JP5587751B2 - Ultrasonic image processing device - Google Patents

Description

  The present invention relates to an ultrasonic image processing apparatus, and more particularly to an apparatus that performs correlation calculation between image data.

  2. Description of the Related Art There are known ultrasonic image processing apparatuses and ultrasonic diagnostic apparatuses that perform correlation calculation on image data of ultrasonic images obtained by transmitting and receiving ultrasonic waves. For example, Patent Documents 1 and 2 propose epoch-making techniques for tracking the movement of the myocardium over a plurality of frames by pattern matching based on correlation calculation. Also known is a technique for forming a panoramic image by partially overlapping a plurality of image data obtained while moving a probe by pattern matching.

  In pattern matching between image data, for example, a template is set at a point of interest in one image data, and the image data in the template are correlated with each other while moving the template in the other image data. Then, the position of the template having the highest degree of similarity in the other image data is set as the position corresponding to the target location. Thus, for example, a point of interest set in the myocardium is tracked in the image data over a plurality of time phases.

  By the way, in the case of tracking the movement of the myocardium, for example, since the heart is periodically contracting and expanding, the movement of the myocardium is also periodic. Therefore, for example, when the movement of the myocardium is tracked over a plurality of time phases, the myocardium moves to approximately the same position as one period before one period after the contraction and expansion movement.

JP 2007-130063 A JP 2007-143606 A

  The inventor of the present application has conducted research and development on a technique that fuses the periodicity and pattern matching related to the above-described object such as the heart.

  The present invention has been made in the course of research and development, and an object thereof is to improve the accuracy of pattern matching in consideration of the periodicity of an object.

  An ultrasonic image processing apparatus suitable for the above object includes an image storage unit that stores a plurality of image data corresponding to a plurality of time phases obtained from an object that periodically moves via an ultrasonic wave, and image data An image processing unit that performs pattern matching over a plurality of periods of the movement based on a correlation calculation between the image processing units, and the image processing unit A plurality of reference image data corresponding periodically are searched, and a correlation calculation is performed between the reference image data in the pattern matching over the plurality of cycles.

  According to the above configuration, a plurality of reference image data periodically corresponding to each other is searched, and for example, the state of the image is relatively approximated for an object that periodically moves such as the heart, blood vessels, and blood flow. Since the correlation calculation is performed between the reference image data, it is possible to improve the accuracy of pattern matching. For example, even when matching errors are accumulated over a plurality of time phases, it is possible to cancel the accumulation of errors in the time phase of the reference image data. In the above configuration, each image data is, for example, two-dimensional data obtained from echo data collected two-dimensionally or three-dimensional data obtained from echo data collected three-dimensionally.

  In a preferred embodiment, the image processing unit searches for the origin image data in which a point of interest is set and the first image data temporally separated from the origin image data by the period of the motion as a plurality of reference image data. It is characterized by.

  In a preferred embodiment, the image processing unit targets a plurality of image data over a plurality of periods, and temporally approaches each other from the starting image data to a time phase before the first image data in order from the temporal phase. It is characterized in that a correlation calculation is executed one after another between adjacent image data, and a correlation calculation is executed between the first image data and the origin image data.

  In a preferred embodiment, the image processing unit includes, as a plurality of reference image data, in addition to the starting image data and the first image data, second image data that is further temporally separated from the first image data by the period of the motion. It is characterized by searching.

  In a preferred embodiment, the image processing unit targets a plurality of image data over a plurality of periods, and is temporally connected to a time phase before the second image data in order of temporal similarity from the first image data. The correlation calculation is performed one after another between the image data adjacent to the second image data, and the correlation calculation is performed for the second image data with the first image data or the origin image data.

  In a desirable specific example, the image processing unit uses, as the plurality of reference image data, a plurality of image data separated from each of a plurality of reference image data corresponding to a periodic characteristic time phase by an adjustment time phase. Features.

  In addition, a suitable ultrasonic diagnostic apparatus for the above purpose includes a probe that transmits / receives ultrasonic waves to / from an area including an object that periodically moves, and a transmission / reception that obtains a reception signal from the area by controlling the probe. An image forming unit that forms a plurality of image data corresponding to a plurality of time phases based on a received signal, and an image that performs pattern matching over a plurality of periods of the motion based on a correlation calculation between the image data A plurality of reference image data periodically corresponding to each other from the plurality of image data over the plurality of cycles, and the pattern over the plurality of cycles. A correlation operation is performed between reference image data in matching.

  In addition, a suitable ultrasonic image processing program that meets the above-described purpose is provided on a computer that processes a plurality of image data corresponding to a plurality of time phases obtained via an ultrasonic wave from an object that periodically moves. Pattern matching over the plurality of periods based on a search function for searching a plurality of reference image data periodically corresponding to each other from among a plurality of image data over a plurality of periods and a correlation calculation between the image data In performing the correlation calculation function for executing the correlation calculation between the reference image data.

  The ultrasonic image processing program is stored in a computer-readable storage medium such as a disk or a memory, and is provided to the computer via the storage medium. Of course, the ultrasonic image processing program may be provided to the computer via an electric communication line such as the Internet.

  According to the present invention, it is possible to improve the accuracy of pattern matching in consideration of the periodicity of an object. For example, according to a preferred aspect of the present invention, a plurality of reference image data periodically corresponding to each other is searched, and between reference image data whose image states are relatively approximate for an object that periodically moves. Since the correlation calculation is executed in the above, even when matching errors are accumulated over a plurality of time phases, it is possible to cancel the accumulation of errors in the time phase of the reference image data.

1 is a diagram illustrating an overall configuration of an ultrasonic diagnostic apparatus that is preferable in the practice of the present invention. It is a figure for demonstrating the pattern matching between image data. It is a figure which shows the change of a mutual difference value. It is a figure for demonstrating the search of a reference | standard image. It is a figure for demonstrating the search of a reference image. It is a figure for demonstrating the pattern matching which considered the periodicity of the target object.

  FIG. 1 is a diagram showing an overall configuration of an ultrasonic diagnostic apparatus suitable for implementing the present invention. The ultrasonic diagnostic apparatus of FIG. 1 has the function of the ultrasonic image processing apparatus according to the present invention.

  The probe 10 is an ultrasonic probe that transmits and receives an ultrasonic wave to a region including an object such as a heart or a blood vessel. The probe 10 includes a plurality of vibration elements that transmit and receive ultrasonic waves, and transmission of the plurality of vibration elements is controlled by the transmission / reception unit 12 to form a transmission beam. In addition, a plurality of vibration elements receive ultrasonic waves obtained from the region including the object, and signals obtained thereby are output to the transmission / reception unit 12, and the transmission / reception unit 12 forms a reception beam to form a reception beam Echo data is collected along.

  The probe 10 collects echo data by scanning an ultrasonic beam (transmission beam and reception beam) in a two-dimensional plane. Of course, a three-dimensional probe that three-dimensionally scans an ultrasonic beam in a three-dimensional space may be used.

  When the ultrasonic beam is scanned in the region including the object and the echo data is collected by the transmission / reception unit 12, the image forming unit 20 forms ultrasonic image data based on the collected echo data. The image forming unit 20 forms, for example, image data of a B mode image. The image forming unit 20 forms a plurality of image data corresponding to the plurality of ultrasonic images. For example, a plurality of image data in which an object is projected over a plurality of times is formed. A plurality of image data formed in the image forming unit 20 is stored in the image storage unit 22.

  The pattern matching processing unit 30 functions as an image processing unit that performs pattern matching between image data. The pattern matching processing unit 30 has a function of searching for standard image data and reference image data from among a plurality of image data stored in the image storage unit 22, and sets a template in the image data to set the image data in the template The function of executing the correlation calculation based on the above is provided. Then, the pattern matching processing unit 30 performs pattern matching between the image data on the basis of the correlation calculation for a plurality of image data stored in the image storage unit 22.

  FIG. 2 is a diagram for explaining pattern matching between image data, and shows processing between image data 1 and image data 2. Image data 1 and image data 2 are image data obtained at different times from the same heart, for example. In pattern matching, first, a point of interest (black circle) is set in the image data 1 by a user such as an inspector, and a template T is set in the image data 1 so as to surround the point of interest. Further, the search area SA is set so as to include an image area at a position corresponding to the template T in the image data 2. Various known methods can be used for setting the template T and the search area SA. Of course, the entire image data 2 may be used as the search area SA.

  When the template T and the search area SA are set, the template T is moved in the search area SA of the image data 2, and a plurality of pixels in the template T of the image data 1 and the template of the image data 2 are moved at each movement position. A correlation value is calculated based on a plurality of pixels in T. For example, a position corresponding to the template T in the image data 1 is set as an initial position, a correlation value is calculated for each displacement (dx, dy) from the initial position, and a plurality of displacements over the entire area in the search area SA are supported. The calculated correlation value is calculated.

  Thus, when correlation values corresponding to a plurality of displacements over the entire search area SA are calculated, a displacement having the highest degree of similarity is identified from the plurality of displacements, and the template T in the image data 1 is moved. The destination, that is, the movement destination in the image data 2 regarding the attention point (black circle).

  When the destination of the attention point is determined in the image data 2, a template T is set so as to surround the attention point in the image data 2, and further, in the image data following the image data 2, the template T The search area SA is set so as to include an image area at a position corresponding to. In the image data subsequent to the image data 2, the destination of the attention point is determined based on the correlation calculation as described above. Similarly, the movement destination of the attention point is sequentially determined based on the correlation calculation over a plurality of image data.

  The correlation value is a numerical value indicating the degree of correlation between image data (similarity), and a known mathematical formula corresponding to each method of correlation calculation is used for calculating the correlation value. For example, the phase-only correlation method and the cross-correlation method use a correlation value that shows a larger value as the degree of similarity is larger, and the minimum sum absolute difference method uses a correlation value that shows a smaller value as the degree of similarity is larger. The

  In addition, FIG. 2 shows the displacement (dx, dy) of the parallel movement in the two-dimensional plane, but even if the correlation value is calculated in consideration of the displacement of the rotational movement by further adding the displacement of the rotational movement. Good. Further, in the case of image data of a three-dimensional image, a correlation value is calculated for each displacement of three-dimensional translation and rotation.

  In the pattern matching based on the above-described correlation calculation, the pattern matching processing unit 30 in FIG. 1 performs pattern matching in consideration of the periodicity of motion related to an object such as a heart or a blood vessel. That is, in pattern matching for a plurality of image data corresponding to a plurality of time phases, the periodicity related to the object is taken into consideration while being based on the correlation calculation between adjacent image data.

  The pattern matching processing unit 30 searches a plurality of reference image data corresponding to the periodic feature time phase from the plurality of image data stored in the image storage unit 22, and further, each of the plurality of reference image data. A plurality of reference image data that are separated from each other by the adjustment time phase are searched. The periodic characteristic time phase is, for example, the end diastole or the end systole if the object is a heart. The characteristic time phase of the heart can be obtained from an electrocardiographic waveform or the like. For example, time-phase image data at the generation timing of an R wave included in an electrocardiogram waveform is used as reference image data.

  Further, based on a plurality of image data stored in the image storage unit 22, a plurality of reference image data can be searched by specifying characteristic time phases such as end diastole and end systole. Therefore, a feature time phase specifying process based on a plurality of image data by the pattern matching processing unit 30 will be described.

  The pattern matching processing unit 30 calculates a virtual period that is a provisional period related to the heart based on the plurality of image data stored in the image storage unit 22. In calculating the virtual period, the pattern matching processing unit 30 uses a mutual difference value defined by the following equation.

  In Equation 1, x and y are coordinate values on each axis when the two-dimensional image data is expressed in the XY orthogonal coordinate system, z indicates the frame number, that is, the time phase of each image data, and p Is a pixel value corresponding to each coordinate in the image data. In Equation 1, one pixel value is multiplied by the difference between two pixel values between two image data adjacent in the Z-axis direction, that is, between image data adjacent in time. As a result, the mutual difference value is relatively large when the heart expands compared to when the heart contracts, and it is possible to identify expansion and contraction that are difficult to identify with a simple difference value by the mutual difference value. .

  For example, in a certain image data z, it is assumed that a pixel p (x, y, z) is a myocardium in the vicinity of the inner wall of the heart, and the pixel value is set to p (x, y, z) = 100. When the heart expands to enlarge the heart chamber, the pixel p (x, y, z + 1) becomes the heart chamber pixel in the image data z + 1 obtained following the image data z. Since the pixel value of the heart chamber is smaller than that of the myocardium, the pixel value is set to p (x, y, z + 1) = 10. In this example, the absolute value of the right side of Equation 1 is calculated to be 100 × (100−10) = 9000. When the heart expands, many pixels that change from the myocardium to the heart chamber are generated around the inner wall of the heart, so that the mutual difference value of Equation 1 becomes relatively large.

  On the other hand, when the heart contracts, a phenomenon opposite to the above example occurs. That is, since the heart contracts and the heart chamber becomes smaller, the pixel p (x, y, z) = 10 corresponding to the heart chamber changes from the pixel p (x, y, z + 1) = 100 corresponding to the heart muscle. . In this example, when the absolute value of the right side of Equation 1 is calculated, | 10 × (10−100) | = 900, which is smaller than the value 9000 in the case of expansion. Therefore, expansion and contraction can be identified by the mutual difference value.

  FIG. 3 is a diagram illustrating changes in mutual difference values. The horizontal axis in FIG. 3 corresponds to the time phase of each image data, that is, z in the equation (1). When the mutual difference value is calculated in each time phase z using Equation 1, the mutual difference value becomes a relatively large value when the heart expands. Therefore, the pattern matching processing unit 30 detects the peak value (maximum value) of the mutual difference value, and determines the interval between adjacent peak values as the cardiac cycle (heartbeat cycle).

  However, the heart cycle may fluctuate in the heart, and when the heart cycle fluctuates, the peak value interval also fluctuates. Therefore, for example, the pattern matching processing unit 30 sets the second largest interval among the peak value intervals as the virtual period. It should be noted that the most frequently used value or centroid value obtained from the peak value interval histogram may be used as the virtual period. Further, the user or device may select the virtual period from a plurality of preset values, or the user may input the value of the virtual period. As the virtual cycle, a value obtained based on a measurement result (for example, a result of M-mode measurement) of the ultrasonic diagnostic apparatus may be used, or a fixed value may be used constantly.

  When the virtual period is set, the pattern matching processing unit 30 (FIG. 1) searches for a plurality of reference images (reference image data) from the plurality of image data using the virtual period.

  FIG. 4 is a diagram for explaining the search for the reference image. Each of FIGS. 4A to 4C shows a change in the mutual difference value described with reference to FIG. The pattern matching processing unit 30 (FIG. 1) first searches for a representative reference image (representative reference image) from among a plurality of image data. As shown in FIG. 4A, the pattern matching processing unit 30 sets image data corresponding to the time phase having the maximum mutual difference value as a representative reference image (representative reference cross section). Then, the pattern matching processing unit 30 sequentially searches for the image data closest to the time phase separated by the virtual period from the plurality of image data corresponding to the maximum mutual difference value, starting from the representative reference image.

  First, as shown in FIG. 4A, the image data closest to the time phase separated from the representative reference image by the virtual period (VHR) in the positive and negative directions in the Z-axis direction is searched and used as the reference image. . Next, as shown in FIG. 4B, the pattern matching processing unit 30 searches the image data closest to the time phase separated from the searched reference image by the virtual period (VHR) and sets it as a new reference image. In FIG. 4B, broken-line arrows indicate time phases of a plurality of reference images (reference cross sections).

  The pattern matching processing unit 30 searches for a plurality of reference images one after another using the representative reference image as a starting point. Thus, a plurality of reference images are searched from a plurality of image data corresponding to the maximum mutual difference value as shown in FIG. In FIG. 4C, broken-line arrows indicate time phases of a plurality of reference images (reference cross sections).

  When a plurality of reference images are searched, the pattern matching processing unit 30 adjusts an adjustment time phase from each of the plurality of reference images (reference image data) in an image sequence composed of a plurality of image data over a plurality of cycles. Locations separated by (offset time phase) are set as a plurality of reference images (reference image data).

  FIG. 5 is a diagram for explaining the search for the reference image. Each of FIGS. 5A and 5B shows an image sequence composed of a plurality of image data stored in the image storage unit 22 (FIG. 1). That is, each horizontal axis corresponds to the time phase (frame) of the image data, and a plurality of image data is indicated by a solid line in a pulse shape along each horizontal axis.

  In FIG. 5A, a plurality of reference images F searched in the image sequence are clearly indicated by thick and long solid lines. The plurality of reference images F are searched based on a change in the virtual period and the mutual difference value (see FIG. 4). Therefore, the interval between adjacent reference images F changes in accordance with the periodic fluctuation of the motion related to the object such as the heart.

  In FIG. 5B, a plurality of reference images R searched in the same image sequence as in FIG. 5A are clearly indicated by thick and long solid lines. As described above (see FIG. 2), in pattern matching, first, a point of interest is set in image data by a user such as an inspector. Then, pattern matching is started from the image data set with the attention point. In FIG. 5B, the starting image Rs is the image data that is the starting point where the attention point is set.

  The pattern matching processing unit 30 (FIG. 1) sets the number of time phases between the origin image Rs and the reference image F closest to the origin image Rs as an offset (adjustment time phase). Then, the pattern matching processing unit 30 sets a plurality of reference images R at locations separated from each of the plurality of reference images F by an offset. In FIG. 5, a plurality of reference images R are set at a time point that is temporally retroactive from each of the plurality of base images F.

  The plurality of reference images R searched in this way are set, for example, at a time point that is temporally backed by an offset from each of the plurality of reference images corresponding to the end diastole. Therefore, the plurality of reference images R including the origin image Rs are The images periodically correspond to each other, and the degree of contraction / expansion is substantially the same and the image states are relatively approximate.

  When a plurality of reference images R are searched, the pattern matching processing unit 30 performs pattern matching between the image data based on the correlation calculation for a plurality of image data including the plurality of reference images R. In the pattern matching, a plurality of reference images R are used to consider the periodicity of the object.

  FIG. 6 is a diagram for explaining pattern matching in consideration of the periodicity of an object. FIG. 6 shows an image sequence in which a plurality of image data stored in the image storage unit 22 (FIG. 1) is arranged in time order. The horizontal axis in FIG. 6 indicates the time phase (frame) of the image data, and a plurality of image data is indicated by a solid line in a pulse shape along the horizontal axis. A plurality of reference images R (including the origin image Rs) searched in the image sequence are clearly indicated by thick solid lines.

  The pattern matching is performed in the order close to the starting point image (starting point image data) Rs in which the attention point is set. First, a correlation operation using a template is executed between the origin image Rs and the adjacent image positioned next to the positive direction of the Z axis, and the destination of the attention point is searched in the adjacent image (FIG. 2). reference). Further, a correlation calculation is performed between the image for which the movement destination is searched and a new adjacent image located next to the positive direction of the Z axis, and the movement destination of the target point is searched for in the new adjacent image. .

  Thus, as indicated by the arc-shaped arrow pointing in the positive direction of the Z-axis in FIG. 6, correlation operations are sequentially performed between image data that are temporally adjacent to each other in order from the origin image Rs. . When the correlation calculation is executed up to the time phase before the reference image R1, the correlation calculation is executed between the reference image R1 and the origin image Rs. That is, since the reference image R1 is an image that periodically corresponds to the starting image Rs, the degree of contraction / expansion is almost the same and the image states are relatively similar to each other. It is targeted. Then, the attention point and template set in the starting image Rs are used, the search area corresponding to the template is set in the reference image R1, and the correlation calculation is executed between the reference image R1 and the starting image Rs. The

  For this reason, even if a matching error or the like is accumulated in the correlation calculation up to the time phase before the reference image R1, the accumulation of the error is canceled at the time of the reference image R1, thereby suppressing a decrease in pattern matching accuracy. Is possible.

  When the movement destination of the target point is searched for in the reference image R1, the image data that are temporally adjacent to each other are sequentially correlated from the reference image R1 to the time phase in front of the reference image R2 in the order of temporal similarity. The operation is executed. Then, for the reference image R2, a correlation calculation is performed with the reference image R1. That is, a template set according to the point of interest searched in the reference image R1 is used, and a search area corresponding to the template is set in the reference image R2, and between the reference image R2 and the reference image R1. The correlation operation is executed.

  For the reference image R2, a correlation calculation may be performed with the origin image Rs. That is, the attention point and template set in the starting image Rs are used, the search area corresponding to the template is set in the reference image R2, and the correlation calculation is executed between the reference image R2 and the starting image Rs. May be.

  Further, pattern matching may be performed from the starting image Rs in the negative direction of the Z axis. In this case, as shown by the arc-shaped arrow pointing in the negative Z-axis direction in FIG. 6, correlation operations are sequentially performed between image data adjacent in time sequence in order from the origin image Rs in order of time phase. When the correlation calculation is executed up to the time phase before the reference image R-1, the correlation calculation is executed between the reference image R-1 and the origin image Rs. That is, since the reference image R-1 is an image that periodically corresponds to the starting image Rs, the degree of contraction / expansion is approximately the same and the image states are relatively similar to each other, and thus the starting image Rs is correlated. It is the target of calculation.

  Thus, in the present embodiment, by taking into account the periodicity of an object such as the heart using a plurality of reference images R, for example, accumulation of matching errors and the like is canceled, and pattern matching accuracy is improved. To do.

  By the above-described pattern matching processing, the attention point is dynamically tracked in the image data over a plurality of time phases, and for example, a display image showing the tracking result is displayed on the display unit 40 of FIG. .

  Note that the pattern matching process described above can be applied to image data other than ultrasound, for example, other medical image data, general video data processed by a computer, and the like.

  The ultrasonic diagnostic apparatus according to the preferred embodiment of the present invention has been described above. For example, a program corresponding to the above-described reference image search process, reference image search process, and correlation calculation process is illustrated in FIG. The function of the pattern matching processing unit 30 may be realized by a computer, and the computer may function as an ultrasonic image processing apparatus. Further, the above-described embodiment is merely an example in all respects, and does not limit the scope of the present invention. The present invention includes various modifications without departing from the essence thereof.

  10 probe, 20 image forming unit, 30 pattern matching processing unit.

Claims (7)

An image storage unit that stores a plurality of image data corresponding to a plurality of time phases obtained from an object that performs periodic motion via ultrasonic waves;
An image processing unit that performs pattern matching over a plurality of periods of the movement based on a correlation calculation between image data; and
Have
The image processing unit
In searching for a plurality of reference image data periodically corresponding to each other from a plurality of image data over the plurality of cycles, in performing a correlation operation between the reference image data in the pattern matching over the plurality of cycles ,
Searching a plurality of reference image data corresponding to a periodic characteristic time phase from a plurality of image data over the plurality of cycles,
The time phase between the origin image data in which the attention point is set and the reference image closest to the origin image data is set as the adjustment time phase.
A plurality of image data separated from each of a plurality of reference image data by an adjustment time phase as the plurality of reference image data;
An ultrasonic image processing apparatus. The ultrasonic image processing apparatus according to claim 1,
The plurality of reference image data searched by the image processing unit includes starting image data in which a point of interest is set and first image data temporally separated from the starting image data by the period of the motion ,
An ultrasonic image processing apparatus. The ultrasonic image processing apparatus according to claim 2,
The image processing unit targets a plurality of image data over a plurality of periods, and includes image data that are temporally adjacent to each other up to a time phase before the first image data in order from the origin image data in order of time phase The correlation calculation is performed one after another, and the first image data is correlated with the origin image data.
An ultrasonic image processing apparatus. The ultrasonic image processing apparatus according to claim 3,
A plurality of reference image data by the image processing unit to search, in addition to the starting point image data and the first image data includes the second image data apart in time phase manner by the period of addition the motion from the first image data ,
An ultrasonic image processing apparatus. The ultrasonic image processing apparatus according to claim 4,
The image processing unit targets the plurality of image data over the plurality of periods, and the image data that are temporally adjacent to each other from the first image data to the time phase before the second image data in order from the time phase. The correlation calculation is sequentially performed between the first image data and the origin image data for the second image data.
An ultrasonic image processing apparatus. A probe for transmitting and receiving ultrasonic waves to a region including an object that performs periodic movement;
A transmission / reception unit for obtaining a reception signal from the region by controlling a probe;
An image forming unit that forms a plurality of image data corresponding to a plurality of time phases based on a received signal;
An image processing unit that performs pattern matching over a plurality of periods of the movement based on a correlation calculation between image data; and
Have
The image processing unit
In searching for a plurality of reference image data periodically corresponding to each other from a plurality of image data over the plurality of cycles, in performing a correlation operation between the reference image data in the pattern matching over the plurality of cycles ,
Searching a plurality of reference image data corresponding to a periodic characteristic time phase from a plurality of image data over the plurality of cycles,
The time phase between the origin image data in which the attention point is set and the reference image closest to the origin image data is set as the adjustment time phase.
A plurality of image data separated from each of a plurality of reference image data by an adjustment time phase as the plurality of reference image data;
An ultrasonic diagnostic apparatus. To a computer that processes a plurality of image data corresponding to a plurality of time phases obtained from an object that moves periodically via ultrasonic waves,
When searching for a plurality of reference image data periodically corresponding to each other from a plurality of image data over a plurality of periods of the motion, a periodic characteristic time is selected from the plurality of image data over the plurality of periods. A plurality of reference image data corresponding to the phase is searched, and the time phase between the starting image data where the attention point is set and the reference image closest to the starting image data is set as an adjustment time phase, and A search function in which a plurality of image data separated from each by an adjustment time phase is the plurality of reference image data ;
In performing pattern matching over the plurality of periods based on correlation calculation between image data, a correlation calculation function for performing correlation calculation between reference image data;
To realize,
An ultrasonic image processing program.

Images