JP4616614B2 - Ultrasonic diagnostic equipment - Google Patents

Description

  The present invention relates to an ultrasonic diagnostic apparatus, and more particularly to removal of unnecessary components contained in a velocity signal.

  In an ultrasonic diagnostic apparatus that forms a blood flow image, generally, a received signal obtained by transmitting and receiving an ultrasonic wave is configured by an MTI filter (Moving Target Indicator Filter) or the like via an orthogonal detection processing circuit. Input to the motion filter. In the filter, clutter components (low-frequency moving body components such as a heart wall) included in the received signal are removed. The signal that has passed through the filter is input to a speed calculation unit including an autocorrelation circuit and an arctangent calculation circuit, and the received signal is converted into a speed signal. Here, the speed signal is constituted by a speed value for each sample point. The speed signal is output to the image forming unit via a noise removal circuit or the like. The noise removal circuit will be described later. The image forming unit includes a digital scan converter and the like, and forms a color two-dimensional blood flow image based on the speed signal. The above autocorrelation circuit is generally a circuit that performs autocorrelation calculation between a plurality of beam data obtained by forming a plurality of ultrasonic beams on the same beam address, specifically, each sample on the beam. For each point, a speed value is obtained by performing autocorrelation calculation between temporally adjacent beams.

  The velocity signal composed of the velocity values of the respective sample points includes a residual clutter component that cannot be removed by the wall motion filter, and also includes a residual noise component that cannot be removed by the noise removal circuit. The residual clutter component and the residual noise component are defined as a residual unnecessary component (residual noise component in a broad sense). Such residual unnecessary components cause a decrease in the image quality of the blood flow image, and therefore effective removal thereof is desired.

  Patent Document 1 below discloses an ultrasonic diagnostic apparatus having an MTI filter, a correlation calculator, a selector, and the like. The Patent Document 1 discloses a selector that selectively passes a speed signal obtained by autocorrelation based on the level of the output signal of the MTI filter or based on the difference between the input signal and the output signal of the MTI filter. It is described that the operation is controlled. Patent Document 2 below describes an ultrasonic diagnostic apparatus that removes unnecessary signals (noise component and clutter component) based on a combination of a real part component and an imaginary part component in the output of an autocorrelation calculator. Patent Document 3 below describes an ultrasonic diagnostic apparatus that discriminates and removes noise components and clutter components based on a combination of power, flow velocity value, and dispersion. However, Patent Documents 1 to 3 do not describe consideration of spatial pixel value randomness (variation) or spatial correlation calculation.

  Patent Document 4 below describes an ultrasonic diagnostic apparatus that determines the processing content of a pixel of interest in a window based on the sum of pixel values in the window after binarization processing and the pixel pattern. Patent Document 5 below discloses an ultrasonic diagnostic apparatus that removes isolated pixels or a small number of consecutive pixels as noise. Patent Documents 4 and 5 do not describe consideration of spatial pixel value randomness or spatial correlation calculation, similar to Patent Documents 1 to 3.

JP 2003-250802 A Japanese Patent Laid-Open No. 7-178092 JP-A-4-218143 JP 7-108043 A JP-A-8-280683

  In order to improve the image quality of a blood flow image, it is required to effectively remove clutter components and noise components, that is, unnecessary components. For this purpose, clutter component removing means and noise component removing means are provided. May have the same velocity value and power as the blood flow component, and the conventional method may not always effectively remove unnecessary signals. In particular, it is desirable to further remove residual unnecessary components that remain after the removal processing of the clutter component and the noise component, but the above-mentioned documents do not disclose a configuration for performing such post-processing.

  An object of the present invention is to effectively remove unnecessary components contained in a speed signal.

  Another object of the present invention is to remove residual unnecessary components that remain after the removal processing of clutter components or noise components.

  Another object of the present invention is to effectively remove unnecessary components or residual unnecessary components by utilizing their spatial properties.

(1) In the present invention, based on a received signal obtained by transmitting and receiving an ultrasonic wave, speed calculation means for calculating a speed value at each sample point, and a ternary process for the speed value at each sample point. , A ternary means for obtaining an attribute value for each sample point, and a spatial region for a region of interest set on the basis of each sample point based on the spatial attribute value array after the ternarization process Randomness evaluation calculation for evaluating randomness is performed, evaluation means for obtaining an evaluation value for each sample point, and the velocity value of each sample point is calculated based on the evaluation value for each sample point. After determining whether it is a flow component or an unnecessary component and executing a process for removing the unnecessary component and executing the process for removing the unnecessary signal, a blood flow image is formed based on the blood flow component Blood flow image forming means And wherein the door.

  According to the above configuration, the velocity value of each sample point is calculated based on the received signal obtained by the transmission / reception of the ultrasonic wave, and the velocity value is normalized to any attribute value by the ternary processing. Then, the randomness of the attribute values in the spatial attribute value array (attribute value set) is evaluated as an evaluation value, and unnecessary components (or residual unnecessary components) are discriminated and removed based on the evaluation values. That is, a signal component having a relatively large randomness is recognized as an unnecessary component and is removed prior to blood flow image formation.

  Generally, regarding the blood flow part, when viewed spatially, the magnitude and sign of individual velocity values tend to be somewhat continuous except for the so-called folded part, while unnecessary components are spatially scattered. The size and code exhibit randomness. This is particularly noticeable for the speed signal after the clutter component is removed and after the noise component is removed. In such a case, it is not possible to recognize such a spatial tendency simply by focusing on the velocity value of the sample point of interest. However, according to the present invention, spatial randomness of the region of interest based on the sample point of interest is used. The evaluation result can be used for discrimination of unnecessary components (or residual unnecessary components).

  It is particularly desirable that the series of processes from the ternarization process to the removal process be performed after the clutter component removal process and the noise component removal process are performed. That is, it is desirable that the process be performed on residual unnecessary components. However, even if it is applied at a stage where one or both of the clutter component removal processing and the noise component removal processing are not performed, or is applied in parallel with these processing, a certain effect can be obtained. The clutter component removal processing is desirably processing for removing low-speed moving body components using a known MTI filter. Various known methods can be used as the noise component removal process, and examples include a process including a threshold process for the power value of the sample point. Note that the series of processes described above may be incorporated in the noise component removal process.

  In the above configuration, the ternarization processing is performed prior to the evaluation of the spatial randomness, that is, the speed value is standardized. There are advantages that the randomness evaluation calculation can be simplified and the evaluation accuracy can be improved. As a modification, a binarization process that substitutes for the ternarization process and a standardization process of four or more values can be given, but the ternarization process is desirable when spatially discriminating unnecessary components. The region of interest is preferably a one-dimensional region or a two-dimensional region, but may be a three-dimensional region.

  Preferably, in the ternarization process, a positive attribute value is given when the velocity value of each sample point satisfies the first condition, and a zero attribute value when the velocity value of each sample point satisfies the second condition. And a negative attribute value is assigned when the velocity value of each sample point satisfies the third condition. That is, the velocity axis is divided into three sections, and the division to which the velocity value of the sample point belongs is determined. Here, the second condition may be a condition that the speed value is zero, or may be a condition that the speed value enters a certain section that spans the positive and negative polarity across the speed value zero. When the clutter component removal process and the noise component removal process are performed in the preceding stage of the above-described series of processes, the unnecessary signal should be considerably removed. Therefore, the second condition is that the speed value is zero. Can be adopted. This ternary processing corresponds to preprocessing for evaluating spatial randomness.

  Desirably, the evaluation means performs the randomness evaluation calculation between the region of interest and a reference region obtained by spatially shifting the region of interest. It is desirable that the forms (size and shape) of the attention area and the reference area coincide with each other, and the shift direction and the shift amount between them can be appropriately set. For example, the shift amount may be one sample point. The attention area and the reference area may exist in different beams or frames. Preferably, the randomness evaluation calculation corresponds to a correlation calculation, and the evaluation value corresponds to a correlation value.

  Preferably, the region of interest is a one-dimensional region along the beam direction, and the reference region is a region obtained by shifting the region of interest in the beam direction. In the case of a one-dimensional region, it is convenient because a randomness evaluation calculation can be performed for each sample point on the beam using one received signal (time-series signal) corresponding to one beam. Preferably, the attention area is a two-dimensional area on the frame, and the reference area is an area obtained by shifting the attention area on the frame. The shift direction is one or both of the horizontal direction and the vertical direction.

  Preferably, for each of the sample points, the removing means is based on a combination of the velocity value of the sample point and the evaluation value calculated for the sample point, or whether the velocity value of each sample point is a blood flow component or not. Determine if it is a component. According to this configuration, the difference between the velocity value and the evaluation value between the blood flow component and the unnecessary component can be used to distinguish the two with high accuracy. Further, the third reference information may be taken into consideration. Preferably, the removing unit determines that the velocity value is an unnecessary component when the velocity value satisfies a first determination condition and the evaluation value satisfies a second determination condition.

(2) The present invention provides a clutter component removing means for removing a clutter component included in a received signal obtained by transmitting / receiving ultrasonic waves, and the received signal after the removal of the clutter component based on the received signal of each sample point. Based on speed calculation means for calculating a speed value, noise component removal means for removing a noise component included in a speed signal constituted by the speed value for each sample point, and the speed value of each sample point , An attribute value calculation means for obtaining an attribute value for each sample point, and a spatial random for a region of interest set based on each sample point based on a spatial attribute value array after the attribute value calculation Based on the evaluation means for calculating the evaluation value for each sample point, the speed value and the evaluation value for each sample point Determining whether the velocity value of each sample point is a blood flow component or a residual unnecessary component, and executing a process of removing the residual unnecessary component; and a process of removing the residual unnecessary component Blood flow image forming means for forming a blood flow image based on a blood flow component after execution.

  According to the above configuration, the clutter component removing unit firstly removes the clutter component in the received signal, and then the noise component removing unit removes the noise component such as white noise (in this case, the residual component). Clutter is also subject to removal). In addition, it is possible to effectively remove residual unnecessary components (which can be regarded as a mixture of residual noise and residual clutter) that remain even after such treatment.

  Focusing on the individual sample points, the residual unnecessary component often has the same velocity value and sign as the blood flow component, and the blood flow component and the residual unnecessary component are discriminated only by considering only the velocity value. However, if it is viewed with a certain spatial extent, there is a difference in the evaluation value of randomness between the blood flow component and the residual unnecessary component. Therefore, it can be used for discrimination between blood flow components and residual unnecessary components. Here, although it is possible in some cases to discriminate on the basis of only the evaluation value, it is desirable to consider the speed value itself in addition to the evaluation value in order to ensure discrimination accuracy. Of course, other third information can be taken into consideration.

  Preferably, the attribute value calculation means gives a positive attribute value when the velocity value of each sample point satisfies a first condition, and a zero attribute value when the velocity value of each sample point satisfies a second condition. And ternarization processing means for assigning a negative attribute value when the velocity value of each sample point satisfies the third condition. Preferably, the evaluation means executes the randomness evaluation calculation corresponding to a correlation calculation between the attention area and a reference area obtained by spatially shifting the attention area.

  As described above, according to the present invention, the image quality of a blood flow image can be improved. In particular, unnecessary components or residual unnecessary signals included in the speed signal can be effectively removed.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments of the invention will be described with reference to the drawings.

  FIG. 1 shows a preferred embodiment of an ultrasonic diagnostic apparatus according to the present invention, and FIG. 1 is a block diagram showing the overall configuration thereof. This ultrasonic diagnostic apparatus is an apparatus having a function of extracting Doppler information based on a received signal obtained by transmission / reception of an ultrasonic wave and forming a two-dimensional (or three-dimensional) blood flow image based on the extracted signal. .

  The probe 10 is a transducer that transmits and receives ultrasonic waves. In this embodiment, an array transducer including a plurality of transducer elements is provided in the probe 10. An ultrasonic beam is formed by the array transducer, and the ultrasonic beam is electronically scanned to form a scanning surface. Examples of the electronic scanning method include electronic linear scanning and electronic sector scanning. In order to form a blood flow image, transmission of ultrasonic pulses is generally performed a plurality of times for each beam address. A so-called 2D array transducer may be provided on the probe 10 to form a three-dimensional data capturing area. The probe 10 is generally used in contact with the body surface, but it may be inserted into a body cavity.

  The transmission / reception unit 12 functions as a transmission beam former and a reception beam former. That is, the transmission / reception unit 12 supplies a plurality of transmission signals to the plurality of vibration elements with a predetermined delay relationship at the time of transmission. As a result, a transmission beam is formed. On the other hand, reflected waves from the body are received by a plurality of vibration elements, and a plurality of reception signals obtained thereby are input to the transmission / reception unit 12. The transmission / reception unit 12 applies a phasing addition process to these reception signals, thereby obtaining a reception signal after phasing addition. That is, a reception beam is electronically formed by such a phasing addition process. The transmission / reception unit 12 includes an A / D conversion unit that samples a received signal.

  The quadrature detection unit 14 has a function of converting an input received signal into a complex signal. In the present embodiment, the quadrature detection unit 14 includes a pair of mixer circuits that mix a reference signal with a received signal. Of course, various circuit configurations can be employed as long as the received signal can be converted into a complex signal. The received signal (complex signal) after quadrature detection is input to the MTI filter unit 16. The MTI filter unit 16 includes an MTI filter for a real part and an MTI filter for an imaginary part, and removes a low-speed moving body component (clutter) included in the received signal. That is, the MTI filter unit 16 functions as a complex wall motion filter. Incidentally, when imaging not a blood flow but a moving tissue such as a heart wall, a received signal that does not pass through the MTI filter 16 is input to the speed calculation unit 18 at the subsequent stage.

  The speed calculation unit 18 includes an autocorrelation calculator and a speed calculator. As is well known, the autocorrelation calculator performs an autocorrelation calculation between a plurality of temporally adjacent received signals obtained on the same beam address. The autocorrelation result obtained thereby is input to a velocity calculator, and a velocity value (average flow velocity) for the blood flow is obtained from the calculation result. Specifically, velocity values are obtained for each sample point, and they constitute a velocity signal. In addition to the speed value calculation function, the speed calculation unit 18 may include a function for calculating power, a function for calculating a variance value (speed variance value on the time axis for each sample point), and the like.

  The noise processing unit 20 is a circuit for removing noise on the white noise included in the speed signal. The residual clutter component that has not been removed by the MTI filter unit 16 is also removed by the noise processing unit 20. The noise processing unit 20 is configured, for example, as a circuit that removes a noise level signal by comparing a power value with a certain threshold value, or an unnecessary signal according to a combination of a plurality of information such as a speed value, a power value, and a variance value. It is configured as a circuit to be removed. For example, you may utilize the circuit hung up in said patent document 1-patent document 5.

  Originally, all of the clutter components and noise components included in the received signal should be removed by the MTI filter unit 16 and the noise processing unit 20 described above. However, there are unnecessary components. The unnecessary components (residual unnecessary components) include residual clutter components that are not removed by the MTI filter unit 16 and the noise processing unit 20, white noise-like residual noise components that are not removed by the noise processing unit 20, and the like. It is a waste. If such a residual unnecessary component is included in the velocity signal, the image quality is deteriorated when a blood flow image is formed. Therefore, effective removal thereof is desired. Therefore, the residual unnecessary component processing unit 22 is provided in the present embodiment.

  More specifically, the velocity value vel output from the noise processing unit 20 is output to the ternarization unit 28 and the removal unit 32. In the present embodiment, the ternary unit 28 sets vel ′ = + 1 when vel> 0, sets vel ′ = − 1 when vel <0, and sets the attribute value vel ′ when vel = 0. = 0. That is, the velocity value vel is standardized as a pre-processing for the subsequent correlation value calculation, and the attribute value vel 'is obtained for each sample point. Such pre-processing can simplify subsequent correlation calculations, and can effectively discriminate blood flow components and unwanted signal components based on their spatial properties.

  The correlation value calculation unit 30 sets a region of interest around a sample point of interest on a frame corresponding to the scanning plane, and sets a reference region as a region of the same shape that is shifted in a certain direction. Then, correlation value calculation, which will be described in detail later, is performed between the attention area and the reference area, and the correlation value R that is the calculation result is output to the removal unit 32 as an evaluation value.

  A correlation value R is obtained for each sample point on the frame and is output to the removal unit 32. In order to perform such a correlation value calculation, a line memory or a frame memory is provided between the ternarization unit 28 and the correlation value calculation unit 30 as necessary. The specific operation of the correlation value calculation unit 30 will be described in detail later.

The removal unit 32 determines whether the velocity value of each sample point is a blood flow component or a residual unnecessary component, and executes a process of removing the residual unnecessary component. Specifically, as will be described in detail later, the two-dimensional threshold determination is performed using the threshold V _th set for the velocity value vel and the threshold R _th set for the correlation value R. By doing so, the blood flow component and the residual unnecessary component are discriminated, and the residual unnecessary component is removed based on the discrimination result. When residual unnecessary components are removed, dummy data is inserted as necessary. Such insertion of dummy data may be performed as an operation of the display processing unit 24 described below.

  In any case, a certain amount of clutter component removal and noise component removal has been achieved by the action of the MTI filter unit 16 and the noise processing unit 20, but by providing the residual unnecessary component processing unit 22 as described above, It is possible to effectively remove unnecessary components and form a high-quality two-dimensional blood flow image. According to experiments by the present inventors, it has been confirmed that the image quality of a two-dimensional blood flow image can be significantly improved. That is, in this embodiment, since the difference in the spatial characteristics of the blood flow component and the residual unnecessary component is used, unnecessary components are removed from a viewpoint different from the conventional clutter processing and noise processing, so that only two steps are unnecessary. More effective removal of unnecessary components can be achieved than when components are removed.

  The display processing unit 24 includes a digital scan converter (DSC) in this embodiment. The DSC has coordinate conversion and interpolation processing functions. A two-dimensional blood flow image is formed based on the velocity signal output from the residual unnecessary component processing unit 22 by the display processing unit 24. In this case, the data lost by the removal of the residual unnecessary signal is supplemented by the interpolation value as necessary. A blood flow image is displayed on the display unit 26.

  Although not shown in FIG. 1, a two-dimensional tomographic image forming unit is provided to display a two-dimensional tomographic image together with the two-dimensional blood flow image. In the above embodiment, the residual unnecessary component processing unit 22 is provided after the MTI filter unit 16 and the noise processing unit 20, but even when one or both of the MTI filter unit 16 and the noise processing unit 20 are not provided. The configuration can be adopted, and a certain effect can be obtained even in such a case.

The operation of the correlation value calculation unit 30 will be described in detail below. As described above, the correlation value calculation unit 30 uses the correlation value (or a value corresponding to it) as an evaluation value of randomness based on the set of attribute values vel ′ after ternarization processing (one-dimensional array in this embodiment). Is calculated. Specifically, W1 in FIG. 2 indicates a one-dimensional region of interest that spreads evenly up and down on the beam around the sample point j of interest, and the size in the vertical direction (beam direction) is N. . W1 ′ in FIG. 2 indicates a reference area defined by shifting the attention area W1 by n in the vertical direction. Here, n is an integer (number of pixels) of 1 or more. For example, n is 1, but the value may be variably set according to the situation. A correlation value (evaluation value) described below is executed between the attention area W1 and the reference area W1 ′. Here, if the correlation coefficient (autocorrelation coefficient) between the attention area W1 and the reference area W1 ′ is R _j (n), it is defined by the following equation (1).

Since the spatial distribution of the velocity values for the residual unnecessary component is highly random as described above, the correlation coefficient R _j (n) between the attention area W1 and the reference area W1 ′ is larger than that of the blood flow component. Get smaller. Using this property, it can be recognized that there is a high possibility of being a residual unnecessary component when the correlation coefficient R _j (n) of each sample point is equal to or less than the threshold value R _th . However, there is an absolute value of the velocity value vel of the sample point of interest in order to prevent the mosaic blood flow part from being unnecessarily excluded as an unnecessary component due to the so-called folding phenomenon in signal processing. If it is higher than the threshold value V _th, it is excluded from the removal target. A combination of the above two conditions is shown in FIG. 3, where the horizontal axis indicates the velocity value and the vertical axis indicates the correlation value. A hatched region 100 is shown as a range in which residual unnecessary components are removed.

  The above processing is executed for each sample point (or pixel point) constituting the frame, and a blood flow image can be formed by using information from which residual unnecessary components contained in the frame are effectively removed. It becomes. Incidentally, after removing unnecessary residual components, another dummy data may be supplemented by interpolation processing. Such an interpolation process can be left to the conversion process in the digital scan converter.

Instead of the above formula (1), the following formula (2) or formula (3) can also be used. Strictly speaking, these expressions are not arithmetic expressions for obtaining correlation values, but are expressions that can obtain equivalent values.

If it is possible to obtain a correlation between the attention area W1 and the reference area W1 ′, a calculation formula other than the above can be used. Furthermore, it is good also as what is shown to (4) Formula below _Rj (0) in said (2) Formula and (3) Formula.

When the above equation (2) is used, the same judgment conditions as those shown in FIG. 3 can be used. When the above equation (3) is used, the signal is highly random. Since R _j (n) increases, determination conditions as shown in FIG. 4 are used. In FIG. 4, the horizontal axis indicates the speed value, and the vertical axis indicates the coefficient. When the coefficient R _j (n) is equal to or greater than the threshold value R _th and the absolute value of the velocity value vel is equal to or less than the threshold value V _th, it is determined as an unnecessary component. This is shown as hatched area 102. The velocity value of the sample point corresponding to the region 102 is removed (corrected to zero), and the velocity value of the sample point corresponding to the other region is stored as it is.

  In the above, the attention area and the reference area are one-dimensional areas along the beam direction. However, a one-dimensional attention area and a reference area can be set in the beam scanning direction, and will be described below. A two-dimensional attention area and reference area can also be set. In FIG. 5, a region of interest W2 is defined around the sample point P of interest, and a reference region W2 'having the same form is defined as a region shifted by m in the horizontal direction and n in the vertical direction. Here, m and n are both integers of 1 or more, and B indicates a beam line (sound ray). In FIG. 6, the attention area W3 and a reference area W3 ′ shifted by m in the horizontal direction are defined, and in FIG. 7, the attention area W4 and the reference area W4 shifted by n in the vertical direction are defined. 'And are defined. Here, m is an integer of 1 or more, and n is an integer of 1 or more. In this way, the correlation value can be calculated using the shift of the two-dimensional region.

Here, the correlation coefficient R _{i, j} (m, n) in the case of FIG. 5 is obtained as in the following equation (5), where the size of the region is M × N. This corresponds to the above equation (1).

Similarly, the expressions corresponding to the expressions (2) and (3) are as follows.

Even in this case, R _{i, j} (0,0) included in the equations (7) and (8) can be replaced as follows.

  As described above, according to the present embodiment, it is possible to effectively remove residual unnecessary components that have not been removed by the MTI filter unit 16 and the noise processing unit 20 and to improve the image quality of the two-dimensional blood flow image. is there. That is, focusing on the spatial properties of the residual unnecessary component, it can be accurately distinguished from the blood flow component, and the residual unnecessary component can be accurately excluded from the speed signal. Incidentally, in the standardization processing in the ternarization unit 28, binarization processing, quaternization processing, etc. can be adopted instead of the ternarization processing. However, from the viewpoint of discriminating residual unnecessary components, the calculation is simplified. From the viewpoint of conversion, it is desirable to perform ternary processing. In addition, as a calculation formula employed in the correlation value calculation unit 30, calculation formulas other than the calculation formulas described above may be employed as long as spatial randomness can be evaluated.

1 is a block diagram showing an overall configuration of an ultrasonic diagnostic apparatus according to the present invention. It is a figure which shows a one-dimensional attention area and a reference area. It is a figure which shows an example of an unnecessary signal determination condition. It is a figure which shows the other example of unnecessary signal determination conditions. It is a figure which shows the two-dimensional attention area | region and reference area | region which have the relationship shifted to the horizontal direction and the vertical direction. It is a figure which shows the two-dimensional attention area | region and reference area | region which have the relationship shifted to the horizontal direction. It is a figure which shows the two-dimensional attention area | region and reference area | region which have the relationship shifted to the perpendicular direction.

Explanation of symbols

16 MTI filter section, 20 noise processing section, 22 residual unnecessary component processing section, 28
Trinization unit, 30 correlation value calculation unit, 32 removal unit.

Claims (10)

Based on a received signal obtained by transmitting and receiving ultrasonic waves, speed calculating means for calculating a speed value of each sample point;
A ternarization means for ternarizing the velocity value of each sample point and obtaining an attribute value for each sample point;
Based on the spatial attribute value array after the ternarization processing, a randomness evaluation calculation is performed for evaluating spatial randomness for a region of interest set with reference to each sample point, and An evaluation means for obtaining an evaluation value for each sample point;
Based on the evaluation value for each sample point, a removal unit that determines whether the velocity value of each sample point is a blood flow component or an unnecessary component, and executes processing for removing the unnecessary component;
Blood flow image forming means for forming a blood flow image based on a blood flow component after executing the process of removing the unnecessary signal;
Only including,
The ultrasonic diagnostic apparatus , wherein the evaluation unit executes the randomness evaluation calculation between the region of interest and a reference region obtained by spatially shifting the region of interest . The apparatus of claim 1.
In the ternary processing, a positive attribute value is assigned when the velocity value of each sample point satisfies the first condition, and a zero attribute value is assigned when the velocity value of each sample point satisfies the second condition. The ultrasonic diagnostic apparatus is characterized in that a negative attribute value is given when the velocity value of each sample point satisfies the third condition. The apparatus of claim 1.
An ultrasonic diagnostic apparatus comprising: means for variably setting a shift amount of the reference area from the attention area . Based on the received signal obtained by transmitting and receiving ultrasonic waves, speed calculation means for calculating the speed value of each sample point,
A ternarization means for ternarizing the velocity value of each sample point and obtaining an attribute value for each sample point;
Based on the spatial attribute value array after the ternarization processing, a randomness evaluation calculation is performed for evaluating spatial randomness for a region of interest set with each sample point as a reference, An evaluation means for obtaining an evaluation value for each sample point;
Based on the evaluation value for each sample point, a removal unit that determines whether the velocity value of each sample point is a blood flow component or an unnecessary component, and executes processing for removing the unnecessary component;
Blood flow image forming means for forming a blood flow image based on a blood flow component after executing the process of removing the unnecessary signal;
Including
The randomness evaluation calculation corresponds to a correlation calculation,
The ultrasonic diagnostic apparatus, wherein the evaluation value corresponds to a correlation value. The apparatus of claim 3.
The region of interest is a one-dimensional region along the beam direction;
The ultrasonic diagnostic apparatus, wherein the reference region is a region obtained by shifting the region of interest in a beam direction. The apparatus of claim 3.
The region of interest is a two-dimensional region on a frame;
The ultrasonic diagnostic apparatus, wherein the reference region is a region obtained by shifting the region of interest on a frame. Based on a received signal obtained by transmitting and receiving ultrasonic waves, speed calculating means for calculating a speed value of each sample point;
A ternarization means for ternarizing the velocity value of each sample point and obtaining an attribute value for each sample point;
Based on the spatial attribute value array after the ternarization processing, a randomness evaluation calculation is performed for evaluating spatial randomness for a region of interest set with reference to each sample point, and An evaluation means for obtaining an evaluation value for each sample point;
Based on the evaluation value for each sample point, a removal unit that determines whether the velocity value of each sample point is a blood flow component or an unnecessary component, and executes processing for removing the unnecessary component;
Blood flow image forming means for forming a blood flow image based on a blood flow component after executing the process of removing the unnecessary signal;
Including
The removing means is a blood flow component or an unnecessary component for each sample point based on a combination of a velocity value of the sample point and an evaluation value calculated for the sample point. An ultrasonic diagnostic apparatus characterized by determining whether or not. The apparatus of claim 7.
The ultrasonic diagnostic apparatus according to claim 1, wherein the removing unit determines that the velocity value satisfies a first determination condition and the evaluation value is an unnecessary component when the evaluation value satisfies a second determination condition. A clutter component removing means for removing clutter components contained in a received signal obtained by transmitting and receiving ultrasonic waves;
Based on the received signal after removal of the clutter component, speed calculation means for calculating the speed value of each sample point;
Noise component removing means for removing a noise component contained in a velocity signal constituted by velocity values for the respective sample points;
Attribute value calculation means for obtaining an attribute value for each sample point based on the velocity value of each sample point;
Based on the spatial attribute value array after the attribute value calculation, a randomness evaluation calculation is performed to evaluate spatial randomness for a region of interest set based on each sample point, and each sample An evaluation means for obtaining an evaluation value for each point;
Based on the velocity value and the evaluation value for each sample point, it is determined whether the velocity value of each sample point is a blood flow component or a residual unnecessary component, and a residual is executed to remove the residual unnecessary component Unnecessary component removing means;
Blood flow image forming means for forming a blood flow image based on a blood flow component after executing the process of removing the residual unnecessary component;
Only including,
The ultrasonic diagnostic apparatus , wherein the evaluation unit performs the randomness evaluation calculation corresponding to a correlation calculation between the attention area and a reference area obtained by spatially shifting the attention area . The apparatus of claim 9.
The attribute value calculation means gives a positive attribute value when the velocity value of each sample point satisfies the first condition, and gives a zero attribute value when the velocity value of each sample point satisfies the second condition. The ultrasonic diagnostic apparatus is a ternary processing means for giving a negative attribute value when the velocity value of each sample point satisfies the third condition.

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