also known.

[0003] Fig. 22 is a diagram showing the frequency characteristics of power of a conventional MTI (Moving Target Indication) filter. In generating C-mode image data, the frequency characteristics of the power of a Doppler signal corresponding to a received signal based on an ultrasonic wave reflected by a subject are taken. As shown in Fig. 22, the Doppler signal contains a clutter component 201, a blood flow component 202, and a noise component 203. The clutter component 201 is a signal component of the movement of the subject's tissue. The blood flow component 202 is a signal component of the blood flow of the subject. The noise component 203 is a signal component of system noise (random noise) specific to the device.

[0004] Generally, in order to visualize blood flow components in a C-mode image, clutter components 201 from the Doppler signal are removed by an MTI filter 204. The MTI filter 204 is a high-pass filter that removes the clutter components and extracts only the Doppler shift components.

[0005] Known examples of this type of MTI filter include an FIR filter that uses the difference in average velocity between blood flow components and clutter components, and an adaptive MTI filter that changes its coefficients according to the input signal. An adaptive MTI filter obtains the tissue velocity from the signal before it is input to the MTI filter, and obtains a signal in which the phase difference has been cancelled.

[0006] In particular, as this type of adaptive MTI filter, an eigenvector-type MTI filter has attracted attention, which performs principal component analysis using a correlation matrix from the Doppler signal before input to the MTI filter, and distinguishes between blood flow components and clutter components based on the principal components (eigenvectors) of each order, thereby obtaining a blood flow image from which clutter has been removed (see, for example, Patent Document 1). Note that the eigenvector-type MTI filter is more useful than an FIR filter, etc., in that it can remove clutter components even when the frequency bands of the blood flow components and the clutter components overlap. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] JP 2014-158698 A Summary of the Invention [Problem to be solved by the invention]

[0008] Conventionally, in an ultrasonic diagnostic device using this type of eigenvector-type MTI filter, a method has been adopted in which an appropriate rank cut order (eigenvector to be reduced) is determined based on the eigenvalues ​​of the eigenvectors (i.e., principal components) of each order obtained by principal component analysis, and a blood flow image from which clutter components have been removed is obtained.

[0009] Fig. 1 is a diagram for explaining the processing of an eigenvector-type MTI filter according to the conventional technology. Fig. 1 shows, from the upper left to the lower right, a blood flow image in which only the eigenvector of the 0th-order component has been reduced, a blood flow image in which the eigenvectors of the 0th-order to 1st-order components have been reduced, a blood flow image in which the eigenvectors of the 0th-order to 2nd-order components have been reduced, and so on, a blood flow image in which the eigenvectors of the 0th-order to nth-order components (0th-13th-order components in Fig. 1) have been reduced.

[0010] The orders of the eigenvectors calculated by the principal component analysis are set in descending order according to the magnitude of the eigenvalue. Since the signal strength (i.e., eigenvalue) of a clutter signal is usually greater than that of a blood flow signal, the orders are assigned to the eigenvectors such that the eigenvectors on the low order side are eigenvectors related to the clutter signal and the eigenvectors on the high order side are eigenvectors related to the blood flow component.

[0011] In the conventional technology, for example, an eigenvector (i.e., principal component) of an order whose eigenvalue is equal to or greater than a threshold is regarded as a clutter component, and a rank cut order is determined (for example, FIG. 1 shows an example in which the fourth-order component is determined as the rank cut order).

[0012] Such a conventional technique is useful in that it can obtain a blood flow image from which clutter components have been removed by simple calculation processing. However, the eigenvalue merely indicates the degree of information held by the principal component, and the distribution of the eigenvalues ​​of the eigenvectors of the 0th to nth order components is greatly influenced by the strength of blood flow signals and the strength of tissue movement in the region of interest (ROI) of the imaging target of the C-mode image. For example, the distribution of the eigenvalues ​​of the eigenvectors of the 0th to nth order components differs between an area where there are many blood flow signals (e.g., the carotid artery) and an area where there are few blood flow signals (e.g., the thyroid gland) (see FIG. 11 described later). Therefore, it is difficult to set an appropriate threshold value for the eigenvalues ​​to distinguish between blood flow components and clutter components.

[0013] In addition, although most of the clutter components are concentrated in eigenvectors of orders with large eigenvalues, some of the clutter components are also included in the high-order eigenvectors representing the blood flow components. In the high-order eigenvectors representing the blood flow components, the change in eigenvalue between the orders is small, so it is difficult to determine the order of the boundary between the eigenvectors of orders that contain a large amount of clutter components and the eigenvectors of orders that contain a large amount of blood flow components.

[0014] In view of this, in an ultrasonic diagnostic apparatus using an eigenvector type MTI filter, it is actually necessary for the user to search for an appropriate rank cut order while checking the ultrasonic image.

[0015] The present disclosure has been made in consideration of the above problems, and aims to provide an ultrasound diagnostic device, a control method for an ultrasound diagnostic device, and a control program for an ultrasound diagnostic device, which enable automatic setting of appropriate MTI filter characteristics. [Means for solving the problem]

[0016] The present disclosure, which solves the above-mentioned problems, is 1. An ultrasound diagnostic apparatus for generating a blood flow image within a subject by transmitting ultrasound into the subject and receiving reflected waves thereof, comprising: a principal component analysis execution unit that executes a principal component analysis on a time series reflected wave data group in a predetermined region in the subject obtained during execution of a color flow mode, and calculates a plurality of eigenvectors; a frequency analysis unit that calculates a main frequency component in a time direction represented by each of the plurality of eigenvectors by performing frequency analysis on each of the plurality of eigenvectors; a reduction rate determination unit that determines a reduction rate of each of the plurality of eigenvectors based on the main frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reducing the clutter component; a filter coefficient calculation unit that calculates a filter coefficient for reducing clutter components based on a plurality of the eigenvectors and the reduction rate corresponding to each of the plurality of the eigenvectors; an image generating unit that applies the filter coefficients to the time-series reflected wave data group to generate blood flow image data; The ultrasonic diagnostic device is provided with:

[0017] In other respects, 1. A method for controlling an ultrasound diagnostic apparatus that generates a blood flow image within a subject by transmitting ultrasound waves into the subject and receiving reflected waves, comprising the steps of: a first process of calculating a plurality of eigenvectors by performing a principal component analysis on a time series of reflected wave data in a predetermined region of the subject obtained during execution of a color flow mode; a second process of calculating a main frequency component in a time direction represented by each of the plurality of eigenvectors by analyzing each of the plurality of eigenvectors; a third process of determining a reduction rate of each of the plurality of eigenvectors based on the principal frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reducing the clutter component; a fourth process of calculating a filter coefficient for reducing clutter components based on a plurality of the eigenvectors and the reduction rate corresponding to each of the plurality of the eigenvectors; A fifth process of applying the filter coefficients to the time-series reflected wave data group to generate blood flow image data; The control method has the following features.

[0018] In other respects, 1. A control program for an ultrasound diagnostic apparatus for generating a blood flow image in a subject by transmitting ultrasound into the subject and receiving the reflected waves, comprising: a first process of calculating a plurality of eigenvectors by performing a principal component analysis on a time series of reflected wave data in a predetermined region of the subject obtained during execution of a color flow mode; a second process of calculating a main frequency component in a time direction represented by each of the plurality of eigenvectors by analyzing each of the plurality of eigenvectors; a third process of determining a reduction rate of each of the plurality of eigenvectors based on the principal frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reducing the clutter component; a fourth process of calculating a filter coefficient for reducing clutter components based on a plurality of the eigenvectors and the reduction rate corresponding to each of the plurality of the eigenvectors; A fifth process of applying the filter coefficients to the time-series reflected wave data group to generate blood flow image data; It is a control program having the following functions. Effect of the Invention

[0019] According to the ultrasound diagnostic device according to the present disclosure, it is possible to automatically set appropriate MTI filter characteristics. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is a diagram for explaining the processing of an eigenvector type MTI filter according to the prior art; [Diagram 2] FIG. 1 is a schematic block diagram showing the configuration of an ultrasonic diagnostic apparatus according to a first embodiment; [Diagram 3] FIG. 1 is a block diagram showing a functional configuration of a C-mode image generating unit according to a first embodiment; [Figure 4] FIG. 1 is a diagram showing an internal configuration of an MTI filter according to a first embodiment; [Diagram 5] Diagram showing the relationship between the input and output of the MTI filter [Figure 6] A diagram showing how to calculate the MTI filter coefficients of the MTI filter [Figure 7] FIG. 1 is a diagram showing the data structure of packet data used to obtain one frame of a C-mode image. [Figure 8] FIG. 11 is a diagram showing a process of a reduction rate determination unit according to the first embodiment; [Figure 9A]FIG. 1 is a diagram showing a method for determining the rank cut order according to the prior art. [Figure 9B] FIG. 1 is a diagram showing a method for determining the rank cut order according to the present invention. [Figure 10A] Blood flow image generated when the rank cut order is determined using the rank cut order determination method according to the prior art (FIG. 9A). [Figure 10B] A blood flow image generated when the rank cut order is determined by the rank cut order determination method according to the present invention (FIG. 9B). [Figure 11] A diagram showing the distribution of eigenvalues ​​of eigenvectors of each order and the distribution of eigenvector frequencies obtained when a principal component analysis is performed by setting the region of interest (the target for acquiring packet data groups) to a more localized region. [Figure 12] FIG. 11 is a diagram for explaining the process of the reduction rate determination unit according to the second embodiment; [Figure 13] FIG. 13 is a diagram for explaining another method of processing by the reduction rate determination unit according to the second embodiment; [Figure 14] FIG. 13 is a diagram for explaining the process of the reduction rate determination unit according to the third embodiment; [Figure 15] FIG. 13 is a diagram for explaining another method of processing by the reduction rate determination unit according to the third embodiment; [Figure 16] FIG. 13 is a diagram for explaining the process of the reduction rate determination unit according to the fourth embodiment; [Figure 17] FIG. 13 is a diagram for explaining another method of processing by the reduction rate determination unit according to the fourth embodiment; [Figure 18] FIG. 13 is a diagram showing an internal configuration of an MTI filter according to a fifth embodiment. [Figure 19] FIG. 13 is a diagram for explaining the process of the reduction rate determination unit according to the fifth embodiment; [Figure 20] FIG. 13 is a diagram for explaining the operation flow of the ultrasound diagnostic apparatus according to the sixth embodiment. [Figure 21] FIG. 13 is a diagram for explaining the operation flow of the ultrasound diagnostic apparatus according to the sixth embodiment. [Figure 22] A diagram showing the power frequency characteristics of a conventional MTI (Moving Target Indication) filter. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functions are denoted by the same reference numerals, and redundant description will be omitted.

[0022] (First embodiment) First, the overall configuration of an ultrasonic diagnostic apparatus 1 according to one embodiment will be described with reference to FIGS.

[0023] Fig. 2 is a schematic block diagram showing the configuration of the ultrasonic diagnostic apparatus 1 according to this embodiment. Fig. 3 is a block diagram showing the functional configuration of the C-mode image generating unit 7 according to this embodiment.

[0024] The ultrasound diagnostic device 1 is installed in a medical institution such as a hospital, and generates ultrasound images of a subject such as a living patient, which is an object to be measured. The ultrasound diagnostic device 1 is configured by connecting an ultrasound probe 101 to an ultrasound diagnostic device main body 100.

[0025] The ultrasound diagnostic device main body 100 includes an operation unit 2, a transmission unit 3, a reception unit 4, a B (Brightness) mode image generation unit 5, a ROI (Region Of Interest) setting unit 6, a C-mode image generation unit 7, a display processing unit 8, a control unit 9, a memory unit 10, and a display unit 11.

[0026] The ultrasonic probe 101 has a plurality of transducers (piezoelectric conversion elements) 101a arranged in one dimension, and each of the transducers 101a converts a drive signal (transmission electrical signal) from a transmission unit 3 (described later) into ultrasonic waves to generate an ultrasonic beam. Therefore, a user can irradiate an ultrasonic beam into the inside of the object by placing the ultrasonic probe 101 on the surface of the object. The ultrasonic probe 101 receives reflected ultrasonic waves from inside the object, and converts the reflected ultrasonic waves into received electrical signals by the plurality of transducers 101a and supplies them to a reception unit 4 (described later).

[0027] In this embodiment, a linear type ultrasonic probe 101 in which a plurality of transducers 101a are arranged in a one-dimensional direction will be described as an example, but the present invention is not limited thereto. For example, it is possible to use a convex type or sector type ultrasonic probe 101 in which a plurality of transducers 101a are arranged in a one-dimensional direction, an ultrasonic probe 101 in which a plurality of transducers 101a are arranged in a two-dimensional direction, or an ultrasonic probe 101 in which a plurality of transducers 101a arranged in a one-dimensional direction oscillates. In addition, based on the control of the control unit 9, the transmission unit 3 selects the transducer 101a used by the ultrasonic probe 101, and individually changes the timing of applying a voltage to the transducer 101a and the voltage value, thereby controlling the irradiation position and irradiation direction of the ultrasonic beam transmitted by the ultrasonic probe 101.

[0028] Furthermore, the ultrasonic probe 101 may include some of the functions of the transmitting unit 3 and the receiving unit 4 described later. For example, the ultrasonic probe 101 may generate a drive signal within the ultrasonic probe 101 based on a control signal for generating a drive signal output from the transmitting unit 3 (hereinafter referred to as a "transmission control signal"), convert this drive signal into ultrasonic waves by the transducer 101a, convert received reflected ultrasonic waves into received electrical signals, and generate received signals within the ultrasonic probe 101 based on the received electrical signals, which will be described later.

[0029] Furthermore, the ultrasound probe 101 is generally configured to be electrically connected to the ultrasound diagnostic device main body 100 via a cable, but is not limited to this, and may be configured, for example, to transmit and receive transmission signals and reception signals between the ultrasound probe 101 and the ultrasound diagnostic device main body 100 by wireless communication such as UWB (Ultra Wide Band). However, in such a configuration, it goes without saying that the ultrasound diagnostic device main body 100 and the ultrasound probe 101 are configured to have a communication unit capable of wireless communication.

[0030] The operation unit 2 receives input from the user and outputs a command based on the user's input to the control unit 9. The operation unit 2 allows the user to select which mode to execute: a mode in which only a B-mode image in which the amplitude of the reflected ultrasound is represented by brightness (luminance) is displayed (hereinafter referred to as "B mode"), or a mode in which a C-mode (color flow mode) image is superimposed on the B-mode image (hereinafter referred to as "C mode"). The operation unit 2 also includes a function of accepting a user's input of a position of an ROI in which a C-mode image is displayed on the B-mode image. The C-mode image to be displayed further includes a V mode in which the flow velocity and direction of the blood flow are displayed in color based on the blood flow velocity V as a blood flow signal indicating the state of the blood flow, a P mode in which the power of the blood flow is displayed in color based on the power P of the blood flow as a blood flow signal, and a VT mode in which the flow velocity and variance of the blood flow are displayed in color based on the blood flow velocity V and the variance T as a blood flow signal. When the operation unit 2 accepts an input of the C mode from the user, it also accepts an input of the display mode. The display mode of the C-mode image may include a T (dispersion) mode, a dP (directional power) mode, etc. Thus, the C-mode includes a color Doppler mode (V mode, VT mode, etc.) and a power Doppler mode (P mode, etc.).

[0031] Moreover, the operation unit 2 may be provided on the display screen of the display unit 11 and include a touch panel that accepts touch input from the user.

[0032] The transmission unit 3 performs a transmission process of generating at least a drive signal and causing the ultrasonic probe 101 to transmit an ultrasonic beam. As an example, the transmission unit 3 performs a transmission process of generating a drive signal for transmitting an ultrasonic beam from the ultrasonic probe 101 having a transducer 101a, and drives the transducer 101a of the ultrasonic probe 101 by supplying a high-voltage drive signal generated at a predetermined timing to the ultrasonic probe 101 based on this drive signal. As a result, the ultrasonic probe 101 can irradiate the subject with an ultrasonic beam by converting the drive signal into ultrasonic waves.

[0033] When the C mode is on, the transmitting unit 3 performs a transmission process for displaying a C mode image in addition to a transmission process for displaying a B mode image under the control of the control unit 9. For example, after supplying an electrical drive signal for displaying a B mode image, the transmitting unit 3 repeatedly supplies a drive signal for displaying a C mode image in the same direction (same line) n times (n is, for example, 16, or more than 10 times), in all directions (all lines) of the ROI set by the ROI setting unit 6. In addition, the transmitting unit 3 specifies additional information for the transmission process for the B mode image or the transmission process for the C mode image during the transmission process, and supplies this additional information to the receiving unit 4.

[0034] The receiving unit 4 performs reception processing to generate a reception signal as an electrical RF (Radio Frequency) signal based on the reflected ultrasound under the control of the control unit 9. For example, the receiving unit 4 receives the reflected ultrasound with an ultrasonic probe 101, and generates a reception signal (sound ray data) by amplifying the reception electrical signal converted based on the reflected ultrasound, and performing A / D conversion and phasing addition.

[0035] The receiving unit 4 acquires the additional information from the transmitting unit 3, and if the acquired additional information is additional information for a B-mode image, it supplies a received signal to a B-mode image generating unit 5, and if the acquired additional information is additional information for a C-mode image, it supplies the received signal to a C-mode image generating unit 7. Hereinafter, a received signal for generating a B-mode image will be referred to as a "B-mode received signal", and a received signal for generating a C-mode image will be referred to as a "C-mode received signal".

[0036] In this embodiment, the receiving unit 4 selects whether the received signal related to the generated image frame is for a B-mode image or a C-mode image and supplies it to each block, but this is not limited to this. For example, the received signal related to the generated image frame may be selected by each of the B-mode image generating unit 5 and the C-mode image generating unit 7.

[0037] The B-mode image generating unit 5, under the control of the control unit 9, performs envelope detection, logarithmic compression, etc. on the B-mode received signal input from the receiving unit 4, adjusts the dynamic range and gain, and performs luminance conversion to generate B-mode image data, which is output to the display processing unit 8.

[0038] The ROI setting unit 6, under the control of the control unit 9, sets the ROI (hereinafter also referred to as the "region of interest") of the C-mode image in the transmission unit 3 and the display processing unit 8 in accordance with the ROI designation information input by the user via the operation unit 2.

[0039] The C-mode image generating unit 7 generates C-mode image data in response to the C-mode reception signal input from the receiving unit 4 under the control of the control unit 9 , and outputs the C-mode image data to the display processing unit 8 .

[0040] The C-mode image generating unit 7 has a quadrature detection circuit 71, a corner turn control unit 72, an MTI filter 73, a correlation calculation unit 74, a data conversion unit 75, a noise removal spatial filter unit 76, an inter-frame filter 77, and a C-mode image conversion unit 78 (see FIG. 3). The correlation calculation unit 74, the data conversion unit 75, the noise removal spatial filter unit 76, the inter-frame filter 77, and the C-mode image conversion unit 78 function as the "image generating unit" of the present invention.

[0041] The quadrature detection circuit 71, under the control of the control unit 9, performs quadrature detection on the C-mode received signal input from the receiving unit 4 to calculate the phase difference between the acquired C-mode received signal and a reference signal, and acquires (complex) Doppler signals I and Q.

[0042] The corner turn control unit 72, under the control of the control unit 9, arranges the Doppler signals I and Q input from the quadrature detection circuit 71 for each acoustic line in the depth direction from the ultrasonic probe 101 to the subject and in the ensemble direction of the number of repetitions n of ultrasonic transmission and reception (hereinafter abbreviated as "repetition number"), stores them in a memory (not shown), and reads out the Doppler signals I and Q in the ensemble direction for each depth.

[0043] The received signals (Doppler signals I, Q) contain not only the blood flow signal components necessary for generating a C-mode image, but also unnecessary information (clutter components) such as blood vessel walls and tissues. Under the control of the control unit 9, the MTI filter 73 filters the Doppler signals I, Q input from the corner turn control unit 72 to remove the clutter components.

[0044] Next, the internal configuration of the MTI filter 73 will be described with reference to Figures 4 to 11. The MTI filter 73 is the above-mentioned eigenvector type MTI filter.

[0045] Fig. 4 is a diagram showing the internal configuration of the MTI filter 73 according to this embodiment. Fig. 5 is a diagram showing the relationship between the input and output of the MTI filter 73. Fig. 6 is a diagram showing a method of calculating the MTI filter coefficients of the MTI filter 73. Fig. 7 is a diagram showing the data structure of packet data used to obtain one frame of a C-mode image.

[0046] The MTI filter 73 includes a principal component analysis execution unit 731 , a filter coefficient calculation unit 732 , a frequency analysis unit 733 , a reduction rate determination unit 734 , and a filtering processing unit 735 .

[0047] In the color Doppler method, ultrasonic transmission and reception is performed multiple times in the same direction while scanning the region of interest with ultrasonic waves, and blood flow signals are extracted from the time-series reflected wave data received. A data string of reflected wave signals (reflected wave data) from the same position obtained by such ultrasonic transmission and reception is called a packet. The packet size is the number of ultrasonic transmissions and receptions performed in the same direction to obtain one frame of blood flow information. The packet size in general color Doppler methods is around 5 to 16.

[0048] The complex number of n repetitions (packet size n) consisting of Doppler signals I and Q output from the corner turn control unit 72 is defined as packet data Sp. In this case, the packet data Sp is expressed as n pieces of time-series input data x(0), x(1), ..., x(n-1) obtained from the same position. x(0), x(1), ..., x(n-1) are arranged in the chronological order in which they were generated or in the reverse order.

[0049] The input and output of the MTI filter 73 are expressed, for example, by the following equation (1) (see FIG. 5). y=A reg ×x …(1) where y is the output vector indicating packet data y(0), y(1), …, y(n-1) output from the MTI filter, A reg : MTI filter coefficients (n×n filter matrix), x: input vector indicating input data x(0), x(1), ..., x(n-1).

[0050] The MTI filter 73 has an MTI filter coefficient A reg (n × n filter matrix) (see Figure 6). A reg =b×G×b H …(2) where b is an orthonormal basis (n × n matrix), G is a gain matrix (n × n matrix), and b H :b and an orthonormal basis for its Hermitian transpose (an n × n matrix).

[0051] The orthonormal basis b,b for calculating the MTI filter 73 H consists of multiple eigenvectors obtained by principal component analysis. H is expressed in descending order according to the magnitude of the eigenvalue, with the eigenvector with the largest eigenvalue being the 0th order. In other words, in the orthonormal basis b, the order increases as the column number increases. H In this case, the degree increases as the row number increases.

[0052] Diagonal elements G0,G1,…,G of gain matrix G n-1 corresponds to the clutter reduction rate of the MTI filter 73. When this diagonal element is 0, the reduction rate corresponds to 100%, and when this diagonal element is 1, the reduction rate corresponds to 0%. n-1 is the eigenvalues ​​arranged in ascending order according to the order. The diagonal elements G0, G1, …, G n-1 For example, the value is set to 0 and 1 at the boundary order corresponding to the rank cut order. The greater the clutter reduction rate of the MTI filter 73, the greater the diagonal components G0, G1, ..., G n-1 However, the diagonal elements G0, G1, …, G n-1 The value may be a number between 0 and 1 including a decimal point, other than 0 or 1.

[0053] In this embodiment, the orthonormal bases b, b H is calculated by the principal component analysis execution unit 731, and the gain matrix G (diagonal components G0, G1, ..., G n-1 ) is set by the reduction rate determination unit 734.

[0054] The principal component analysis execution unit 731, the filter coefficient calculation unit 732, the frequency analysis unit 733, the reduction rate determination unit 734, and the filtering processing unit 735 are, for example, functional units that execute the above-mentioned calculation processing.

[0055] The principal component analysis execution unit 731 executes principal component analysis on the time-series reflected wave data group within the region of interest obtained when the color flow mode is executed, and calculates the orthonormal basis b, b H Calculate the multiple eigenvectors that make up

[0056] Specifically, the principal component analysis execution unit 731 first acquires packet data (hereinafter referred to as "packet data group Sp1") of each observation point in the region of interest set in the ROI setting unit 6 from the corner turn control unit 72, and calculates a matrix C (see the following formula (3)) related to the packet data group Sp1 and a matrix C HThe packet data group Sp1 contains input data x0, x1, ..., x M The matrix C is an n×M matrix (see FIG. 7). In the packet data group Sp1, packet data of each observation point in the kth iteration of n repetitions is organized in frame units as F1(k-1).

number

[0057] Next, the principal component analysis execution unit 731 calculates the matrices C, C H The covariance matrix R is calculated from equation (4). R = C × C H …(4)

[0058] Then, the principal component analysis execution unit 731 solves the eigenvalue problem (i.e., Rb=λb) related to the covariance matrix R to obtain eigenvalues ​​and eigenvectors (i.e., orthonormal basis b, b H ) is calculated. At this time, the principal component analysis execution unit 731 calculates the eigenvalues ​​and eigenvectors for the nth order corresponding to the packet size, for example. Then, the principal component analysis execution unit 731 sends the calculated eigenvalues ​​and eigenvectors to the frequency analysis unit 733 and the MTI filter coefficient calculation unit 732.

[0059] The principal component analysis executing unit 731 sets the orders of the calculated eigenvectors so that the eigenvector with the largest eigenvalue is set as the 0th order and the orders increase in descending order according to the magnitude of the eigenvalue. Since the clutter signal usually has a larger signal intensity (i.e., eigenvalue) than the blood flow signal, the orders are assigned to the eigenvectors so that the eigenvectors on the low order side are eigenvectors related to the clutter signal and the eigenvectors on the high order side are eigenvectors related to the blood flow component.

[0060] The frequency analysis unit 733 calculates, for each of the n-th order eigenvectors calculated by the principal component analysis execution unit 731, the principal frequency component in the time direction represented by the eigenvector.

[0061] The inventors of the present application have found the conventional technique of determining the rank cut order from the magnitude of the eigenvalue of the eigenvector of each order problematic, as described above, and have sought a technique for determining the reduction rate of the eigenvector of each order by an approach different from that of the conventional technique. As a result of intensive investigation, they have come up with a technique for calculating the main frequency component in the time direction represented by each of the multiple eigenvectors by frequency analysis of each of the multiple eigenvectors, and determining the reduction rate of the eigenvector based on the main frequency component in the time direction represented by the eigenvector.

[0062] Since the eigenvector is a space-time vector (i.e., a composite vector of multiple frequency vectors) expressed in an eigenspace obtained by principal component analysis, it cannot be compared with the frequency band of clutter components in its current form. Therefore, the inventors of the present application performed frequency analysis of the eigenvectors of each order by a mathematical method using the following formulas (5) and (6), and calculated the main frequency component in the time direction represented by the eigenvector of each order. Note that the main frequency component in the time direction represented by the eigenvector (hereinafter abbreviated as "main frequency component represented by the eigenvector" or "eigenvector frequency") means, for example, the average frequency of the time change of the observation target position represented by the eigenvector.

[0063] Equation (5) is a formula for calculating the autocorrelation value of the eigenvector of each order associated with the reflected wave signal from the same position (here, the autocorrelation value of one lag difference among n repetitions). The autocorrelation value is a measure of how closely a signal matches a signal that is time-shifted from itself, and can represent the magnitude of the time shift. Here, equation (5) can be used to calculate the phase difference component in the time direction represented by the eigenvector of each order (i.e., the rate of phase change). Then, equation (6) is used to convert the phase difference component in the time direction represented by the eigenvector of each order into a frequency component in the time direction (eigenvector frequency).

[0064]

number

[0065]

number

[0066] In this way, the frequency analysis unit 733 calculates the main frequency components in the time direction represented by the eigenvectors of each order, making it possible to compare them with the frequency band of the clutter components.

[0067] In addition, in equation (5), the eigenvector e k The weight w for the m-th column value of m is a coefficient for weighting the average of each complex Doppler signal of the ultrasonic wave repeated n times. Weight w m is set so that the complex Doppler signals of the first and nth ultrasonic waves out of the nth repetition are small. This corresponds to the timing of switching the ultrasonic transmission and reception positions, and the weight of the first and nth complex Doppler signals that are likely to be unstable can be reduced. However, the weight w m The setting is optional.

[0068] The reduction rate determination unit 734 determines the reduction rate of the eigenvector of each order based on the main frequency component (eigenvector frequency) represented by the eigenvector of each order and the clutter component reduction condition that defines the reference frequency for reducing the clutter component. The reduction rate determination unit 734 then sets the gain matrix G of equation (2) based on the determined reduction rate of the eigenvector of each order, and outputs it to the MTI filter coefficient calculation unit 732.

[0069] The reference frequency is a time-varying frequency that serves as a reference for distinguishing between the frequency components of blood flow signals and the frequency components of clutter signals, and is typically set to an intermediate frequency between the typical frequency of blood flow signals and the typical frequency of clutter signals. The clutter component reduction conditions are, for example, stored in advance in the storage unit 10. Here, the reference frequency is described as a fixed value, but it is preferable that the reference frequency be adjustable by a user operation. It is also preferable that the reference frequency be automatically adjusted based on the transmission and reception conditions of ultrasound when the color flow mode is executed (described later with reference to the second to sixth embodiments).

[0070] For example, the reduction rate determination unit 734 compares the eigenvector frequency with a reference frequency for each order of the eigenvector, and when the eigenvector frequency exceeds the reference frequency, determines the reduction rate of the eigenvector to be 0, and when the eigenvector frequency is less than the reference frequency, determines the reduction rate of the eigenvector to be 1. Here, the reference frequency is a threshold value for determining the rank cut order (hereinafter also referred to as "threshold value").

[0071] Fig. 8 is a diagram showing an example of the process of the reduction rate determination unit 734 according to this embodiment. Fig. 8 shows a method in which the reduction rate determination unit 734 determines the rank cut order based on the eigenvector frequency. In the clutter component reduction conditions according to this embodiment, the value of the reference frequency is set to "0.5" (explained in absolute value notation, the same applies below), and it is specified that the reduction rate is 0 for eigenvectors whose eigenvector frequency exceeds "0.5", and the reduction rate is 1 for eigenvectors whose eigenvector frequency is less than "0.5". Here, the eigenvector frequency is calculated as a value from -1 to +1 using equation (6).

[0072] Here, with reference to Figs. 9A, 9B, 10A, 10B, and 11, the difference between the rank cut order determination method according to the prior art and the rank cut order determination method according to the present invention will be specifically described.

[0073] Fig. 9A is a diagram showing a method for determining the rank cut order according to the conventional technology. Fig. 9B is a diagram showing a method for determining the rank cut order according to the present invention. Fig. 9A and Fig. 9B show data related to eigenvectors of the same n (here, 12) orders calculated by the principal component analysis execution unit 731. The vertical axis of Fig. 9A indicates the eigenvalue of the eigenvector of each order, and the vertical axis of Fig. 9B indicates the eigenvector frequency of the eigenvector of each order.

[0074] FIG. 10A shows a blood flow image generated when the rank cut order is determined using the rank cut order determination method of the conventional technology (FIG. 9A), and FIG. 10B shows a blood flow image generated when the rank cut order is determined using the rank cut order determination method of the present invention (FIG. 9B).

[0075] Fig. 9A shows a mode in which the rank cut order is determined using "eigenvalue: -50" as a threshold value. In the prior art method of determining the rank cut order, in Fig. 9A, the reduction rate is determined to be 1 for eigenvectors of orders whose eigenvalues ​​are greater than -50, and the reduction rate is determined to be 0 for eigenvectors of orders whose eigenvalues ​​are -50 or less. As a result, in Fig. 9A, the 0th to 4th order eigenvectors are removed from the packet data group (i.e., blood flow images) after MTI filter processing.

[0076] Fig. 9B shows an aspect in which the rank cut order is determined using "eigenvector frequency: 0.5" as a threshold (here meaning a reference frequency). In the rank cut order determination method according to the present invention, in Fig. 9B, for eigenvectors of orders whose eigenvector frequency is smaller than 0.5, the reduction rate is determined to be 1, and for eigenvectors of orders whose eigenvector frequency is 0.5 or more, the reduction rate is determined to be 0. As a result, in Fig. 9B, eigenvectors of the 0th to 5th orders are removed from the packet data group (i.e., blood flow image) after MTI filter processing.

[0077] The difference between the case where the rank cut order determination method according to the prior art is adopted and the case where the rank cut order determination method according to the present invention is adopted is expressed as the difference in whether or not the fifth-order eigenvector is regarded as a reflected wave component based on a clutter signal in the aspects of Figures 9A and 9B. However, as can be seen from Figure 9B, the fifth-order eigenvector frequency actually represents a low-frequency component, and is highly likely to represent a clutter signal. Therefore, when the rank cut order determination method according to the prior art is adopted, a blood flow image (Figure 10A) in which a clutter signal based on the fifth-order eigenvector frequency remains is generated, and the image quality representing the blood flow signal is inferior to that of a blood flow image (Figure 10B) generated when the rank cut order is determined by the rank cut order determination method according to the present invention (Figure 9B).

[0078] Fig. 11 is a diagram showing the distribution of eigenvalues ​​of eigenvectors of each order and the distribution of eigenvector frequencies obtained when the region of interest (the target of packet data group acquisition) is set to a more local region and principal component analysis is performed. Fig. 11B and Fig. 11C are diagrams showing the distribution of eigenvalues ​​of eigenvectors of each order (Fig. 11B) and the distribution of eigenvector frequencies (Fig. 11C) obtained by principal component analysis when the region of interest is set to a thick blood vessel region (R1 region in Fig. 11A), and Fig. 11D and Fig. 11E are diagrams showing the distribution of eigenvalues ​​of eigenvectors of each order (Fig. 11D) and the distribution of eigenvector frequencies (Fig. 11E) obtained by principal component analysis when the region of interest is set to a thin blood vessel region (R2 region in Fig. 11A).

[0079] 11A to 11E also show that the eigenvalues ​​vary greatly with the signal strength of the blood flow signal and the clutter signal in the observation target region (see Figs. 11B and 11D). Therefore, in this example, if an attempt is made to set a threshold value for determining the rank cut order in accordance with the eigenvalue distribution in Fig. 11B, the clutter signal will be emphasized in the eigenvalue distribution in Fig. 11D.

[0080] On the other hand, it can be seen that the eigenvector frequencies associated with the clutter signals and the eigenvector frequencies associated with the blood flow signals are expressed in approximately the same frequency bands, regardless of the signal strengths of the blood flow signals and the clutter signals in the region being observed (see Figures 11C and 11E).

[0081] In this way, the distribution of eigenvalues ​​of the eigenvectors of the 0th to nth order components is greatly influenced by the strength of blood flow signals and the strength of tissue movement in the region of interest of the subject captured in the C-mode image, and the distribution of the eigenvalues ​​shows different patterns in regions with many blood flow signals (e.g., the carotid artery) and regions with few blood flow signals (e.g., the thyroid gland).In addition, in the high-order eigenvectors indicating blood flow signals, the change in eigenvalues ​​between orders is small, making it difficult to determine the order of the boundary between eigenvectors of orders that contain many clutter components and eigenvectors of orders that contain many blood flow signals.

[0082] For this reason, if a decision is made as to whether or not to reduce an eigenvector based on a threshold value of the eigenvalue of the eigenvector, there is a risk that a large amount of clutter signals will remain or even blood flow signals will be removed.

[0083] In this regard, in the present invention, the eigenvector of each order is frequency analyzed, the main frequency component represented by the eigenvector of each order is calculated, and the main frequency component represented by the eigenvector of each order is compared with the frequency component of the actual clutter signal to determine the reduction rate of the eigenvector of each order, which makes it possible to appropriately determine the reduction rate of the eigenvector of each order.

[0084] In this case, among the main frequency components represented by the eigenvectors of each order obtained by frequency analysis, the frequency components of the eigenvectors representing the blood flow signal show approximately the same high frequency regardless of the part of the observation target such as the carotid artery or the thyroid gland (see FIG. 9B). Therefore, even under conditions where the part of the observation target is different, it is possible to maintain stable blood flow extraction performance even if the reduction rate of the eigenvectors of each order is determined based on the same threshold value (i.e., the reference frequency).

[0085] In the above description, the reduction rate determination unit 734 determines the reduction rate of the eigenvector of each order to be 0 or 1. Alternatively, the reduction rate determination unit 734 may determine the reduction rate of the eigenvector to be a value between 0 and 1 (including a decimal point) based on the difference or ratio between the main frequency component represented by the eigenvector and a reference frequency. Among the multiple eigenvectors calculated by the principal component analysis execution unit 731, there are also eigenvectors that represent frequency components that include both clutter signals and blood flow signals. For such eigenvectors, it is preferable to finely adjust the reduction rate of the eigenvector between 0 and 1, including a decimal point, from the viewpoint of improving the image quality of the ultrasound image.

[0086] The MTI filter coefficient calculation unit 732, under the control of the control unit 9, calculates the filter coefficients of the MTI filter 73 (i.e., the MTI filter coefficients A Reg ) is calculated.

[0087] The MTI filtering processing unit 735, under the control of the control unit 9, calculates the packet data x input from the corner turn control unit 72 and the filter coefficients input from the MTI filter coefficient calculation unit 732 (i.e., the MTI filter coefficients A Reg ) and calculates packet data y as a complex Doppler signal according to equation (1), and outputs the calculated packet data y to the correlation calculation unit 74 as Doppler signals I, Q related to the blood flow components after clutter signals have been removed.

[0088] Returning to FIG. 3, the processing by the C-mode image generating unit 7 (correlation calculation unit 74, data conversion unit 75, noise removal spatial filter unit 76, inter-frame filter 77, and C-mode image conversion unit 78) following the processing by the MTI filter 73 will be described.

[0089] The correlation calculation unit 74, under the control of the control unit 9, calculates the real part D and the imaginary part N of the average value S (average value of the phase difference vector) of the autocorrelation calculation of the Doppler signal, given by the following equation (7), from the Doppler signals I, Q (complex Doppler signal z) filtered by the MTI filter 73.

number

[0090] The data conversion unit 75, under the control of the control unit 9, calculates the blood flow velocity V, power P, and variance T from the Doppler signals I and Q filtered by the MTI filter 73 and the real part D and imaginary part N of the average value S of the autocorrelation calculation of the Doppler signal. More specifically, the data conversion unit 75 calculates the blood flow velocity V from the real part D and imaginary part N of the average value S of the autocorrelation calculation of the Doppler signal using the following equation (8).

number

[0091] Furthermore, the data conversion unit 75 calculates power P as the average value of the intensity of the Doppler signal from the Doppler signals I and Q (complex Doppler signal z) using the following equation (9).

number

[0092] In addition, the data conversion unit 75 calculates the variance T as the ratio of the magnitude and power of the phase difference vector (however, this is subtracted from 1 to invert the magnitude) from the real part D and imaginary part N of the average value S of the autocorrelation calculation of the Doppler signal using the following equation (10).

number

[0093] The noise removal spatial filter unit 76 filters the power P, blood flow velocity V, and variance T calculated by the data conversion unit 75. The noise removal spatial filter unit 76 has, for example, a keyhole filter and a spatial filter (both not shown).

[0094] The keyhole filter filters the power P, blood flow velocity V, and variance T that constitute the frame of a C-mode image to remove noise. In V mode and VT mode, the keyhole filter removes the blood flow velocity V of the region to be removed that is set based on the blood flow velocity V calculated by the data conversion unit 75 and the power P, and filters the blood flow velocity V. In V mode and VT mode, the blood flow velocity V is used for image display (coloring). In P mode, the keyhole filter removes the power P of the region to be removed that is set based on the blood flow velocity V calculated by the data conversion unit 75 and the power P, and filters the power P. In P mode, the power P is used for image display (coloring).

[0095] More specifically, in V mode and VT mode, the keyhole filter regards blood flow signals in regions where the blood flow velocity V is smaller than a predetermined threshold as clutter noise, and blood flow signals in regions where the power P is smaller than a predetermined threshold as background noise, and removes the blood flow velocity V in these regions. In P mode, the keyhole filter regards blood flow signals in regions where the blood flow velocity V is smaller than a predetermined threshold as clutter noise, and blood flow signals in regions where the power P is smaller than a predetermined threshold as background noise, and removes the power P in these regions.

[0096] The spatial filter is a two-dimensional weighted average filter for smoothing data of blood flow velocity V, power P, and variance T that constitute a frame of a C-mode image. In the V mode or VT mode, the spatial filter filters the blood flow velocity V filtered by the keyhole filter and the variance T calculated by the data conversion unit 75. In the P mode, the spatial filter filters the power P filtered by the keyhole filter.

[0097] The inter-frame filter 77 filters the blood flow velocity V, power P, and variance T filtered by the noise removal spatial filter unit 76 in accordance with the display mode input through the operation unit 2, for the blood flow components of each frame constituting the C-mode image, so as to smooth out changes between frames and leave an afterimage.

[0098] The C-mode image conversion unit 78 performs color mapping on the blood flow velocity V, power P, and variance T filtered by the inter-frame filter 77, and converts them into C-mode image data.

[0099] Returning to Fig. 2, the display processing unit 8 constructs display image data to be displayed on the display unit 11, and performs processing to display the display image data on the display unit 11. In particular, when B mode is selected, processing is performed to include a B-mode image of the B-mode image data generated by the B-mode image generating unit 5 in the display image data as an ultrasound image. Also, when C mode is selected, processing is performed to generate composite image data by superimposing a C-mode image of the C-mode image data generated by the C-mode image generating unit 7 at the position of the ROI selected on the B-mode image generated by the B-mode image generating unit 5 as an ultrasound image, and to include this in the display image data.

[0100] The control unit 9 is configured with, for example, a CPU (Central Processing Unit), a ROM (Read Only Memory), and a RAM (Random Access Memory), reads out various processing programs such as a system program stored in the ROM, expands them in the RAM, and controls the operation of each part of the ultrasound diagnostic apparatus 1 according to the expanded programs. The RAM forms a work area for temporarily storing various programs executed by the CPU and data related to these programs. The ROM is configured with non-volatile memory such as a semiconductor, and stores the system program for the ultrasound diagnostic apparatus 1, various processing programs executable on the system program, and various data. These programs are stored in the form of computer-readable program codes, and the CPU sequentially executes operations in accordance with the program codes.

[0101] The storage unit 10 is configured, for example, by a large-capacity recording medium such as an HDD (Hard Disk Drive), and stores ultrasound image data (B-mode image data, C-mode image data, composite image data), a clutter removal table 110 described later, a frame rate table 120, a gain matrix, a frame rate, etc.

[0102] The display unit 11 displays image data output from the display processing unit 8, and is a so-called monitor such as an LCD (Liquid Crystal Display) or an EL (Electro Luminescence) display.

[0103] For each part of the ultrasound diagnostic device 1, a part or all of the functions of each functional block can be realized as a hardware circuit such as an integrated circuit. An integrated circuit is, for example, an LSI (Large Scale Integration), and an LSI may be called an IC (Integrated Circuit), a system LSI, a super LSI, or an ultra LSI depending on the degree of integration. The method of integrating the integrated circuit is not limited to an LSI, and may be realized by a dedicated circuit or a general-purpose processor, or may use a field programmable gate array (FPGA) or a reconfigurable processor that can reconfigure the connections and settings of circuit cells inside the LSI. Also, a part or all of the functions of each functional block may be executed by software. In this case, the software is stored in one or more storage media such as a ROM, an optical disk, or a hard disk, and the software is executed by a processor.

[0104] [effect] As described above, according to the ultrasound diagnostic apparatus 1 of this embodiment, for each of the multiple eigenvectors obtained by the principal component analysis of the reflected wave data group, the main frequency component represented by the eigenvector is calculated, and a reduction rate for reducing the eigenvector component from the ultrasound image is determined based on the main frequency component represented by the eigenvector.

[0105] This makes it possible to appropriately reduce clutter components from packet data groups (i.e., time-series reflected wave data groups within the region of interest obtained when running color flow mode) and extract blood flow information with a high S / N ratio, regardless of the size of the blood flow information within the region of interest or the part of the object of observation. This makes it possible to improve the image quality of ultrasound images without the need for users to set the filter characteristics of the MTI filter.

[0106] Second embodiment Next, the configuration of an ultrasound diagnostic device 1 according to a second embodiment will be described with reference to Fig. 12 and Fig. 13. The ultrasound diagnostic device 1 according to this embodiment differs from the ultrasound diagnostic device 1 according to the first embodiment in that a reduction rate determination unit 734 changes the setting of the clutter component reduction condition based on the ultrasound transmission / reception condition (here, the ultrasound repetition frequency) when the color flow mode is executed. Note that a description of the configuration common to the first embodiment will be omitted (the same applies to the other embodiments below).

[0107] FIG. 12 is a diagram for explaining an example of the process of the reduction rate determination unit 734 according to this embodiment.

[0108] The repetition frequency of the ultrasound when the color flow mode is executed is appropriately set and changed based on the type of the part to be observed, the depth of the part to be observed, the desired frame rate, etc. However, in general, the Doppler shift frequency obtained when the color flow mode is executed tends to shift overall to the high frequency side or the low frequency side depending on the repetition frequency of the ultrasound (see FIG. 12). Specifically, when the repetition frequency of the ultrasound is increased, the Doppler shift frequency overall shifts to the low frequency side, and when the repetition frequency of the ultrasound is decreased, the Doppler shift frequency overall shifts to the high frequency side.

[0109] This is because, in the ultrasonic diagnostic device 1, the measured value of the Doppler shift frequency (i.e., the measured value of the blood flow velocity) is generally calculated as a relative value to the maximum observable flow velocity value defined by the ultrasonic transmission / reception conditions, and this maximum observable flow velocity value is proportional to the repetition frequency. The maximum observable flow velocity Vmax is the critical velocity of the blood flow velocity at which no aliasing phenomenon (aliasing) occurs due to the ultrasonic transmission / reception conditions (i.e., the ultrasonic repetition frequency, the ultrasonic transmission frequency), and is calculated, for example, by using the following conventionally known formula (11). Vmax = c × ft / (4 × fs) × 10 -1 …(11) (where Vc [cm / s] is the maximum observable flow velocity, c [m / s] is the speed of ultrasound in the subject, ft [kHz] is the critical frequency of the pulse repetition frequency, and fs [MHz] is the transmission frequency of the ultrasound beam.)

[0110] That is, here, the maximum observable flow velocity Vmax is set to, for example, "1.0" in the above formula (6). The measured value of the blood flow velocity (i.e., the measured value of the Doppler shift frequency) is determined on the axis of frequency normalized by the ultrasonic transmission and reception conditions (i.e., the ultrasonic repetition frequency, the ultrasonic transmission frequency).

[0111] In this background, the frequency components of the clutter signal and the blood flow signal both change overall to the high or low frequency side depending on the ultrasonic repetition frequency. If the reduction rate of the eigenvector is determined without taking the ultrasonic repetition frequency into consideration, there is a risk that a large amount of clutter components will remain in the blood flow image, or conversely, that blood flow components will be removed excessively from the blood flow image.

[0112] From this viewpoint, the reduction rate determination unit 734 according to this embodiment changes the setting of the clutter component reduction condition so that the reference frequency (i.e., the frequency for distinguishing between blood flow components and clutter components) shifts to the higher frequency side as the repetition frequency of the ultrasound during execution of the color flow mode becomes lower.

[0113] Specifically, the reduction rate determination unit 734 according to this embodiment changes the reference frequency based on the repetition frequency of the ultrasonic waves when the color flow mode is executed, and typically, the lower the repetition frequency of the ultrasonic waves when the color flow mode is executed, the higher the reference frequency is changed (see FIG. 12). Note that the storage unit 10 stores correction data for shifting and correcting the reference frequency by the deviation of the repetition frequency of the ultrasonic waves when the color flow mode is executed from the standard value, and the reduction rate determination unit 734 sets the reference frequency using the correction data. Then, the reduction rate determination unit 734 determines the reduction rate for the eigenvector of each order using the corrected reference frequency.

[0114] This makes it possible to appropriately determine the reduction rate of the eigenvector so as to match the frequency band of the clutter components and the frequency band of the blood flow components, which change in conjunction with the repetition frequency of the ultrasound.

[0115] In this case, the reduction rate determination unit 734 according to the present embodiment may correct the eigenvector frequency instead of or together with correcting the reference frequency. FIG. 13 is a diagram for explaining another method of processing by the reduction rate determination unit 734 according to the present embodiment. For example, FIG. 13 shows that the value of the reference frequency is left as "0.5" and the value of the eigenvector frequency is converted to the value of "eigenvector frequency x ultrasonic repetition frequency (here, PRF / 2)". Here, the value of "ultrasonic repetition frequency" to be multiplied by the eigenvector frequency is a normalized value, and for example, the standard value of the repetition frequency is set to "1.0", and the repetition frequency when the color flow mode is executed is set to the larger or smaller side of "1.0" by the deviation from the standard value.

[0116] With this method, similarly to the above, the clutter component reduction conditions are changed so that the reference frequency is relatively shifted to the higher frequency side as the repetition frequency of the ultrasound during execution of the color flow mode is lower.

[0117] As described above, according to the ultrasound diagnostic device 1 of this embodiment, it is possible to appropriately determine the reduction rate of the eigenvector based on the ultrasound transmission and reception conditions (here, the ultrasound repetition frequency) when the color flow mode is executed, thereby enabling further improvement in the image quality of the ultrasound image.

[0118] (Third embodiment) Next, the configuration of an ultrasound diagnostic device 1 according to the third embodiment will be described with reference to Fig. 14 and Fig. 15. The ultrasound diagnostic device 1 according to this embodiment differs from the ultrasound diagnostic device 1 according to the first embodiment in that the reduction rate determination unit 734 automatically changes the settings of the clutter component reduction conditions based on the ultrasound transmission / reception conditions (here, the ultrasound transmission frequency) when the color flow mode is executed. The reduction rate determination unit 734 according to this embodiment is designed based on the same design concept as the reduction rate determination unit 734 described in the second embodiment.

[0119] FIG. 14 is a diagram for explaining an example of the process of the reduction rate determination unit 734 according to this embodiment.

[0120] The ultrasonic transmission frequency when the color flow mode is executed is appropriately set and changed based on the type of the part to be observed, the depth of the part to be observed, the desired frame rate, etc. However, in general, the Doppler shift frequency obtained when the color flow mode is executed tends to shift overall to the high frequency side or the low frequency side depending on the ultrasonic transmission frequency (see FIG. 14). Specifically, when the ultrasonic transmission frequency is increased, the Doppler shift frequency overall shifts to the high frequency side, and when the ultrasonic transmission frequency is decreased, the Doppler shift frequency overall shifts to the low frequency side.

[0121] This is because, generally, in the ultrasonic diagnostic device 1, the measured value of the Doppler shift frequency (i.e., the measured value of the blood flow velocity) is calculated as a relative value to the maximum observable flow velocity value defined by the ultrasonic transmission / reception conditions, and this maximum observable flow velocity value is proportional to the inverse of the transmission frequency.

[0122] The relationship between the maximum observable flow velocity value and the transmission frequency is as described above with reference to formula (11). In formula (11), the transmission frequency of the ultrasonic beam is the frequency of the burst wave transmitted as the ultrasonic beam. In the pulse Doppler mode, the Doppler shift frequency is calculated from the phase difference between the nth transmission wave and the n+1th transmission wave. Therefore, as the transmission frequency of the ultrasonic beam increases, the resolution of the Doppler shift frequency increases, but the maximum observable flow velocity value decreases.

[0123] In this context, the frequency components of the clutter signals and the blood flow signals will both vary overall to higher or lower frequencies depending on the transmission frequency of the ultrasound.

[0124] From this viewpoint, the reduction rate determination unit 734 according to this embodiment changes the setting of the clutter component reduction conditions so that the reference frequency (i.e., the frequency for distinguishing between blood flow components and clutter components) is shifted to the lower frequency side as the transmission frequency of the ultrasound when the color flow mode is executed is lower.

[0125] Specifically, the reduction rate determination unit 734 according to this embodiment changes the reference frequency set in the clutter component reduction condition based on the ultrasonic transmission frequency when the color flow mode is executed, and typically changes the reference frequency to a lower frequency value as the ultrasonic transmission frequency when the color flow mode is executed is lower (see FIG. 14). Note that the storage unit 10 stores correction data for shifting and correcting the reference frequency by the deviation of the ultrasonic transmission frequency when the color flow mode is executed from the standard frequency, and the reduction rate determination unit 734 sets the reference frequency using the correction data. Then, the reduction rate determination unit 734 determines the reduction rate for each order eigenvector using the corrected reference frequency.

[0126] This makes it possible to appropriately determine the reduction rate of the eigenvector so as to match the frequency band of the clutter components and the frequency band of the blood flow components, which change in conjunction with the transmission frequency of the ultrasonic waves.

[0127] In this case, the reduction rate determination unit 734 according to the present embodiment may correct the eigenvector frequency instead of or together with correcting the reference frequency. FIG. 15 is a diagram for explaining another method of processing by the reduction rate determination unit 734 according to the present embodiment. For example, FIG. 15 shows that the value of the reference frequency is left as "0.5" and the value of the eigenvector frequency is converted to the value of "eigenvector frequency x transmission frequency". Here, the value of "transmission frequency" multiplied by the eigenvector frequency is a normalized value, and for example, the standard value of the transmission frequency is set to "1.0", and the transmission frequency when the color flow mode is executed is set to the larger or smaller side of "1.0" by the deviation from the standard value.

[0128] With this method, similarly to the above, the clutter component reduction conditions are changed so that the reference frequency is relatively shifted to the higher frequency side as the transmission frequency of the ultrasound during execution of the color flow mode becomes lower.

[0129] As described above, according to the ultrasound diagnostic device 1 of this embodiment, it is possible to appropriately determine the reduction rate of the eigenvector based on the ultrasound transmission and reception conditions (here, the ultrasound transmission frequency) when the color flow mode is executed, thereby enabling further improvement in the image quality of the ultrasound image.

[0130] (Fourth embodiment) Next, the configuration of an ultrasonic diagnostic device 1 according to a fourth embodiment will be described with reference to Fig. 16 and Fig. 17. The ultrasonic diagnostic device 1 according to this embodiment differs from the ultrasonic diagnostic device 1 according to the first embodiment in that the reduction rate determination unit 734 automatically changes the setting of the clutter component reduction condition based on the ultrasonic transmission / reception condition (here, the flow velocity scale of the observation target) when the color flow mode is executed. The reduction rate determination unit 734 according to this embodiment is designed based on the same design concept as the reduction rate determination unit 734 described in the second embodiment.

[0131] 16 and 17 are diagrams for explaining the clutter component reduction conditions of the reduction rate determination unit 734 according to this embodiment.

[0132] The flow velocity scale specifies the range and resolution of blood flow velocity that can be displayed, and is set manually by the user or automatically based on the blood flow velocity during a predetermined period. Typically, the setting information of the flow velocity scale is automatically reflected in the pulse repetition frequency for transmitting an ultrasonic beam that corresponds to the sampling frequency. Specifically, when the flow velocity scale is set to the low velocity scale range (i.e., the range of the observation target is only low velocity), the pulse repetition frequency is set to a low frequency, and when the flow velocity scale is set to the high velocity scale range (i.e., the range of the observation target includes low velocity to high velocity), the pulse repetition frequency is set to a high frequency. This process is typically performed by the control unit 9.

[0133] In this way, since the flow velocity scale setting determines the pulse repetition frequency, the Doppler shift frequency obtained when the color flow mode is executed generally tends to shift to the high frequency side or the low frequency side depending on the flow velocity scale setting (see FIG. 16). Specifically, in general, when the flow velocity scale setting is increased, if the flow velocity scale setting is in the high velocity scale range (i.e., wide range scale), the Doppler shift frequency shifts to the low frequency side as a whole, and if the flow velocity scale setting is in the low velocity scale range, the Doppler shift frequency shifts to the high frequency side as a whole.

[0134] From this viewpoint, the reduction rate determination unit 734 according to this embodiment changes the reference frequency set in the clutter component reduction condition based on the flow velocity scale setting when the color flow mode is executed, as in the second embodiment. Typically, the lower the flow velocity scale setting when the color flow mode is executed, the higher the reference frequency is changed (see FIG. 16). Note that the storage unit 10 stores correction data for shifting and correcting the reference frequency by the deviation of the flow velocity scale setting when the color flow mode is executed from the standard scale, and the reduction rate determination unit 734 sets the reference frequency using the correction data. Then, the reduction rate determination unit 734 determines the reduction rate for each order eigenvector using the corrected reference frequency.

[0135] This makes it possible to appropriately determine the reduction rate of the eigenvector so as to match the frequency band of the clutter components and the frequency band of the blood flow components, which change in conjunction with the flow velocity scale setting.

[0136] In this case, the reduction rate determination unit 734 according to the present embodiment may correct the eigenvector frequency instead of or together with correcting the reference frequency. FIG. 17 is a diagram for explaining another method of processing by the reduction rate determination unit 734 according to the present embodiment. For example, FIG. 17 shows that the value of the reference frequency is left as "0.5" and the value of the eigenvector frequency is converted to the value of "eigenvector frequency x flow velocity scale setting". Here, the value of "flow velocity scale setting" multiplied by the eigenvector frequency is a normalized value, and for example, the standard value of the flow velocity scale setting is set to "1.0", and the flow velocity scale setting when the color flow mode is executed is set to the larger or smaller side from "1.0" by the deviation from the standard value.

[0137] With this method, similarly to the above, the clutter component reduction conditions are changed so that the reference frequency shifts relatively to the higher frequency side as the flow velocity scale setting when the color flow mode is executed becomes lower in the range of the flow velocity scale.

[0138] As described above, according to the ultrasound diagnostic device 1 of this embodiment, it is possible to appropriately determine the reduction rate of the eigenvector based on the ultrasound transmission and reception conditions (here, the flow velocity scale setting) when the color flow mode is executed, thereby enabling further improvement in the image quality of the ultrasound image.

[0139] Fifth embodiment Next, the configuration of an ultrasonic diagnostic apparatus 1 according to a fifth embodiment will be described with reference to FIGS.

[0140] Fig. 18 is a diagram showing the internal configuration of the MTI filter 73 according to this embodiment. Fig. 19 is a diagram for explaining the processing of the reduction rate determination section 734 according to this embodiment.

[0141] The ultrasound diagnostic apparatus 1 according to this embodiment differs from the ultrasound diagnostic apparatus 1 according to the first embodiment in that it has a tissue component analysis unit 736 that analyzes the frequency band in which the clutter components appear based on a time-series group of reflected wave data, and a reduction rate determination unit 734 that automatically changes the setting of the clutter component reduction condition so as to offset the frequency band of the reference frequency based on the frequency band in which the clutter components appear.

[0142] The blood vessels to be observed do not necessarily exist completely independent of the tissue structures (e.g., the heart) that are the source of the clutter components, but often exist on the tissue structures so as to be linked to the tissue structures. In such cases, the blood flow in the blood vessels to be observed is superimposed on the movement of the tissue structures, so the Doppler signal from the blood flow is Doppler shifted by the speed of the movement of the tissue structures. Therefore, the frequency band of the eigenvectors representing the blood flow calculated by the principal component analysis is also shifted by the speed of the movement of the tissue structures.

[0143] From this perspective, in the ultrasound diagnostic device 1 according to this embodiment, the reference frequency (i.e., the frequency for distinguishing between blood flow components and clutter components) is offset by an amount corresponding to the speed of the movement of the tissue structure superimposed on the blood vessel under observation (see FIG. 19).

[0144] Specifically, the tissue component analysis unit 736 acquires a group of time-series reflected wave data obtained in the blood flow region of the observation target from the corner turn control unit 72 when the color flow mode is executed. The tissue component analysis unit 736 then performs a conventionally known frequency analysis using FFT, autocorrelation calculation, or the like on the group of time-series reflected wave data obtained in the blood flow region of the observation target to calculate the frequency components contained in the blood flow region of the observation target, and thereby obtains the frequency components related to the clutter components in the blood flow region of the observation target. At this time, the tissue component analysis unit 736 may, for example, estimate the frequency components in a low frequency band having the strongest signal intensity among the frequency components contained in the blood flow region of the observation target as the frequency components related to the clutter components, or may estimate the average frequency of the frequency components contained in the blood flow region of the observation target as the frequency components related to the clutter components.

[0145] The reduction rate determination unit 734 offsets the frequency band of the reference frequency based on the frequency components related to the clutter components estimated by the tissue component analysis unit 736 (see FIG. 19). Note that the storage unit 10 stores correction data for shifting and correcting the reference frequency in accordance with the frequency components related to the clutter components, and the reduction rate determination unit 734 sets the reference frequency using the correction data. For example, FIG. 19 shows an aspect in which the reduction rate determination unit 734 changes the setting of the reference frequency from the initial value "0.5" to a value "0.6" offset by the frequency component "0.1" related to the clutter components. Then, the reduction rate determination unit 734 uses the offset reference frequency to determine the reduction rate of the eigenvector of each order.

[0146] As described above, according to the ultrasonic diagnostic device 1 of this embodiment, it is possible to appropriately determine the reduction rate of the eigenvector by offsetting the frequency band of the reference frequency based on the frequency band of the clutter components in the blood flow region of the observation target, thereby enabling further improvement in the image quality of the ultrasonic image.

[0147] The time-series reflected wave data group on which the tissue component analysis unit 736 performs frequency analysis is typically a reflected wave data group obtained in the ROI region when the color flow mode is executed (i.e., a reflected wave data group used in the principal component analysis by the principal component analysis execution unit 731). However, the reflected wave data group does not necessarily have to be obtained at the same timing as the reflected wave data group used in the principal component analysis by the principal component analysis execution unit 731. For example, the reflected wave data group may be a reflected wave data group obtained one time earlier than the reflected wave data group used in the principal component analysis by the principal component analysis execution unit 731.

[0148] Sixth embodiment Next, the configuration of an ultrasonic diagnostic apparatus 1 according to a sixth embodiment will be described with reference to FIGS.

[0149] The ultrasonic diagnostic device 1 according to this embodiment is configured to have all of the automatic reference frequency setting functions described in the second to fifth embodiments so that the reference frequency can be set to a more accurate value. However, the ultrasonic transmission frequency, ultrasonic repetition frequency, and flow velocity scale setting may be automatically set in conjunction with each other depending on the operation setting of the ultrasonic diagnostic device 1. Therefore, in the ultrasonic diagnostic device 1 according to this embodiment, each of these automatic setting functions can be switched between enabled and disabled by a user's operation. Note that setting information related to the enablement or disablement of each of these automatic setting functions is stored in, for example, the storage unit 10.

[0150] 20 and 21 are diagrams for explaining the operation flow of the ultrasonic diagnostic device 1 according to this embodiment. Note that it is assumed here that each of the automatic reference frequency setting functions described in the second to fifth embodiments has already been enabled or disabled by a user operation.

[0151] FIG. 20 is a diagram showing a process in which the ultrasound diagnostic device 1 according to this embodiment first sets a threshold value (i.e., a reference frequency) that determines the rank cut order based on ultrasound transmission and reception conditions when executing the color flow mode.

[0152] In step Sa1, the ultrasound diagnostic apparatus 1 (reduction rate determination unit 734) acquires the threshold value of the eigenvector frequency from the storage unit 10. The threshold value acquired at this time means the initial value before adjustment, and corresponds to "0.5" in FIG. 8.

[0153] In step Sa2, the ultrasonic diagnostic device 1 (reduction rate determination unit 734) determines whether or not to link the threshold for determining the rank cut order to the transmission frequency based on the user's setting information. If the threshold is linked to the transmission frequency (Sa2: YES), the process proceeds to step Sa3. On the other hand, if the threshold is not linked to the transmission frequency (Sa2: NO), the process proceeds to step Sa4.

[0154] In step Sa3, the ultrasound diagnostic device 1 (reduction rate determination unit 734) adjusts the threshold value according to the transmission frequency of the ultrasound when the color flow mode is executed. At this time, the ultrasound diagnostic device 1 (reduction rate determination unit 734) corrects the threshold value by shifting it to the lower frequency side as the transmission frequency of the ultrasound when the color flow mode is executed is lower.

[0155] In step Sa4, the ultrasonic diagnostic device 1 (reduction rate determination unit 734) determines whether or not to link the threshold for determining the rank cut order to the ultrasonic repetition frequency (RPF) based on the user's setting information. If the threshold is linked to the ultrasonic repetition frequency (Sa4: YES), the process proceeds to step Sa5. On the other hand, if the threshold is not linked to the ultrasonic repetition frequency (Sa4: NO), the process proceeds to step Sa6.

[0156] In step Sa5, the ultrasound diagnostic device 1 (reduction rate determination unit 734) adjusts the threshold value according to the repetition frequency of the ultrasound when the color flow mode is executed. At this time, the ultrasound diagnostic device 1 (reduction rate determination unit 734) corrects the threshold value by shifting it to the higher frequency side as the repetition frequency of the ultrasound when the color flow mode is executed is lower.

[0157] In step Sa6, the ultrasonic diagnostic device 1 (reduction rate determination unit 734) determines whether or not to link the threshold that determines the rank cut order to the flow velocity scale based on the user's setting information. If the threshold is to be linked to the flow velocity scale (Sa6: YES), the process proceeds to step Sa7. On the other hand, if the threshold is not to be linked to the flow velocity scale (Sa6: NO), the process of the flowchart in FIG. 20 is terminated.

[0158] In step Sa7, the ultrasound diagnostic device 1 (reduction rate determination unit 734) adjusts the threshold value according to the flow velocity scale when the color flow mode is executed. At this time, the ultrasound diagnostic device 1 (reduction rate determination unit 734) corrects the threshold value by shifting it to the high frequency side as the flow velocity scale when the color flow mode is executed is in the low velocity scale range.

[0159] FIG. 21 is a diagram showing the process that the ultrasound diagnostic device 1 according to this embodiment executes every time it generates each frame of a blood flow image while the color flow mode is being executed.

[0160] In step S1, the ultrasound diagnostic device 1 performs ultrasound scanning within a region of interest while transmitting and receiving ultrasound multiple times in the same direction when executing the color flow mode, and obtains a time-series reflected wave data group thus received as an analysis target for principal component analysis (i.e., a packet data group).

[0161] In step S2, the ultrasound diagnostic apparatus 1 (principal component analysis execution unit 731) performs principal component analysis on the packet data group acquired in step S1 (that is, solves the eigenvalue problem related to the covariance matrix R) and calculates eigenvectors.

[0162] In step S3, the ultrasound diagnostic apparatus 1 (frequency analysis unit 733) calculates the main frequency components represented by the eigenvectors of each order using the above-mentioned equations (5) and (6).

[0163] In step S4, the ultrasound diagnostic device 1 (reduction rate determination unit 734) determines whether or not to link the threshold for determining the rank cut order to the average frequency of the packet data group (i.e., the clutter component) based on the user's setting information. If the threshold is to be linked to the average frequency of the packet data group (i.e., the frequency band of the clutter component) (S4: YES), the process proceeds to step S5. On the other hand, if the threshold is not to be linked to the average frequency of the packet data group (i.e., the frequency band of the clutter component) (S4: NO), the process proceeds to step S7.

[0164] In step S5, the ultrasonic diagnostic apparatus 1 (tissue component analysis section 736) calculates the average frequency of the packet data group (that is, the frequency band of the clutter components).

[0165] In step S6, the ultrasound diagnostic device 1 (reduction rate determination unit 734) adjusts the threshold based on the average frequency of the packet data group calculated in step S5. Note that the threshold referred to in step S6 is the threshold determined in the process of the flowchart in FIG.

[0166] In step S7, the ultrasound diagnostic apparatus 1 (reduction rate determination section 734) determines the reduction rate of the eigenvector of each order from the frequency of the eigenvector based on a threshold value.

[0167] In step S8, the ultrasound diagnostic apparatus 1 (filter coefficient calculation unit 732) calculates the filter coefficients of the MTI filter 73 using the above-mentioned equation (2) by referring to the reduction rate of the eigenvector of each order determined in step S7.

[0168] In step S9, the ultrasound diagnostic apparatus 1 (filtering processing unit 735) refers to the MTI filter 73 calculated in step S8 and performs filtering processing on the packet data group acquired in step S1 using the above-mentioned equation (1), and treats the calculated packet data group as Doppler signals related to blood flow components after clutter signal removal.

[0169] In step S10, the ultrasound diagnostic apparatus 1 (correlation calculation unit 74) performs autocorrelation calculation processing on the Doppler signal obtained in step S9.

[0170] In step S11, the ultrasound diagnostic apparatus 1 (data conversion unit 75, noise removal spatial filter unit 76, inter-frame filter 77, C-mode image conversion unit 78) estimates blood flow information based on the Doppler signal obtained in step S10.

[0171] The ultrasound diagnostic device 1 according to this embodiment is capable of generating high-quality blood flow images through such processing.

[0172] As described above, according to the ultrasound diagnostic device 1 of this embodiment, it is possible to appropriately determine the reduction rate of the eigenvector based on the ultrasound transmission and reception conditions when the color flow mode is executed, and therefore it is possible to further improve the image quality of the ultrasound image.

[0173] Although the specific examples of the present invention have been described in detail above, these are merely examples and do not limit the scope of the claims. The technology described in the claims includes various modifications and changes of the specific examples exemplified above. [Industrial Applicability]

[0174] According to the ultrasound diagnostic device according to the present disclosure, it is possible to automatically set appropriate MTI filter characteristics. [Explanation of symbols]

[0175] 1. Ultrasound diagnostic equipment 2 Control section 3. Transmitter 4. Receiving section 5 B-mode image generation unit 6 ROI setting section 7 C-mode image generation unit 8 Display Processing Section 9. Control Unit 10 Storage section 71 Quadrature detection circuit 72 Corner turn control section 73 MTI Filter 731 Principal Component Analysis Execution Unit 732 Filter coefficient calculation section 733 Frequency Analysis Section 734 Reduction Rate Determination Unit 735 Filtering Processing Unit 736 Tissue component analysis department 74 Correlation calculation section 75 Data Conversion Section 76 Noise reduction spatial filter section 77 Interframe Filter 78 C-mode image conversion unit 100 Ultrasound diagnostic device body 101 Ultrasonic probe 101a Transducer

Claims

1. 1. An ultrasound diagnostic apparatus for generating a blood flow image within a subject by transmitting ultrasound into the subject and receiving reflected waves thereof, comprising: a principal component analysis execution unit that executes a principal component analysis on a time series reflected wave data group in a predetermined region in the subject obtained during execution of a color flow mode, and calculates a plurality of eigenvectors; a frequency analysis unit that calculates a main frequency component in a time direction represented by each of the plurality of eigenvectors by performing a frequency analysis on each of the plurality of eigenvectors using an autocorrelation calculation; a reduction rate determination unit that determines a reduction rate of each of the plurality of eigenvectors based on the main frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reducing the clutter component; a filter coefficient calculation unit that calculates a filter coefficient for reducing clutter components based on a plurality of the eigenvectors and the reduction rate corresponding to each of the plurality of the eigenvectors; an image generating unit that applies the filter coefficients to the time-series reflected wave data group to generate blood flow image data; Equipped with the main frequency component of each of the plurality of eigenvectors is an average frequency of a time change of an observation target position represented by each of the plurality of eigenvectors, the reduction rate determination unit changes the setting of the clutter component reduction condition so as to shift the reference frequency to a higher frequency side or a lower frequency side based on an ultrasonic transmission / reception condition when the color flow mode is executed. Ultrasound diagnostic equipment.

2. the reduction rate determination unit determines the reduction rate of the eigenvector to be 0 when the main frequency component of the eigenvector exceeds the reference frequency, and determines the reduction rate of the eigenvector to be 1 when the main frequency component of the eigenvector is less than the reference frequency. The ultrasonic diagnostic apparatus according to claim 1 .

3. the reduction rate determination unit determines the reduction rate of the eigenvector to a value greater than or equal to 0 and less than or equal to 1 based on a difference or a ratio between the main frequency component of the eigenvector and the reference frequency; The ultrasonic diagnostic apparatus according to claim 1 .

4. The frequency analysis unit calculates the main frequency component of the eigenvector based on an autocorrelation value of the eigenvector in accordance with the following formulas (1) and (2): The ultrasonic diagnostic apparatus according to claim 1 . [0010] [0025]

5. The ultrasonic transmission / reception conditions include an ultrasonic transmission frequency. The ultrasonic diagnostic apparatus according to claim 1 .

6. The ultrasonic transmission and reception conditions include an ultrasonic repetition frequency. The ultrasonic diagnostic apparatus according to claim 1 .

7. The ultrasonic transmission and reception conditions include a flow velocity scale setting. The ultrasonic diagnostic apparatus according to claim 1 .

8. a tissue component analysis unit that analyzes a frequency band of clutter components based on a group of time-series reflected wave data in a predetermined region in the subject obtained when a color flow mode is executed; the reduction rate determination unit changes a setting of the clutter component reduction condition so as to offset the reference frequency based on a frequency band of the clutter components. The ultrasonic diagnostic apparatus according to claim 1 .

9. the reduction rate determination unit is configured to be able to change the clutter component reduction condition based on first information relating to a transmission frequency of ultrasonic waves, second information relating to a repetition frequency of ultrasonic waves, third information relating to a blood flow velocity scale setting, and fourth information relating to a frequency band in which clutter components appear, when the color flow mode is executed; the reduction rate determination unit determines whether each of the first to fourth information is valid or invalid as information to be referenced when changing the clutter component reduction condition based on a setting operation by a user. The ultrasonic diagnostic apparatus according to claim 1 .

10. The reduction rate determination unit is configured to adjust the reference frequency based on a setting operation by a user. The ultrasonic diagnostic apparatus according to claim 1 .

11. 1. A method for controlling an ultrasound diagnostic apparatus that generates a blood flow image within a subject by transmitting ultrasound waves into the subject and receiving reflected waves, comprising the steps of: a first process of calculating a plurality of eigenvectors by performing a principal component analysis on a time series of reflected wave data in a predetermined region of the subject obtained during execution of a color flow mode; a second process of calculating a main frequency component in a time direction represented by each of the plurality of eigenvectors by analyzing each of the plurality of eigenvectors using an autocorrelation calculation; a third process of determining a reduction rate of each of the plurality of eigenvectors based on the main frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reducing the clutter component; a fourth process of calculating a filter coefficient for reducing clutter components based on a plurality of the eigenvectors and the reduction rate corresponding to each of the plurality of the eigenvectors; A fifth process of applying the filter coefficients to the time-series reflected wave data group to generate blood flow image data; having the main frequency component of each of the plurality of eigenvectors is an average frequency of a time change of an observation target position represented by each of the plurality of eigenvectors, In the fourth process, the clutter component reduction condition is changed so as to shift the reference frequency to a higher frequency side or a lower frequency side based on an ultrasonic transmission / reception condition when the color flow mode is executed. Control methods.

12. 1. A control program for an ultrasound diagnostic apparatus for generating a blood flow image in a subject by transmitting ultrasound into the subject and receiving the reflected waves, comprising: a first process of calculating a plurality of eigenvectors by performing a principal component analysis on a time series of reflected wave data in a predetermined region of the subject obtained during execution of a color flow mode; a second process of calculating a main frequency component in a time direction represented by each of the plurality of eigenvectors by analyzing each of the plurality of eigenvectors using an autocorrelation calculation; a third process of determining a reduction rate of each of the plurality of eigenvectors based on the main frequency component of each of the plurality of eigenvectors and a clutter component reduction condition that defines a reference frequency for reducing the clutter component; a fourth process of calculating a filter coefficient for reducing clutter components based on a plurality of the eigenvectors and the reduction rate corresponding to each of the plurality of the eigenvectors; A fifth process of applying the filter coefficients to the time-series reflected wave data group to generate blood flow image data; having the main frequency component of each of the plurality of eigenvectors is an average frequency of a time change of an observation target position represented by each of the plurality of eigenvectors, In the fourth process, the clutter component reduction condition is changed so as to shift the reference frequency to a higher frequency side or a lower frequency side based on an ultrasonic transmission / reception condition when the color flow mode is executed. Control program.

Images