JP2002177273A - Ultrasonic diagnostic device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To carry out high performance and high speed pattern matching by eliminating or restraining an arch fact contained in a receiving signal from an organism. SOLUTION: An ultrasonic diagnostic device provides a receiving signal corresponding to an ultrasonic reflective signal in accordance with probing by periodically carrying out the two-dimensional or three-dimensional proving on a diagnoding portion of a subject by a ultrasonic signal. This device has at least one of a fixed echo remover 15 to remove a fixed echo component of small fluctuation in time series from a frame of the receiving signal provided by the probing and a band pass filter 21 to extract a higher harmonic component from the receiving signal. Additionally, this device is furnished with a special microcomputer 16 to compute two-dimensional distributed information of specially small quantity (for example, cross-correlation coefficient) to express mutual similarity of a local region in a space region respectively formed of the receiving signals of the two frames different from each other in timing of the probing which are the receiving signals processed by this remover 15 and/or the filter 21.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an ultrasonic diagnostic apparatus, and more particularly to an ultrasonic diagnostic apparatus having a function of performing a high-performance time-series cross-correlation operation on a three-dimensional local area.

[0002]

2. Description of the Related Art An ultrasonic diagnostic apparatus is an apparatus that obtains an image from a received signal obtained by transmitting and receiving an ultrasonic signal to and from a subject, and utilizes various noninvasive ultrasonic signals. Used in embodiments. Although there are various types of ultrasonic diagnostic apparatuses, the mainstream is an apparatus that performs imaging to obtain a tomographic image of a soft tissue of a living body using an ultrasonic pulse reflection method.

In particular, in recent years, this ultrasonic diagnostic apparatus has been remarkably developed, and various arithmetic functions effective for clinical use have become rich. One of them is provided with a function of calculating a time-series similarity between two-dimensional or three-dimensional local regions, that is, a so-called pattern matching function.

As a function of the pattern matching, for example, a function described in Japanese Patent Application Laid-Open No. 8-164139 is known. According to the ultrasonic diagnostic apparatus described in this publication, the reception signal output from the reception beamformer is received separately from the system for generating the image data of the tomographic image, and the kernel ROI of the first frame and the object of the second frame are received. There is provided arithmetic means for obtaining two-dimensional distribution information of a feature quantity (for example, a cross-correlation coefficient) representing the similarity between the received signal and the ROI. Thus, for example, the degree of myocardial deformation can be quantified between two frames with different cardiac phases and represented as an image, and this image can be displayed in parallel with or superimposed on the tomographic image.

[0005]

However, the function of the pattern matching provided in the ultrasonic diagnostic apparatus described in the above-mentioned publication is to perform a phasing addition process on a reception signal received by a probe by a reception beamformer, Since this function was used to calculate time-series features using signals, the received signal containing various artifact components from the living body was directly used for pattern matching calculation, and the performance of this calculation often deteriorated. Was.

For example, when there is a fixed reflector such as a chest wall at a short distance or an artifact of a fixed echo caused by multiple reflections at the same, the correlation coefficient between frames of the received signal always becomes a high value. This hinders the evaluation of distance myocardium (a typical case is when an external apical approach is performed on the apex). In particular, the apex is also a site that is easily affected by all three main coronary arteries (the left coronary artery, the right coronary artery, and the circumflex branch), and is associated with ischemic heart disease and its complications such as mural thrombus. Despite being an important part for diagnosis, fixed echo artifacts are likely to occur.

Further, in the ultrasonic diagnostic apparatus described in the above-mentioned publication, evaluation based on a tomographic image is mainly performed. Therefore, when a body motion occurs in a direction perpendicular to the tomographic plane, even if pattern matching is performed, a time series is obtained. There is a problem that similarity cannot be accurately evaluated.

In order to solve the problem of inaccuracy of the similarity evaluation, it is desired to perform three-dimensional pattern matching (evaluation). However, there is also a problem that the amount of calculation (calculation time) becomes enormous, and high-speed processing cannot be performed.

Further, in the case of the ultrasonic diagnostic apparatus described in the above-mentioned publication, pattern matching is only performed and the result is merely displayed as an image. There was a request to enhance the display function for visually monitoring.

The present invention is intended to overcome the reality of such conventional pattern matching, and eliminates artifacts contained in a received signal from a living body and the effect of body movement in a direction perpendicular to a tomographic plane. Or high performance with suppression,
In addition, to provide an ultrasonic diagnostic apparatus having a pattern matching function that can perform high-speed processing with a small amount of calculation,
One of the purposes.

Another object of the present invention is to provide a method for visually monitoring the movement of a site of interest in an organ with a simple operation simultaneously or separately with the above-mentioned object.

[0012]

In order to achieve the above-mentioned object, an ultrasonic diagnostic apparatus according to the present invention, as one aspect, performs two-dimensional or three-dimensional scanning of a diagnostic part of a subject with an ultrasonic signal. It is an ultrasonic diagnostic apparatus that performs periodically and obtains a reception signal of an electric quantity corresponding to the ultrasonic reflection signal accompanying this scanning, and a component having little variation in time series from the set of the reception signals obtained by the scanning. A preprocessing means having at least one of a means for removing and a means for extracting a harmonic component from the reception signal; and two sets of reception signals processed by the preprocessing means and having different scanning timings. A feature calculation unit configured to calculate spatial distribution information of a feature indicating mutual similarity of local regions in a spatial region formed by each signal;

In another aspect of the ultrasonic diagnostic apparatus according to the present invention, scanning means for periodically performing two-dimensional or three-dimensional scanning of a diagnostic part of a subject with an ultrasonic signal, and the scanning means Signal collecting means for obtaining a received signal of an electric quantity corresponding to the ultrasonic reflected signal, and first and second signals in first and second spatial regions formed by two sets of received signals having different scanning timings, respectively. An ultrasonic diagnostic apparatus comprising: a similarity obtaining unit that obtains spatial distribution information of a feature quantity representing a similarity between local regions, wherein the similarity obtaining unit converts the first local region into the second local region. And a search range setting unit that adaptively sets a search range of the second local region to be set in the second spatial region when the feature amount is obtained in light of the local region.

[0014] For example, the similarity acquiring means is configured to execute the second
A feature amount calculating means for moving the local area within the search range and calculating the feature quantity for each movement, and a representative value selecting means for selecting one representative value from the one or more feature quantities. And a repetition means for moving the first local area in the first space area, and for making the calculation means and the selection means function each time the first local area is moved.

Preferably, the search range setting means includes vector information between the first local region in the past time phase and the search range and the first information in the current time phase.
Means for adaptively setting the center coordinates and the size of the search range using at least one of the vector information between the local region and the search range.

Further, the feature quantity calculating means may be configured to control the first
Means for calculating the absolute value sum (SAD) of the mutual difference between the signal values of the second local region and the second local region, and a cross-correlation coefficient of the signal value as the feature value at the moving vector position May be provided.

Further, an ultrasonic diagnostic apparatus according to the present invention
As still another aspect, a scanning unit that periodically performs two-dimensional or three-dimensional scanning of a diagnostic portion of a subject with an ultrasonic signal and a reception signal of an electric quantity corresponding to an ultrasonic reflection signal accompanying the scanning are obtained. A two-dimensional distribution of a signal amount indicating a similarity between the first and second local regions in the first and second spatial regions formed by the two sets of reception signals having different scanning timings from each other. An ultrasound diagnostic apparatus including a similarity acquisition unit that seeks information, wherein the similarity acquisition unit includes:
Means for calculating a sum of absolute values (SAD) of mutual differences between signal values in the first and second spatial regions to obtain a movement vector position; Means for determining a correlation coefficient.

Further, an ultrasonic diagnostic apparatus according to the present invention
As still another aspect, a scanning unit that periodically performs two-dimensional or three-dimensional scanning of a diagnostic portion of a subject with an ultrasonic signal and a reception signal of an electric quantity corresponding to an ultrasonic reflection signal accompanying the scanning are obtained. An ultrasonic diagnostic apparatus comprising signal collection means, wherein at least one position of interest is located in a space area of a desired initial time phase among spatial areas formed by a plurality of sets of reception signals having different scan time phases. Initial interest position designation means for designating, and processing for obtaining a movement vector indicating a movement destination in the space area of the next time phase of this interest position, up to the space area of the last time phase every time the interest position is moved to the movement destination And a trajectory display means for displaying the movement vector as spatio-temporal trajectory information of the position of interest.

Here, the trajectory display means may be, for example, means for identifying and displaying the magnitude of the movement vector in each of the time phases, or by associating the movement vector in each of the time phases with a cardiac cycle. This is a means for displaying.

Further, the spatial value of the feature quantity representing the similarity between the first and second local regions in the first and second spatial regions formed by the two sets of received signals having different scanning phases from each other. And a similarity acquisition unit that obtains accurate distribution information.

[0021]

Embodiments of the present invention will be described below with reference to the accompanying drawings.

(First Embodiment) Referring to FIG.
An ultrasonic diagnostic apparatus according to the embodiment will be described.

This ultrasonic diagnostic apparatus will be described by employing a sector electronic scanning method which has a narrow shallow visual field and a wide deep visual field, which is suitable for heart diagnosis, but can scan a two-dimensional or three-dimensional region of a subject. If so, a linear electronic scanning method or a convex electronic scanning method may be employed.

The ultrasonic diagnostic apparatus includes an ultrasonic probe (hereinafter, simply referred to as a “probe”) 11. The probe 11 is provided with a vibrator array for sector scanning in which a plurality of vibrators for reversibly converting an acoustic signal and an electric signal are arranged at its tip. The probe 11 is electrically connected to the transmission system 12 during transmission, and is electrically connected to the reception beamformer 13 during reception.

Although not shown, the transmission system 12 has a clock generator, a rate pulse generator, and a delay circuit and a pulsar provided for each transducer (for each channel). The clock generator generates clock pulses, which are sent to a rate pulse generator. The rate pulse generator divides the clock pulse into, for example, a 5 kHz rate pulse. The rate pulse is distributed for each channel, sent to each delay circuit, and subjected to delay processing for a desired time. That is, each delay circuit gives the rate pulse a delay time necessary to focus the ultrasonic wave into a beam and determine the direction of the ultrasonic beam (called the scanning line direction or the azimuth direction).

The delayed rate pulse is sent to the pulser for each channel. As a result, the pulser applies a pulse voltage to the corresponding vibrator at the reception timing. Thereby, the ultrasonic pulse is emitted from the probe 11 in the azimuth direction corresponding to the delay time.

The radiated ultrasonic pulse is partially reflected at the boundary of the acoustic impedance in the subject and becomes a reflected wave. This reflected wave is received by the transducer of the probe 11, converted into an electric signal, and taken into the reception beam former 13.

The receiving beamformer 13 has a
It is constituted by a digital beamformer system as shown in US Pat. This receiving beamformer 13
It has a preamplifier, an A / D converter, a digital delay circuit, and an adder (not shown). The analog reception signal transmitted from the vibrator for each channel is amplified by a preamplifier, converted to a digital signal by an A / D converter, and transmitted to a digital delay circuit. In this circuit, in order to obtain reception directivity, a delay time opposite to that at the time of transmission is given for each channel, and then added by an adder. Hereinafter, the added digital signal is referred to as a reception signal.

By sequentially controlling the above-described delay time at the time of transmission and reception for each repetition of the ultrasonic pulse, a two-dimensional area of the subject can be sector-scanned to obtain one frame (one set) of reception signals. it can. Further, by repeating such sector scanning periodically, it is possible to obtain received signals of a plurality of time-series frames.

On the output side of the receiving beam former 13, a signal processor 14, a fixed echo remover 15 and a feature calculator 16 are provided in parallel as shown in the figure.

For this reason, the reception signal generated by the reception beam former 13 is sent to the signal processor 14 as one of the transmission destinations. Therefore, the received signal is transmitted to the signal processor 1
In step 4, it is detected and logarithmically amplified to generate B-mode image (tissue tomographic image) data. This image data is sent to a DSC (digital scan converter) 17.

The reception signal generated by the reception beam former 13 is also sent to the fixed echo canceller 15.
The remover 15 is composed of a time-series HPF including a plurality of frame memories, a plurality of multipliers, a multiplication coefficient ROM, an adder, and a filter controller, as described in, for example, Japanese Patent Application Laid-Open No. 8-107896. . This allows
The time series HPF is formed in an inter-frame HPF filter,
It has a cutoff frequency that removes fixed echo components and passes other signal echo components from the signal value of the received signal at the same position in each frame.

For this reason, the fixed echo remover 15 eliminates or almost neglects the fixed echo component of the stationary part with no motion from the received signal, and generates a received signal consisting mostly of the signal echo component. This received signal is sent to the next-stage feature value calculator 16.

The feature value calculator 16 is disclosed in, for example,
64139. The arithmetic unit 16 includes a plurality of frame memories capable of writing at least two frames of reception signals having different scanning time phases (timings) on a tomographic plane, and two frames of different time phases read from the frame memories. And an arithmetic unit for performing pattern matching.

Specifically, the arithmetic unit executes the kernel ROI designated in the spatial region consisting of the received signal of one frame.
A feature calculator for calculating a feature (eg, a cross-correlation coefficient or SAD) indicating a similarity between the (local region) and an object ROI (local region) in a spatial region including a received signal of another frame. It consists of. Object RO
I is moved within a predetermined search ROI, and the feature amount is calculated each time the I is moved. Therefore, since a plurality of feature values are calculated for one kernel ROI, a representative value of the feature value (for example, the maximum value of the cross-correlation coefficient) is selected from these, and similarity information for the kernel ROI is selected. Is stored as

Next, the kernel ROI is moved to an adjacent position on the set space area, and a representative value of the characteristic amount is obtained as described above. Therefore, by changing the position of the kernel ROI and obtaining a representative value of the characteristic amount at each position, two-dimensional distribution information of the characteristic amount can be obtained. The two-dimensional distribution information of the feature amount is converted into image data and sent to the DSC 17.

The DSC 17 receives the image data of the tomographic image from the signal processor 14 and the image data of the characteristic amount from the characteristic amount calculator 16. Therefore, DSC17
Converts a scan format into a standard TV system and converts both image data into, for example, Japanese Patent Application Laid-Open No. 8-164413.
The image data is combined with one frame of image data in a display mode such as overlapping or juxtaposed as exemplified in No. 9.

The composite image data is read out at a predetermined timing for each frame and sent to the display 18. The display 18 converts the composite image data into an analog signal and displays the analog signal on a monitor screen. Thus, the B-mode tomographic image and the feature amount image as the pattern matching result are displayed on the monitor screen in an appropriate mode.

According to the present embodiment, the fixed echo remover 15 is provided before the feature calculator 16 to reliably remove or suppress the fixed echo from the stationary part before the feature calculation, ie, pattern matching. Is done. That is, most of the received signals used for pattern matching are only signal components from moving parts.

That is, when performing myocardial pattern matching, artifacts such as fixed echoes from a fixed reflector such as a chest wall at a short distance and fixed echoes due to multiple reflections are reliably removed in advance. Also, when diagnosing the apex, this artifact is reliably removed. Therefore, in particular, the performance of the myocardial evaluation at a short distance and the myocardial evaluation of the apex can be remarkably improved as compared with the related art.

In the related art, since the correlation is high in the stationary phase of the wall motion of the myocardium, the signal value is enhanced even in a normal part, which may hinder the evaluation.
However, in the present embodiment, due to the fixed echo pre-removal, a signal component having a high correlation due to no movement even in such a normal part is previously removed as a fixed echo. Therefore, the case where the signal of the normal part is enhanced is reduced. Therefore, conversely, only in the phase of the myocardium moving during the cardiac cycle (early contraction, early diastole), a highly correlated portion (often abnormal in terms of myocardial function) is enhanced. Thus, there is also an advantage that when imaging the myocardium, a specific site where wall motion is abnormal can be selectively provided.

(Second Embodiment) Referring to FIG.
An ultrasonic diagnostic apparatus according to the embodiment will be described. The same components as those in the first embodiment are denoted by the same reference numerals, and the description thereof will be omitted or simplified.

As in the first embodiment, this ultrasonic diagnostic apparatus is characterized in that it eliminates or suppresses artifacts in the received signal sent to the feature value calculator 16. In this embodiment, a technique called tissue harmonic imaging (THI) is used to realize such features.

Specifically, as shown in FIG.
A band-pass filter (BPF) 21 which is a main element for performing tissue harmonic imaging is inserted in a reception path between the reception beam former 1 and the reception beam former 13. The filter 21 includes an A / D converter and a filter circuit (not shown), and receives an echo signal of the electric quantity received by the probe 11. The echo signal may be first preamplified by a preamplifier and then sent to the bandpass filter 21.

In the band pass filter 21, the echo signal is converted into a digital signal by an A / D converter and sent to a filter circuit. The filter circuit is configured to perform band-pass filtering for extracting only a signal component of a predetermined band centered on an integer multiple of the center frequency f ₀ of the transmission ultrasonic wave, here, for example, a double harmonic frequency. The extracted harmonic signal is sent to the reception beam former 13, and a digital reception signal based on the harmonic signal is generated as described above. That is, the received signal based on the harmonic signal is the first signal.
In the same manner as in the first embodiment, the signal is sent to the signal processor 14 for generating a B-mode tomogram and the feature value calculator 16 for performing pattern matching, and is processed in the same manner as described above.

As described above, according to the present embodiment, a harmonic signal is extracted from an echo signal at the first stage of reception. That is, after this extraction, generation and display of a B-mode tomographic image and a feature image (pattern matching) to which tissue harmonic imaging is applied are performed. According to tissue harmonic imaging, the extraction of the harmonic component makes the received beam extremely sharp and narrow, so the artifact removal effect and the visibility of the myocardium and intima are superior to those using the fundamental component. ing.

Therefore, the artifact component contained in the received signal based on the harmonic signal is greatly reduced.
Pattern matching is performed with higher accuracy using the received signal. In general, similarity cannot be accurately evaluated unless a signal of sufficient intensity is obtained from the myocardial part to be evaluated.However, according to the present embodiment, the use of a harmonic signal makes it possible to evaluate the similarity from the myocardial part. Since a received signal with excellent visibility can be obtained, the similarity evaluation accuracy is also improved from this point.

Further, by using the tissue harmonic imaging together, the influence of individual differences in image quality is reduced, and the similarity can be evaluated with higher accuracy for more patients.

The tissue harmonic imaging as a pre-process of the pattern matching is not necessarily limited to the above-described filter method using the band-pass filter 21, but is performed based on an echo signal including a fundamental component and a harmonic component. It is sufficient that the harmonic components can be extracted. For example, a pulse inversion method may be used.

In the configuration shown in FIG.
Is to suppress or remove the fundamental wave component of the transmission ultrasonic wave by, for example, resonating or cutting it off, generate a drive pulse mostly based only on the harmonic component of the transmission ultrasonic wave, and supply the drive pulse to the probe 11. Can be. With this configuration, since the transmitted wave is a harmonic signal, the side lobe of the transmitted ultrasonic wave is significantly reduced, and the biological artifact due to the side lobe is reduced accordingly, so that pattern matching can be performed with higher accuracy. It can be carried out.

Further, FIG. 3 shows a combination of the above-described fixed echo removal method (the configuration of FIG. 1) according to the first embodiment and the tissue harmonic imaging method (the configuration of FIG. 2) according to the second embodiment. 1 shows an example of an ultrasonic diagnostic apparatus.

When only the tissue harmonic imaging method is used, fixed artifacts due to multiple reflections generated by a fixed reflector such as a close chest wall may remain. However, as described above, by also using the fixed echo removal method, the fixed echo that may not be removed by the tissue harmonic imaging method alone is also removed. And the similarity can be evaluated with high accuracy and stability.

(Third Embodiment) Referring to FIGS. 4 to 7,
An ultrasonic diagnostic apparatus according to a third embodiment of the present invention will be described.

The purpose of this ultrasonic diagnostic apparatus is to calculate a characteristic amount representing similarity between local regions, that is, to speed up pattern matching. As an outline of this pattern matching, the local spatiotemporal continuity of the movement of the living body is assumed, and the motion vector at the stationary phase and the stationary part, that is, the search area of the best match is made as small as possible to achieve high distance. It becomes something. At least one or both of the information of the "past motion vector amount" and the "movement vector amount of the adjacent point which has already been calculated" for the calculation position where the matching is performed is effectively used.

In this ultrasonic diagnostic apparatus, a pattern matching process described below is executed, and this process is also suitably executed in any one of the feature quantity calculators 16 shown in FIGS.

Of course, this pattern matching process
In an ultrasonic diagnostic apparatus other than those described in FIGS. 1 to 3, for example, an ultrasonic diagnostic apparatus described in JP-A-8-164139, the processing may be executed in place of the pattern matching process described in the publication.

The feature value calculator 1 according to any one of FIGS.
6, a plurality of frame memories 31A to 31A, as shown in FIG.
31N, a processor 32 for calculating the feature quantity, a calculation result (for example, a cross-correlation coefficient at each calculation position) of this processor 32 and calculation information in the middle (for example, a calculation for calculating the cross-correlation coefficient at each calculation position) And a memory 33 for storing the signal power value of the signal. Various kinds of designation information are sent from the controller 34 to the arithmetic unit 16. The controller 34 is further connected to the controller 35, and operation information provided by the operator via the controller 35 is sent to the controller 34.

The controller 34 stores information specifying two different time phases desired by the operator in the frame memories 31A to 31A.
In addition to sending the information to the processor 31N and the processor 32, the processor 32 sends information designating a method for speeding up pattern matching and information on a search range.

FIG. 5 shows a pattern matching algorithm executed by the feature quantity calculator 16.

The processor 32 of the feature calculator 16 reads two time phases L and L + 1 having different two-dimensional scanning timings instructed by the operator via the controller 34 (step S1). In response, processor 32
Are designated time phases L, L from the received signal group of a plurality of frames stored in the plurality of frame memories 31A to 31N.
Two sets of the received signals of the two-dimensional section scanned in the time phase matching +1 are read out and individually written into the work area (step S2). Note that the designated time phases L, L
The reception signals for two frames of +1 may be performed almost in real time while collecting echo signals.

As a result, in the work area of the processor 32, as schematically shown in FIGS. 6A and 6B, the first frame F of the reception signal of the first frame F in the time phase L is formed.
Of the two-dimensional section (spatial region) SC1 of the second frame F + 1 in the time phase L + 1
A two-dimensional section (space area) SC2 is constructed on the memory.

Next, the processor 32 initializes a search area specified by the operator via the controller 34 (step S3). That is, when the operator sets an ROI of a desired range on the same image while observing the B-mode tomographic image acquired at one time phase L + 1 and displayed on the display 18, the ROI information is displayed in the initial search area. Is sent to the processor 32 (see FIG. 6B).

Next, the processor 32 sets the kernel RO
I: KN _ROI is initialized and its center position (Xi, Y
i) is designated as the calculation position (step S4, FIG. 6)
(A)).

Next, the processor 32 determines the search center coordinate.
(Xc, Yc) and the size 2Xw, 2Y of the optimal search range
By adaptively (dynamically) estimating w, the specified search range
Surround SR _SPCIs set (steps S5 and S6).

(Adaptive Estimation of Search Central Coordinates) [Estimation of Search Central Coordinates (Xc, Yc)] First, an adaptive estimation process of the search central coordinates (Xc, Yc) will be described with reference to FIG. Step S5).

Now, assume that the current time phase is L, and as shown in FIG.
i, Yj) L. The movement vector vijL = (vx,
To determine vy) ijL, first, it is necessary to set the search center coordinates (Xc, Yc) ijL of the pattern matching and the search range. Assuming that the X-axis search width is 2XwijL and the Y-axis search width is 2YwijL, the search range is (Xc ± Xw,
Yc ± Yw) ijL.

In order to make the search range sufficiently small, first, it is necessary to bring the search center coordinates close to the movement vector vijL to some extent. Under these conditions, vxijL and vyij
Considering the estimation of L, the estimated values are respectively referred to as vα and vβ
Then, these estimated values can be set as follows according to various conditions.

(1) When the temporal continuity of the movement of the myocardium can be expected, the “past motion vector” (vx, v
y) An estimated value can be set using ijL-1.

(2) When spatial continuity can be expected, an estimated value can be set by using “movement vector amounts of adjacent points that have already been calculated”. The adjacent points that can be adapted to this are four peripheral points (vi-1j-1) excluding the end.
L, vij-1L, vi + ij-1L, vi-1jL)
Is preferred.

(3) Further, since spatiotemporal continuity can be expected in an actual living body, it is desirable to obtain an estimated value by averaging all such information with appropriate weighting. this,
When a movement vector using one past point and four neighboring points is expressed in a general expression, an estimated value is determined as in the following expression.

[0071]

(Equation 1)

Here, ki indicates a weighting coefficient, and Σk
i = 1 or all ki = 0 (i = 1 to 5).

In the present embodiment, the above-mentioned (1) to (3)
Can be arbitrarily selected / changed to estimate the search center coordinate value. Usually, the condition (3) is set as a default.

In the above general expression, k2
If k5 = 0 (k1 = 1), estimated values vα and vβ equivalent to the estimation under the condition (1) can be obtained, and k1
If = 0, the estimated values vα and vβ equivalent to the estimation under the condition (2) can be obtained.

The optimum apparatus conditions according to the clinical use, that is, the setting of the frame (volume) rate (the time difference between the time phases changes) and the setting of the magnitude of the calculation pitch change, so that the appropriate Preferably, a weight ki is given.

For example, for the moving amount of the moving vector,
In the case where the time phase difference is sufficiently small, the weight of k1 is increased, and in the state close to the condition of (1), and in the case of a sufficiently small operation pitch, the weight of k2 to k5 is increased. It is preferable to estimate in a state close to the condition.

In the above example, for simplicity, a single point vector is used as the past movement vector. However, the past movement vector amounts at a plurality of adjacent points are appropriately weighted, and this is used. May be used.

It is also possible to set all the coefficients ki = 0. This setting is a special case, and means that the search center coordinate is set to the calculation position. This is used in situations where the various continuities described above cannot be assumed. For example, when the received signal of the local area to be calculated is noise, the continuity cannot be assumed at the calculation position, and it is desirable that such a setting (ki = 0) can be selected. With this setting, it is possible to prevent the estimation error from becoming unnecessarily large even for noise that lowers the reliability of the motion vector calculation itself (it becomes substantially meaningless). Property can be ensured.

For determining whether or not the signal at the calculation position is noise, similarity information and intermediate information in the process of calculating similarity are used. For example, using the cross-correlation coefficient, when the absolute value of the correlation coefficient is equal to or less than a certain threshold value, it is regarded as noise, and the setting is switched to (ki = 0). Alternatively, the signal power is calculated using the power of the received signal (which occurs during the calculation of the cross-correlation coefficient. For simplicity, the denominator for normalization in the equation for calculating the cross-correlation coefficient can be used as it is). If it is less than a certain threshold value, it is regarded as noise, and the setting is switched to (ki = 0). The threshold processing may be performed by combining the cross-correlation coefficient and the signal power.

In the present embodiment, step S1 described later
2. As shown in S13, the noise determination is performed using a cross-correlation coefficient that is a calculation result at each calculation position. Thereby, when the signal value is recognized as noise, the weight coefficient ki is set to 0, and the cross-correlation coefficient is recalculated.

Probable search center coordinates (Xc, Yc) ijL = (Xi + vα, Yj + vβ) using destination coordinate values vα and vβ of the movement vector estimated in this way.
L is determined.

[Estimation of Designated Search Range] Next, an adaptive estimation process of the designated search range SR _SPC will be described with reference to FIG. 7 (step S6).

The coordinates (Xc, Y
c) Since the movement vector is searched as the best matching part centering on ijL, the smaller the search range is, the higher the calculation becomes. Unless the search range is set to be larger than the actual movement range (true value), the similarity cannot be accurately evaluated. So, the optimal search range,
That is, the values of 2XwiL and 2YwiL are estimated.

In this case as well, the spatio-temporal continuity of the movement of the living body is used, as in the estimation of the search center coordinates described above. The difference from the above is that it is necessary to estimate an “upper limit of the error” of the magnitude (movement speed) of the likely movement vector amount. So, the past movement vector

(Equation 2) Search range SR using maxV _err that maximizes
Set the _SPC as follows.

[0085]

(Equation 3)

[0086] This is because when the coefficient ka = 1, estimated coordinates v?, As the error of v?, Equivalent to expect the range of ± _{MAXV err.} Since it is necessary to allow a margin in the search range and to consider the acceleration component of the movement, the coefficient ka ≧ 1 is set to make the range slightly larger.
It is preferable to set

The optimum designated search range SR _SPC is
Various setting methods can be selectively adopted in addition to the setting method described above.

For example, the past movement vector

(Equation 4) May be set as follows using the standard deviation vsx of the x component of the vector and the standard deviation vsy of the y component (vs is a scalar quantity).

[0089]

(Equation 5)

In this case, it is preferable to set the coefficient kb ≧ 1 for the same purpose as the above-mentioned coefficient ka.

It is desirable to selectively use vector information according to clinical use. For example, in the case where temporal discontinuity is considered to be small, the past movement vector (vx, vy) ijL-1 is not used. The movement vector (vi-1j-1L,
vij-1L, vi + 1j-1L, vi-1jL).

Further, when the spatial continuity is small,
A motion vector (vx, vy) ijL-1 one time earlier,
Using (vx, vy) ijL-2 which is one time earlier,

(Equation 6) Thus, the optimum designated search range SR _SPC may be set as follows.

[0093]

(Equation 7)

Also in this case, the coefficient kc ≧
It is preferably set to 1.

In this way, an appropriate search center position and an appropriate search area size can be dynamically set.

As described above, when the designated search range SR _SPC is set as the optimal and necessary minimum range, the CPU 32 of the feature quantity calculator 16 sets the designated search range SR _SPC within the designated search range SR _{SPC as} shown in FIG. Object ROI: OB _ROI
Is set to its initial position (FIG. 5, step S7). The size of this object ROI: OB _ROI is set to be the same as that of the kernel ROI: KN _ROI .

Next, the CPU 32 determines that the kernel ROI: KN _{ROI at} the given operation position of the first frame F
And the specified object RO of the second frame F + 1
A cross-correlation coefficient is calculated as a feature representing similarity with I: OB _ROI, and the calculated value is stored in the memory 33 (step S8). The cross-correlation coefficient ρ _{m, n} is defined as follows: when the signal of the pixel value of the kernel ROI is A and that of the object ROI is B,

(Equation 8) Is calculated based on At the time of this calculation, the value of the denominator (signal power value) is also stored in the memory as intermediate information for each calculation.

Next, the CPU 32 sets the object RO
I: OB_ROISpecify search range SR _SPCAll places within
To determine whether the calculation of the cross-correlation coefficient has been completed.
Judge and specify search range SR_SPCNot finished within
Object ROI: OB_ROITo
Move and repeat the same calculation (steps S9, S1
0). Conversely, the specified search range that is set to the minimum necessary
Surround SR_SPCCoefficient calculation is completed at all calculation positions in
In some cases, the CPU 32 calculates up to that time and
From the multiple cross-correlation coefficients stored in
To select the cross-correlation coefficient having the largest value (step S
11).

Next, the CPU 32 determines whether or not the absolute value of the selected cross-correlation coefficient (maximum value) is larger than a predetermined threshold value (step S12). This determination is a process of determining whether the signal value is noise or not. When the signal value is noise, that is, when the | coefficient |> threshold value is determined, as described above, all the weight coefficients ki =
The value is set to 0, and the cross-correlation coefficient is calculated again (step S13). This determination is made as described above in the memory 3
3 may be performed based on the signal power value as the information on the way of the calculation stored in 3.

Conversely, when it is recognized that the noise is not a noise but a cross-correlation coefficient based on signal values in a normal range (step S12; NO), the CPU 32
It is determined whether or not the operation has been completed by moving the OI: KN _ROI to all the operation positions, and if there is a position where the operation has not been completed, the position of the kernel ROI: KN _ROI is updated (steps S14 and S15). ). Then, the process returns to the process of adaptively setting the designated search range SR _SPC and its size, and the above-described series of processes is executed for all desired calculation positions.

[0102] Thus, the operation at the specified search range _{SR SPC:} while adaptively optimal setting for each (kernel ROI _KN position of _{R OI),} the cross-correlation coefficient is obtained in each operation position. Therefore, when the above-described series of pattern matching processes is completed, two-dimensional distribution data of a feature amount (here, a cross-correlation coefficient) representing the similarity of the desired tomographic image is obtained in the memory 33. The two-dimensional distribution data of the feature amount is juxtaposed or superimposed on the tomographic image as a feature amount image by the DSC 17, and the image is displayed on the display 18 in the display mode.

As described above, according to the present embodiment, when performing pattern matching for observing the time-series similarity of moving organs such as myocardium, the designated search range SR _SPC
Is adaptively estimated and set within a minimum necessary range for each calculation position. Therefore, it is sufficient for the feature quantity representing the similarity to be calculated by searching only the necessary minimum area. Therefore, as compared with the conventional configuration in which the search ROI range which is set to be large in order to detect the maximum moving speed included in the data is searched all over each calculation position, the feature amount is obtained. , The amount of calculation required is greatly reduced, and the calculation is remarkably speeded up.

In the above-described ultrasonic diagnostic apparatus, the cross-correlation coefficient is calculated one by one between the kernel ROI and the object ROI in order to obtain a feature amount representing the similarity. SAD (Su
An arithmetic method using m-Absolute-Difference (sum of absolute values of mutual differences) can be used.

SADε _{m, n} is expressed as follows _{, where} A and B represent pixel value signals of both images.

(Equation 9) It is represented by

Since the position of the spatial minimum value obtained by the SAD method is considered to be a position with high similarity, the movement vector can be detected by using the SAD method. The cross-correlation method is said to be the gold standard in the field of pattern matching, but the SAD method has the advantage of faster processing because it requires fewer computation steps than the cross-correlation method. However, although the SAD method can detect a motion vector, even if it is used alone, it is difficult to standardize the similarity because it depends on the size of the signal source in terms of quantifying similarity, and it is physically meaningful. It is hard to obtain a certain index with

Therefore, taking advantage of the high speed advantage of the SAD, a motion vector is first searched for by the SAD, and a cross-correlation coefficient is obtained at the detected position of the motion vector. This reduces the time-consuming cross-correlation calculation to one,
It is possible to achieve higher speed than in the case of searching for a motion vector by the cross-correlation operation, and to obtain a physical quantity having a certain significance regarding similarity, that is, a cross-correlation coefficient.

When the SAD method and the cross-correlation method are executed in combination, for example, in the process of FIG. 5, instead of steps S8 to S10, the kernel ROI
And performing a process of calculating the SAD between the designated search range and
Next, two steps of calculating a cross-correlation coefficient between the object ROI and the kernel ROI centered on the movement destination of the movement vector obtained by the SAD may be provided.

Apart from the processing of FIG. 5, the kernel R
Two steps of performing a process of calculating the SAD between the OI and the initial search range, and then calculating a cross-correlation coefficient between the object ROI and the kernel ROI centered on the destination of the movement vector obtained by the SAD May be provided.

The present invention also provides a method of effectively tracking the movement of a part of interest in three-dimensional space and time by effectively using information of a movement vector obtained by a pattern matching operation, and a method of displaying the movement. Can be. An embodiment relating to this display will be described below.

(Fourth Embodiment) Referring to FIGS. 8 and 9,
A fourth embodiment of the present invention will be described.

In the present embodiment, in the feature quantity calculator 16 configured in the same manner as in FIG. 4 described above, the CPU 32 cooperates with the controller 34 and the operating unit 35 in addition to the calculation of the feature quantity described above. In addition, a function for calculating the movement tracking of a site of interest is provided.

For this reason, the CPU 32 performs a series of processes schematically shown in FIG. Specifically, an initial time phase S and an end time phase E are set, a variable of “time phase” = S is set, and a received signal of a frame corresponding to the initial time phase is stored in the frame memory 3.
1, the operator sets an interest point of interest in a spatial region formed by the received signal (steps S21 to S23).

Next, after initially setting the movement vector to 0, the variable of the "point of interest" is set to the point of interest + V (movement vector), and the time phase is incremented to the time phase + 1 (steps S24 to S26). .

Next, the CPU 32 determines that “time phase = S
The movement vector V of the point of interest is calculated between the received signals of two frames ranging from "+1" to "time phase-1 = S" (step S27). The movement vector V may be calculated by a conventionally known method, or may be obtained in the speeded-up search area setting described in the third embodiment. Next, the CPU 32 outputs the locus data of the movement vector V to the DSC 17, and updates the display of the locus (step S28).

Thereafter, the CPU 32 repeats the above-described movement tracking processing of the region of interest while updating the time phase until the end time phase E, together with determining whether or not the time phase <end time phase E (step S25). To S29). When the time phase = end time phase E is reached, it is determined whether or not another region of interest has been designated by the operator, and if so, the movement tracking process is repeated by going back to step S22 (step S30).
Conversely, if no other part of interest is specified, the movement tracking ends.

By the above-described movement tracking processing, an arbitrary one is displayed on the spatial image constructed by the received signal of the frame in a certain initial time phase.
Means for specifying one or more sites of interest, means for calculating a movement vector at an arbitrary point of interest, and means for calculating a movement vector by moving an operation point (position) to a destination position of the movement vector Functionally configured. Since the movement tracking processing by these means is sequentially repeated until the end time phase every time phase elapses, the spatio-temporal movement of the site of interest is tracked.

The trajectory accompanying this movement corresponds to a position on the image as a tracking position from the initial time phase to the designated end time phase by the DSC 17, as shown in FIG. 9 or FIG.

The DSC 17 receives a command signal of a desired display mode given by the operator via the operating device 35,
, And performs a process of synthesizing image data in order to display the information of the movement locus according to the command signal on the image. 9 and FIG. 10 show the change in the position of the trajectory information on a line (a myocardium or the like) on a structure (a myocardium or the like) on the image, and FIG. 9 shows a two-dimensional image, and FIG. Are shown below. Since a single phase is preferable for the time phase section (interval from the initial phase to the end phase) for displaying the movement trajectory of the region of interest, FIGS. 9 and 10 are also used as display images of the trajectory in one heart cycle. It is shown. Each image displays an image at a certain time phase (in the case of two-dimensional, an image of an arbitrary cross section at a certain time phase), and displays all trajectories in the time phase period from the initial time phase to the end time phase It is displayed using a line above, and the position is associated. In the case of three dimensions, when moving to the back side of the display cross section, it is represented by, for example, a dotted line.

The two-dimensional or three-dimensional image data may be information representing a structure (in a two-dimensional case, this is usually called a B-mode) or a feature representing similarity (such as a cross-correlation coefficient). ) Information.

(Modification 1 of Display) The DSC 17
Is not limited to a configuration in which only an image of a specific time phase is displayed when displaying an image serving as a background, and each time phase from the initial time phase to the end time phase and the movement trajectory are compared one by one. A display may be employed. This example is shown in FIGS. 11 to 13 for a two-dimensional image.

In the display example of FIG. 11, while updating both the tomographic image and the movement trajectory of the part of interest, the movement trajectory is displayed while the current trajectory is added to the past trajectory (image-wise). Is an example that assumes a state of turning over the image memory for observation). In the figure, crosses indicate a site of interest specified by the operator.

In the display example of FIG. 12, the tomographic image is updated, and the movement trajectory is displayed as a whole from the first time phase.
The locus portion corresponding to the currently displayed time phase (indicated by a black circle in the figure) is shown as differentiated from the others (again,
The image is an example in which the image memory is turned over and observed.)

Further, in the display examples of FIGS. 13A and 13B, the tomographic images of the characteristic two phases (for example, the end of diastole and the end of systole) are displayed side by side with the entire movement trajectory. For the trajectory, each time phase portion (shown by a black circle in the figure) is shown in a differentiated manner.

Since the spatio-temporal trajectory of the site of interest is expressed in various manners in this manner, it is possible to visually and surely observe the state of the local motion over the cardiac cycle.

(Modification 2 of Display) As another display method, there is a mode in which speed information of a movement vector is added together and displayed. This speed information is calculated from the time between the time phases and the moving distance. The speed information may be obtained by the CPU 32 or the DSC 17 of the feature value calculator 16, or the speed information may be separately provided on the plate. May be provided.

In the display example of FIG. 14A, a speed indicator V _IND corresponding to different hues is provided for different speeds, and the color of the movement locus represented by the line ML is displayed as the speed indicator V.
It is obtained by changing the basis of the _{IN D.} In the display example of FIG. 11B, a speed indicator V _IND corresponding to different speeds is provided for different speeds, and the brightness of the movement locus represented by the line ML is changed based on the speed indicator V _IND. It is. In the display examples shown in FIGS. 14A and 14B, differences in color and brightness are represented by differences in hatching.
The trajectory line is exaggerated.

Further, in the display example of FIG. 13C, a speed indicator V _IND corresponding to different thicknesses (line widths) is provided for different speeds, and the thickness of the movement locus represented by the line ML is displayed. This is changed based on the speed indicator V _IND . In the display example of FIG. 9D, the movement locus of the movement vector is displayed by a segment arrow AR, and the obtained speed is reflected on the length of the segment.

(Modification 3 of Display) As another display method, there is an example in which the trajectory of the movement vector is displayed in association with the cardiac phase. This association display is performed, for example, by taking an electrocardiogram (ECG) signal collected by an electrocardiograph into the device and causing the CPU 32 to associate the collected time phase with the electrocardiogram signal, while transmitting the electrocardiogram signal to the DSC 17 for display. Done.

According to the display example of FIG.
In the CG time phase, an ECG indicator ECG _IND and an ECG waveform corresponding to different hues are displayed, and the hue of the movement locus represented by the line ML is indicated by the ECG indicator ECG _IND.
Can be changed based on In addition, according to the display example of FIG. 3B, different brightnesses are made to correspond to different ECG time phases.
The CG indicator ECG _IND and the ECG waveform are displayed, and the luminance of the movement locus represented by the line ML is changed based on the ECG indicator ECG _IND . Further, according to the display example of FIG. 3C, an ECG indicator ECG in which different thicknesses (line widths) correspond to different ECG phases.
_{The IND} and the ECG waveform are displayed, and the thickness of the movement trajectory represented by the line ML is changed based on the ECG indicator ECG _IND . In the display example of FIG. 11D, the movement locus of the movement vector is represented by a line ML and an ECG waveform is displayed.
On the other hand, arrows AR1 and AR2 indicating time phases are displayed on both of them.
Is attached. The double-headed arrows AR1 and AR2 may be displayed so as to always move in conjunction with each other, or may be stationary at all times, and when one of them is moved to a desired position or a desired time phase, the other moves to one side. May be moved in conjunction with.

(Modification 4 of Display) Further, as another display method, there is an example in which the addition of the speed information of the movement vector and the association of the movement trajectory with the cardiac time phase are performed at the same time.

For example, a display method in which the display shown in FIG. 14D and the display shown in FIG.
A display method combining the display of FIG. 15A and the display of FIG. 15D can be adopted.

Further, in such a combination display, only the time phase information is identifiably given to the movement trajectory line ML without adding the speed information, while the association with the cardiac time phase and the speed are added. The information may be displayed as another graph or a numerical value. In the display example of FIG. 16, the speed information is given as a graph GR, and the correspondence with the cardiac phase with the ECG waveform is indicated by a dotted line DL.

(Modification 5 of Display) As another display example, an example in which the movement trajectories of the same part before and after the stress is applied in the stress echo test is simultaneously displayed (see FIG. 17).
Is mentioned. In this example, both movement trajectories are displayed together with the ECG waveform, and the correlation between the cardiac phase and the trajectory line ML is indicated by black circles.

(Modification 6 of Display) As yet another display example, there is an example (see FIG. 18) in which the moving trajectories of a plurality of segments are simultaneously displayed to enable comparison. In this example, the movement trajectory lines M at four sites of interest set in the myocardium
L, a graph of speed information of each locus line ML, and an ECG waveform are shown.

According to such various display methods, the degree of movement is added to the spatio-temporal trajectory of the local wall motion of the myocardium, and it is shown in comparison with the cardiac phase. It can be used to assist in the diagnosis of wall motion evaluation.

(Another Example for Obtaining Movement Vector)
In FIG. 8 described above, the moving vector is calculated one by one while updating the time phase. However, another example of obtaining the moving vector is shown in FIG. In this example, a process of reading and using a motion vector that has already been calculated and stored is performed.

The processing shown in FIG.
Of the similarity image generation routine and the trajectory display routine. In the similarity image generation routine, for example, an image of a feature amount (for example, a cross-correlation coefficient) indicating similarity based on the method described in Japanese Patent Application Laid-Open No. 8-164139 is converted from an initial time phase S to an end time phase E to a target image. And the result is stored in the memory 33, for example. In the similarity image generation routine, the high-speed feature amount calculation method described in the third embodiment and its modification may be used. When this calculation is completed, the process proceeds to a trajectory display routine, in which the moving position is sequentially read from the memory storing the moving vector every time the time phase elapses and is displayed for tracking. Thus, the region of interest can be tracked by effectively utilizing the calculation result of the pattern matching, and an ultrasonic diagnostic apparatus having a substantial application with a small calculation amount can be provided.

It should be noted that the present invention is not limited to the configurations of the above-described embodiments and modifications, and it is needless to say that various modifications can be made based on the gist of the claims. For example, the feature quantity calculator calculates the CP as described above.
In addition to having software functions provided by U,
It may be constituted by dedicated hardware such as SIC.

[0139]

As described above, according to the ultrasonic diagnostic apparatus of the present invention, artifact components can be effectively removed or suppressed, the performance of pattern matching calculation can be ensured even in a living body, and a highly accurate pattern can be obtained. Matching can be performed with high accuracy, which can contribute to improvement in diagnostic performance.

In addition, by speeding up the pattern matching calculation, it is possible to easily achieve both a short inspection time and a more reliable three-dimensional motion evaluation of a site of interest.

Conventionally, only the feature amount (for example, the cross-correlation coefficient) representing the similarity of the organization is displayed on the page, but in the present invention, the movement vector obtained in the process of the pattern matching calculation is used. The movement trajectory of the region of interest can be visually displayed while associating the movement trajectory with the movement speed and the cardiac time phase, thereby effectively supporting the evaluation of the wall motion.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an outline of an ultrasonic diagnostic apparatus according to a first embodiment of the present invention.

FIG. 2 is a block diagram showing an outline of an ultrasonic diagnostic apparatus according to a second embodiment of the present invention.

FIG. 3 is a block diagram showing an outline of an ultrasonic diagnostic apparatus according to a modified embodiment of the present invention.

FIG. 4 is a block diagram showing an outline of a feature value calculator mounted on an ultrasonic diagnostic apparatus according to a third embodiment of the present invention.

FIG. 5 is a flowchart illustrating an outline of a pattern matching process executed by a CPU of a feature amount calculator according to the third embodiment;

FIG. 6 is a view for explaining a positional relationship between a kernel ROI, an initial search range, a designated search range, and an object ROI in two frame images at different time phases.

FIG. 7 is a diagram schematically illustrating a method of adaptively setting a designated search range.

FIG. 8 is a flowchart illustrating an outline of processing of tracking (movement tracking) of a site of interest performed by a CPU of a feature amount calculator according to the fourth embodiment.

FIG. 9 is an image diagram showing a display example of tracking for two-dimensional image data.

FIG. 10 is an image diagram showing a display example of tracking for three-dimensional image data.

FIG. 11 is an image diagram showing another display example of tracking for two-dimensional image data.

FIG. 12 is an image diagram showing still another display example of tracking for two-dimensional image data.

FIG. 13 is an image diagram showing still another display example of tracking for two-dimensional image data.

FIG. 14 is a diagram showing still another display example of tracking.

FIG. 15 is a diagram showing still another display example of tracking.

FIG. 16 is a diagram showing still another display example of tracking.

FIG. 17 is a diagram showing still another display example of tracking.

FIG. 18 is a diagram showing still another display example of tracking.

FIG. 19 is a diagram showing still another display example of tracking.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 11 Ultrasonic probe 12 Transmission system 13 Reception beamformer 14 Signal processor 15 Fixed echo remover 16 Feature amount calculator 17 DSC 18 Display 21 Bandpass filter 31 (31-31N) Frame memory 32 CPU 33 Memory 34 Controller 35 Actuator

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 4C301 EE10 EE11 JB28 JB29 JB38 JC14 KK12 KK13 KK16 5B057 AA07 BA05 CA13 CA16 CE02 DB03 DC33

Claims (10)

[Claims] 1. An ultrasonic diagnostic apparatus which periodically performs a two-dimensional or three-dimensional scan of a diagnostic part of a subject with an ultrasonic signal and obtains a received signal of an electric quantity corresponding to an ultrasonic reflected signal accompanying the scan. In the pre-processing means having at least one of a means for removing a component with little variation in time series from the set of the received signals obtained by the scanning, and a means for extracting a harmonic component from the received signal, A feature for calculating spatial distribution information of a feature quantity representing a mutual similarity of a local area in a spatial area formed by two sets of received signals, each of which is a received signal processed by a processing unit and whose scanning timing is different from each other. An ultrasonic diagnostic apparatus comprising: an amount calculating unit. 2. A scanning means for periodically performing two-dimensional or three-dimensional scanning of a diagnostic part of a subject with an ultrasonic signal, and a signal for obtaining a received signal of an electric quantity corresponding to an ultrasonic reflected signal accompanying the scanning. A spatial distribution of a collecting means and a feature quantity representing the similarity between the first and second local areas in the first and second spatial areas formed by each of the two sets of received signals having different scanning timings; An ultrasonic diagnostic apparatus comprising: a similarity acquiring unit that obtains information; wherein the similarity acquiring unit is configured to convert the first local region into the second local region.
An ultrasonic wave having a search range setting means for adaptively setting a search range of the second local region to be set in the second spatial region when the feature amount is obtained in light of the local region. Diagnostic device. 3. The ultrasonic diagnostic apparatus according to claim 2, wherein the similarity acquisition means moves the second local area within the search range, and calculates the feature amount for each movement. Quantity calculation means, and one or more
Representative value selecting means for selecting one representative value; and iterative means for moving the first local area in the first spatial area and causing the calculating means and the selecting means to function for each movement. An ultrasonic diagnostic apparatus characterized by the following. 4. The ultrasonic diagnostic apparatus according to claim 2, wherein the search range setting means includes vector information and a current time phase between the first local region and the search range in a past time phase. Means for adaptively setting the center coordinates and size of the search range using at least one of vector information between the first local region and the search range in Ultrasound diagnostic equipment. 5. The ultrasonic diagnostic apparatus according to claim 3, wherein the feature amount calculating means calculates an absolute value sum (SAD) of a mutual difference between signal values between the first and second local regions. An ultrasonic diagnostic apparatus comprising: means for obtaining a movement vector position by using the movement vector position; and means for obtaining a cross-correlation coefficient of the signal value as the feature value at the movement vector position. 6. A scanning means for periodically performing two-dimensional or three-dimensional scanning of a diagnostic part of a subject with an ultrasonic signal, and a signal for obtaining a received signal of an electric quantity corresponding to an ultrasonic reflected signal accompanying the scanning. Two-dimensional distribution information of a feature amount indicating a similarity between the first and second local regions in the first and second spatial regions formed by the collection unit and the two sets of received signals having different scanning timings, respectively; An ultrasonic diagnostic apparatus comprising: a similarity acquisition unit that calculates a sum of absolute values (SAD) of mutual differences between signal values in the first and second spatial regions. An ultrasonic diagnostic apparatus comprising: means for calculating a movement vector position; and means for calculating a cross-correlation coefficient of a signal value as the feature value at the movement vector position. 7. A scanning means for periodically performing two-dimensional or three-dimensional scanning of a diagnostic part of a subject with an ultrasonic signal, and a signal for obtaining a reception signal of an electric quantity corresponding to an ultrasonic reflection signal accompanying the scanning. An ultrasound diagnostic apparatus comprising: an acquisition unit; and at least one position of interest is designated in a spatial area of a desired initial time phase among spatial areas formed by a plurality of sets of reception signals having different scanning time phases. A movement that performs an initial position of interest designation means and a process of obtaining a movement vector indicating a destination in the space area of the next time phase of the interest position to the space area of the last time phase every time the interest position is moved to the destination. An ultrasonic diagnostic apparatus comprising: vector calculation means; and trajectory display means for displaying the movement vector as spatio-temporal trajectory information of the position of interest. 8. The ultrasonic diagnostic apparatus according to claim 7, wherein said trajectory display means is means for identifying and displaying the magnitude of said movement vector in each of said time phases. Diagnostic device. 9. The ultrasonic diagnostic apparatus according to claim 7, wherein said trajectory display means is means for displaying said movement vector in each of said time phases in correspondence with a cardiac cycle. Diagnostic device. 10. The ultrasonic diagnostic apparatus according to claim 7, wherein two sets of reception signals having different scanning phases from each other are formed in first and second spatial regions. An ultrasonic diagnostic apparatus comprising: a similarity acquisition unit configured to obtain spatial distribution information of a feature amount representing a similarity between the first and second local regions.