JP4634872B2 - Ultrasonic diagnostic equipment - Google Patents

Description

  The present invention relates to an ultrasonic diagnostic apparatus, and more particularly to an ultrasonic diagnostic apparatus that obtains a boundary of a target tissue in an ultrasonic image.

  It is important for diagnosis to measure the size of a target tissue such as an organ or a tumor projected on an ultrasonic image. Examples of the measurement item include a distance between two points of the target tissue, a perimeter, an area, and a volume. Also known are hip joint angles, obstetric measurements, histograms, LV measurements, and the like.

  When measuring the inner diameter of an organ, tumor, etc. with an ultrasound diagnostic device, the doctor looks at the image displayed on the monitor and uses a pointing device such as a trackball to see the inner diameter end, that is, the organ A method for setting points at boundaries is known. In this case, it is difficult to detect an accurate boundary by visual observation, and there is a problem that it takes time for an operation for specifying a position by a user such as a doctor if an attempt is made to set the boundary accurately.

  For this reason, conventionally, an ultrasonic diagnostic apparatus having an auxiliary function for detecting a boundary of a target tissue is known.

  For example, Patent Document 1 discloses a technique for detecting the degree of change in image information on a line segment crossing an organ and determining the boundary of the organ from the detected degree of change. That is, a technique for determining a boundary by utilizing a large change in image information in a boundary portion of an organ is shown.

  Patent Document 2 discloses that a start point for boundary extraction is set, a scan line is radially extended, and image data is set as a threshold value within a detection range centered on an intersection with the boundary manually on the line. Shows a technique for detecting a boundary position to be corrected by binarization processing.

JP-A-8-627 JP-A-11-164834

  Depending on the organ, a method that uses the degree of change in image information or a method that binarizes image data with a threshold may not be able to accurately extract a desired boundary. For example, there is a case where another boundary exists in the vicinity of a desired boundary. In this case, even if the boundary is detected using the change degree of the image information by the technique described in Patent Document 1, a plurality of boundaries are detected, and the boundary required by the inspector is determined from the plurality of boundaries. It is not easy to do. This problem is also possible in the technique described in Patent Document 2 when a plurality of boundary positions are detected within the detection range. For this reason, the technique which can set the boundary of target tissues, such as an organ and a tumor correctly, was desired.

  The present invention has been made in such a background, and an object thereof is to provide a technique for accurately setting a boundary of a target tissue in an ultrasonic image.

  In order to achieve the above object, an ultrasonic diagnostic apparatus according to a preferred aspect of the present invention includes a transmission / reception unit that transmits and receives an ultrasonic wave in a space including a target tissue to acquire echo data, and the echo data An image forming means for forming image data of an ultrasound image including the target tissue based on the image, an initial end point setting means for setting an initial end point in the image data as an end point corresponding to the boundary of the target tissue, For a plurality of pixel data, an index value calculation means for calculating an index value indicating the degree of difference between the pixel data for each pixel data and its neighboring pixel data, and a plurality of index values for the plurality of pixel data A weighting processing means for performing weighting processing in accordance with a distance from the initial endpoint, and a plurality of the weighted index values in a region near the initial endpoint. Index value detects the pixel data having the largest has a final end point setting means for setting a final end point as were fixed to the detected pixel data position endpoints, and it is characterized by Te.

  In the above-described configuration, the weighting processing unit performs weighting processing corresponding to the distance from the initial endpoint with respect to the plurality of index values. For example, by setting the maximum weighting coefficient at the position of the initial end point and decreasing the weighting coefficient as the distance from the initial end point increases, the index value of the pixel data existing at a position close to the initial end point is weighted more. For this reason, the final endpoint setting means can detect the peak of the index value present at the position closest to the initial endpoint by detecting the pixel data having the maximum index value in the region near the initial endpoint. In other words, even when there are multiple index value peaks (extreme values) near the initial endpoint, the peak closest to the initial endpoint is heavily weighted, so the peak of the index value closest to the initial endpoint is accurately determined. Can be detected. As a result, the boundary of the target tissue can be set accurately.

  Preferably, the index value calculation means calculates a spatial differential value for each pixel data as the index value.

  Preferably, the initial endpoint setting means sets an initial endpoint A and an initial endpoint B as the endpoint based on an instruction from a user, and the index value calculation means is a straight line passing through the initial endpoint A and the initial endpoint B. The spatial differential value for each of the pixel data is calculated, and the weighting processing unit responds to the distance from the initial end point A for the plurality of differential values corresponding to the plurality of pixel data on the straight line. A weighting process and a weighting process corresponding to the distance from the initial end point B are performed, and the final end point setting means has a differential value within a region near the initial end point A based on the plurality of differential values subjected to the weighting process. The maximum pixel data is detected and the final end point C is set at the position, and further, the pixel data having the maximum differential value in the region near the initial end point B is detected and Set the final end point D to the location, the further comprising a distance measuring means for measuring a distance between the final end point C and the final end point D, characterized in that.

  Preferably, the index value calculation means calculates a variance value for a plurality of pixel data including each pixel data and neighboring pixel data as the index value.

  Preferably, the initial end point setting means sets an initial end point A and an initial end point B as the end points based on an instruction from a user, and the weighting processing means applies to a plurality of variance values for the plurality of pixel data. The weighting process according to the distance from the initial endpoint A and the weighting process according to the distance from the initial endpoint B are performed, and the final endpoint setting means is based on the plurality of weighted variance values, Pixel data having a maximum variance value in the region near the initial endpoint A is detected, the final endpoint C is set at that position, and pixel data having a maximum variance value in the region near the initial endpoint B And a distance measuring means for setting the final end point D at the position and measuring the distance between the final end point C and the final end point D.

  According to the present invention, the boundary of the target tissue can be accurately set in the ultrasonic image.

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

  FIG. 1 shows a preferred embodiment of an ultrasonic diagnostic apparatus according to the present invention, and FIG. 1 is a block diagram showing the overall configuration thereof.

  The probe 10 is an ultrasonic probe that transmits and receives ultrasonic waves in a space including target tissues such as organs and tumors. The probe 10 includes a plurality of vibration elements (not shown), and the ultrasonic beam is electronically scanned by the plurality of vibration elements. The probe 10 may be either a type that acquires echo data (volume data) in a three-dimensional space or a type that acquires echo data in a two-dimensional plane. The probe 10 may be either a type used in contact with a body surface of a living body or a type used by being inserted into a body cavity of a living body.

  The transmission / reception unit 20 controls the probe 10 to scan the ultrasonic beam and obtain a reception signal (echo data). The transmission / reception unit 20 functions as a transmission beamformer and a reception beamformer, supplies a transmission signal to each of the plurality of vibration elements, and performs phasing addition processing on the reception signal from each of the plurality of vibration elements Execute.

  The image forming unit 30 forms image data of an ultrasonic image including the target tissue based on the reception signal (echo data) supplied from the transmission / reception unit 20. The reception signal supplied from the transmission / reception unit 20 is supplied as a reception signal for each ultrasonic beam, and is supplied as data on a coordinate system (for example, rθφ polar coordinate system) of ultrasonic transmission / reception. For this reason, the image forming unit 30 performs a process of converting the received signal into a display coordinate system (for example, an xyz orthogonal coordinate system) by performing a coordinate conversion process on the received signal. At this time, interpolation processing or the like is also executed as necessary.

  In this manner, the image forming unit 30 has a function as a digital scan converter that executes a conversion process from the coordinate system of ultrasonic transmission / reception to the display coordinate system of ultrasonic images. When echo data (volume data) in a three-dimensional space is acquired from the probe 10, the image forming unit 30 forms image data of an ultrasonic image of a predetermined cross section in the three-dimensional space. For example, tomographic image data having three orthogonal cross sections is formed. When echo data in a two-dimensional plane is acquired from the probe 10, the image forming unit 30 forms tomographic image data corresponding to the two-dimensional plane.

  Image data (tomographic image data) formed by the image forming unit 30 is supplied to the monitor 40, and an ultrasonic image corresponding to the image data is displayed on the monitor 40. The image data formed by the image forming unit 30 is also supplied to the boundary detection block 50.

  The boundary detection block 50 detects and sets an end point corresponding to the boundary of the target tissue included in the image data of the ultrasonic image. As described above, since ultrasonic waves are transmitted and received by the probe 10 in the space including the target tissue, the image forming unit 30 forms tomographic image data including the target tissue such as an organ or a tumor. The boundary detection block 50 accurately extracts the boundary of the target tissue on the tomographic image data and sets the end points. Therefore, the operation of the boundary detection block 50 will be described below with reference to FIGS. In the following description, the parts shown in FIG.

  FIG. 2 is a flowchart for explaining the operation of the boundary detection block 50. The processing in each step of the flowchart of FIG. 2 is as follows.

  First, an initial endpoint is set by the initial endpoint setting unit 51 (S201). A user such as a doctor designates the position of the end point corresponding to the boundary of the target tissue in the tomographic image using a device such as a trackball or a mouse while viewing the tomographic image of the target tissue displayed on the monitor 40. .

  FIG. 3 shows a display example of a tomographic image displayed on the monitor 40, and target tissues 60 and 60 'such as an organ and a tumor are displayed. In the tomographic image of FIG. 3, when the user wants to measure the long axis length of the left target tissue 60, the user uses a device such as a trackball or a mouse to find the end point corresponding to the boundary of the target tissue 60 in the tomographic image. Designate points A and B as the positions. In FIG. 3, for the convenience of illustration, the boundary between the target tissue 60 and the surrounding tissue is clearly shown. However, in the tomographic image actually displayed on the monitor 40, the boundary portion may be blurred. In addition, due to factors such as a small display image, it is difficult to accurately identify the boundary only by visually observing the monitor 40. For this reason, in FIG. 3, it is assumed that the points A and B are designated at positions slightly deviated from the original boundary. Incidentally, in the present embodiment, an accurate boundary position is searched based on these points A and B. The initial endpoint setting unit 51 sets an initial endpoint A and an initial endpoint B as endpoints based on an instruction from the user.

  Returning to FIG. 2, when the initial end points A and B are set, the image data acquisition unit 52 reads pixel data (luminance value) on a straight line connecting the points A and B from the memory 32 in the image forming unit 30. (S202). That is, the image data acquisition unit 52 reads pixel data (luminance values) of pixels existing on the straight line 70 shown in FIG. At this time, the luminance value of the pixel corresponding to the straight line 70 may be obtained by performing interpolation processing or the like on the data read from the memory 32.

  FIG. 4 is a diagram for explaining the luminance value read by the image data acquisition unit 52. In FIG. 4, the horizontal axis indicates a position on a straight line (reference numeral 70 in FIG. 3), and the vertical axis indicates The luminance value of the pixel of each position on the straight line (code | symbol 70 of FIG. 3) is shown. In FIG. 4, positions A and B on the horizontal axis indicate the positions of points A and B in FIG. 3, respectively.

  Returning to FIG. 2, when the luminance value on the straight line connecting the points A and B is read, the smoothing processing unit 53 performs a smoothing process on the luminance value (straight line data) on the read straight line ( S203). The straight line data of FIG. 4 read by the image data acquisition unit 52 is accompanied by local fluctuations due to the influence of minute fluctuations in the transmission / reception state, noise, and the like. Therefore, a smoothing process is performed on the straight line data in FIG. 4 to cancel the local variation.

  FIG. 5 is a diagram for explaining a luminance value (straight line data) on a straight line on which smoothing processing has been performed. As in FIG. 4, the horizontal axis indicates a position on a straight line (reference numeral 70 in FIG. 3). The vertical axis indicates the luminance value after smoothing processing of pixels at each position on a straight line (reference numeral 70 in FIG. 3). Smoothing is performed by, for example, average value processing or median processing.

Returning to FIG. 2, when the smoothing process is performed, the index value calculation unit 54 performs a linear first-order differential filtering process on the smoothed straight line data (S204). FIG. 9 is a diagram for explaining differentiation processing executed by the index value calculation unit 54. In FIG. 9, Y _i−3 , Y _i−2 , Y _i−1 , Y _i ,... Each indicate a luminance value on a straight line subjected to smoothing processing. Differential value, the target pixel is the case of luminance values _{Y i,} from the luminance values of pixels adjacent to the pixel of the luminance value _{Y i |} is given by _{| Y i + 1 -Y i-} 1. The index value calculation unit 54 calculates differential values for all data on the straight line that has been subjected to the smoothing process.

  FIG. 6 is a diagram for explaining a luminance value (straight line data) on a straight line on which differentiation processing has been performed. The horizontal axis indicates a position on the straight line (reference numeral 70 in FIG. 3), and the vertical axis indicates The differential value of each position on the straight line (reference numeral 70 in FIG. 3) is shown. Due to the nature of the differential processing, the differential value is large at the position where the brightness difference of the luminance value is large. That is, the differential value is large at the boundary portion between each of the target tissue 60 and the target tissue 60 ′ shown in FIG. 3 and the surrounding tissue. However, the points A and B designated by the user are set at positions shifted from the original boundary portion.

The index value calculation unit 54 may execute the following differentiation process. FIG. 10 is a diagram for explaining another differentiation process executed by the index value calculation unit 54. 10, Y _i−3 , Y _i−2 , Y _i−1 , Y _i ,... Each indicate a luminance value on a straight line subjected to smoothing processing. In the differentiation process shown in FIG. 10, in addition to the luminance value on the straight line, the luminance value on the straight line adjacent to the straight line is also used. That is, the luminance values Z _i-3 , Z _i-2 , Z _i-1 , Z _i ,... On the straight line located above the target straight line, the luminance values X _i on the straight line located below. _-3 , X _i-2 , X _i-1 , X _i ,. When the target pixel has a luminance value Y _i , the differential value is given by | (Z _{i + 1} + Y _{i + 1} + X _{i + 1} ) − (Z _i−1 + Y _i−1 + X _i−1 ) |. Note that the differential value may be obtained by | (Z _{i + 1} + 2Y _{i + 1} + X _{i + 1} ) − (Z _i−1 + 2Y _i−1 + X _i−1 ) | by weighting the value on the straight line to which the luminance value Y _i belongs. Good.

  Returning to FIG. 2, when the differentiation process is performed, the weighting processing unit 55 performs the weighting process according to the distance from the end point to the linear data after the differentiation process (S205). The weighting processing unit 55 gives the maximum weighting coefficient at the point B centered on the point B designated by the user to the linear data after the differentiation process shown in FIG. 6 and gradually increases the weighting coefficient as the distance from the point B increases. Make it smaller. For example, the weighting coefficient is “5” at point B, and the weighting coefficient “4” is given at a position one pixel away from point B. Further, the weighting coefficient is gradually reduced to “3”, “2”, “1”, “0” as the distance increases by one pixel.

  The weighting processing unit 55 also performs weighting processing around the point A designated by the user. In other words, for example, the weighting coefficient is “5” at point A, and the weighting coefficient “4” is given at a position one pixel away from point A. Further, the weighting coefficient is gradually reduced to “3”, “2”, “1”, “0” as the distance increases by one pixel.

  FIG. 7 is a diagram for explaining a differential value on a straight line on which weighting processing has been performed. Like FIG. 6, the horizontal axis indicates a position on the straight line (reference numeral 70 in FIG. 3), and the vertical axis The axis indicates the differential value at each position on the straight line (reference numeral 70 in FIG. 3). As a result of the weighting process, the peak of the differential value located farther from the points A and B than the peak of the differential value located near the points A and B specified by the user (in FIG. The peak located on the right side) is kept small.

  Note that the weighting processing in the weighting processing unit 55 is not limited to the six-stage weighting of the weighting coefficients “5” to “0”, and may be set with more stages than six stages or less than six stages. . Further, instead of the method of decreasing the weighting coefficient in steps as the distance from the A point and the B point becomes one pixel, the weighting coefficient may be decreased in steps for a plurality of pixels.

  Returning to FIG. 2, when the weighting process is performed, the final endpoint setting unit 56 detects and detects pixel data (luminance value) having a maximum differential value in the vicinity of each of the points A and B. The final endpoint is set as the corrected endpoint at the position of the pixel data (S206).

  FIG. 8 is a diagram for explaining the final end point. Like FIG. 7, the horizontal axis indicates the position on the straight line (reference numeral 70 in FIG. 3), and the vertical axis indicates the straight line (reference numeral 70 in FIG. 3). ) The differential value after the weighting process of each position is shown. The final end point setting unit 56 sets the final end point C at the position of the luminance value at which the differential value is maximized in the vicinity region of the point A (see FIG. 7). For example, the vicinity of the point A is an area within a predetermined number of pixels from the point A. Similarly, the final end point setting unit 56 sets the final end point D at the position of the luminance value at which the differential value is maximum within the vicinity of the point B (see FIG. 7) (within a predetermined number of pixels).

  As described with reference to FIG. 7, as a result of the weighting process, the derivative located farther from the points A and B than the peak of the derivative located near the points A and B specified by the user. The value peak (the peak located on the right side of the point B in FIG. 7) is kept small. For this reason, by detecting the luminance value having the maximum differential value in the vicinity region of each of the points A and B, the final end point C and the final value corresponding to the original boundary portion of the target tissue (reference numeral 60 in FIG. 3) are detected. The end point D is appropriately extracted.

  In FIG. 8, the final end point C and the final end point D are each set to a peak of the differential value peak, that is, a portion having a large shade difference of the image. The final end point may be set at the rising part of the mountain.

  Returning to FIG. 2, when the final endpoint is set, the distance measuring unit 57 measures the distance between the final endpoint C and the final endpoint D (S207). As described above, since the final end point C and the final end point D corresponding to the original boundary portion of the target tissue (reference numeral 60 in FIG. 3) are appropriately extracted, the distance (major axis length) between the target tissue boundaries is long. Accurately measured. That is, the positions of the end points A and B initially set by the user are corrected, and an accurate major axis length is measured from the corrected final end points C and D. Then, the image of the target tissue and the measurement result of the distance are displayed on the monitor 40 (S208).

  FIG. 11 shows a display example of the monitor 40 after the final end points C and D are set. As shown in FIG. 11, the long axis length 72 of the target tissue 60 is displayed on the tomographic image of the target tissue 60. In addition to the display example shown in FIG. 11, the measurement value of the long axis length 72 may be further displayed.

  As described above, the boundary of the target tissue is accurately extracted in the boundary detection block 50. As a result, the major axis length of the target tissue can be accurately measured. In the boundary detection operation described with reference to FIG. 2, the final end points C and D are searched for on the straight line passing through the points A and B designated by the user. Without being limited thereto, the final end point may be set at a position closest to the points A and B as follows.

  FIG. 12 is a flowchart for explaining another operation of the boundary detection block 50. First, an initial endpoint is set by the initial endpoint setting unit 51 (S1201). That is, the initial endpoint setting unit 51 sets the initial endpoint A and the initial endpoint B as endpoints based on an instruction from the user by the same operation as the processing in S201 of FIG.

  When the initial end points A and B are set, the index value calculation unit 54 calculates a variance value at each of the peripheral points around the initial end points A and B (S1202). For example, the index value calculation unit 54 sets a two-dimensional search area centered on each of the initial end points A and B. Then, a variance value is calculated at each point (position of each pixel) in the search area centered on the initial end point A, and at each point (position of each pixel) in the search area centered on the initial end point B. Calculate the variance value. The search area may be large enough to include the original boundary, but the entire ultrasonic image may be used as the search area. For the variance value at each point, for example, a reference area consisting of 9 pixels of 3 pixels in the vertical direction and 3 pixels in the horizontal direction is set as the center, and the variance value of the luminance values of 9 pixels in the reference area is set. The reference area may be an area composed of 25 pixels of 5 pixels vertically and 5 pixels horizontally.

  When the variance values at the respective peripheral points of the initial endpoints A and B are calculated, the weighting processing unit 55 performs a weighting process according to the distance from the endpoint on the variance value at each point (S1203). That is, in the search area centered on the initial end point A, the maximum weighting coefficient is given to the point A, and the weighting coefficient is gradually reduced as the distance from the point A increases. For example, the weighting coefficient is “5” at point A, and the weighting coefficient “4” is given at the positions of 8 pixels surrounding point A. Further, the weighting coefficient is reduced stepwise as “3”, “2”, “1”, “0” as the distance from the point A by one pixel, and weighting processing is performed two-dimensionally. Even in the search area centered on the initial end point B, the weighting process is two-dimensionally performed as in the case of the initial end point A.

  When the weighting process is performed, the final endpoint setting unit 56 detects the point (pixel data position) at which the variance value is maximum in each of the search areas of the points A and B, and the detected pixel data The final end point is set as the end point corrected to the position (S1204). As a result of the weighting processing by the weighting processing unit 55, the dispersion values at points far from the points A and B are suppressed to be smaller than the dispersion values at points near the points A and B specified by the user. That is, the dispersion value at the boundary of the target tissue (reference numeral 60 ′ in FIG. 3) existing at a position far from the points A and B is suppressed. For this reason, the original boundary portion of the target tissue (reference numeral 60 in FIG. 3) is appropriately extracted by two-dimensionally searching for the point having the maximum variance value in the search area of each of the points A and B. The The final endpoint setting unit 56 sets the final endpoint C as the corrected endpoint corresponding to the point A, and sets the final endpoint D as the corrected endpoint corresponding to the point B.

  When the final endpoint is set, the distance measuring unit 57 measures the distance between the final endpoint C and the final endpoint D (S1205). Since the final endpoint C and the final endpoint D corresponding to the original boundary portion of the target tissue (reference numeral 60 in FIG. 3) are appropriately extracted, the distance (major axis length) between the boundaries of the target tissue is accurately measured. . That is, the positions of the end points A and B initially set by the user are two-dimensionally corrected, and an accurate major axis length is measured from the corrected final end points C and D. Then, the image of the target tissue and the measurement result of the distance are displayed on the monitor 40 (S1206).

  By the operation described with reference to FIG. 12, a point having a large shade difference at a position closest to each of the end points A and B can be set as the final end points C and D without being limited to a straight line. In S1202 of FIG. 12, instead of the variance value of each point in the search area, a two-dimensional gradient at each point may be obtained using a Laplacian filter or the like, and this may be used as an index value instead of the variance value. .

  As mentioned above, although preferred embodiment of this invention was described, embodiment mentioned above is only a mere illustration in all the points, and does not limit the scope of the present invention.

1 is a block diagram showing an overall configuration of an ultrasonic diagnostic apparatus according to the present invention. It is a flowchart for demonstrating operation | movement of a boundary detection block. It is a figure which shows the example of a display of the tomographic image displayed on the monitor. It is a figure for demonstrating the luminance value read by the image data acquisition part. It is a figure for demonstrating the luminance value on the straight line in which the smoothing process was performed. It is a figure for demonstrating the luminance value on the straight line in which the differentiation process was performed. It is a figure for demonstrating the differential value on the straight line to which the weighting process was performed. It is a figure for demonstrating the last endpoint. It is a figure for demonstrating the differentiation process in an index value calculation part. It is a figure for demonstrating another differentiation process in an index value calculation part. It is a figure which shows the example of a display of the monitor after the last end points C and D are set. It is a flowchart for demonstrating another operation | movement of a boundary detection block.

Explanation of symbols

  30 image forming unit, 51 initial endpoint setting unit, 52 image data acquisition unit, 53 smoothing processing unit, 54 index value calculation unit, 55 weighting processing unit, 56 final endpoint setting unit, 57 distance measurement unit.

Claims (5)

Wave transmitting / receiving means for transmitting and receiving ultrasonic waves in a space including the target tissue to acquire echo data;
Image forming means for forming image data of an ultrasonic image including the target tissue based on the echo data;
An initial endpoint setting means for setting an initial endpoint A and an initial endpoint B in the image data as endpoints corresponding to the boundary of the target tissue;
An index value calculation means for calculating an index value indicating a degree of difference between each of the pixel data on the straight line passing through the initial endpoint A and the initial endpoint B and the neighboring pixel data for each pixel data;
Weighting processing means for applying a weighting process according to a distance from the initial endpoint A and a weighting process according to a distance from the initial endpoint B to a plurality of index values for the plurality of pixel data;
Based on the plurality of weighted index values, the pixel data on the straight line having the maximum index value in the vicinity of the initial endpoint A is detected, and the final endpoint C is set at that position. A final endpoint setting means for detecting pixel data on the straight line having the maximum index value in a region near the initial endpoint B and setting the final endpoint D at the position ;
Distance measuring means for measuring a distance between the final end point C and the final end point D;
Having
An ultrasonic diagnostic apparatus. The ultrasonic diagnostic apparatus according to claim 1,
The index value calculation means calculates a spatial differential value for each pixel data as the index value.
An ultrasonic diagnostic apparatus. The ultrasonic diagnostic apparatus according to claim 1 or 2,
It said initial end point setting means sets the initial end point A and an initial end point B on the basis of an instruction from the user,
An ultrasonic diagnostic apparatus. The ultrasonic diagnostic apparatus according to claim 1,
The index value calculation means calculates a variance value for a plurality of pixel data including each pixel data and neighboring pixel data as the index value.
An ultrasonic diagnostic apparatus. The ultrasonic diagnostic apparatus according to claim 4,
It said initial end point setting means sets the initial end point A and an initial end point B on the basis of an instruction from the user,
An ultrasonic diagnostic apparatus.

Images