JP2007190288A - Medical image processor, ultrasonograph and medical image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a medical image processor simply extracting the outline of a diagnosis site at a high speed. <P>SOLUTION: A search route setting section 12 sets a rout searching a boundary of an intended tissue using a prescribed point on a medical image as a starting point. A weighting addition process section 13 changes a position of an interval including a plurality of pixels from the starting point along the route, weights a prescribed value to a pixel value of each pixel included in the interval at each position and adds the weighted pixel value. A boundary determination section 14 determines the position of the interval whose added value becomes a prescribed value or more as the position of the boundary of the intended tissue. A drawing section 15 draws the boundary position determined by the boundary determination section 14 on a display section 8. This constitution can prevent the increase in information amount for the computation and the number of times of the computation so as to easily extract the outline of the diagnosis site at the high speed. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a medical image processing apparatus that extracts a contour of a diagnostic part based on medical image data collected by a medical image diagnostic apparatus such as an ultrasonic diagnostic apparatus.

  An ultrasonic diagnostic apparatus is used to analyze the wall motion of the myocardium. In order to analyze the wall motion of the myocardium, it is necessary to detect the position of the myocardium, and a method for extracting the contour of the ventricle from the heart image is known (for example, Patent Document 1). Since various measurements are performed in the examination using the ultrasonic diagnostic apparatus, an ultrasonic diagnostic apparatus and a medical image processing apparatus that can automatically detect the position of the myocardium are desired. Furthermore, in order to shorten the examination time, an ultrasonic diagnostic apparatus and a medical image processing apparatus that can detect the position of the myocardium at high speed are desired.

  As a method for detecting the position of the myocardium, an automatic contour tracking method (ACT) is known. According to this method, the position of the endocardium (endocardium) of the heart can be detected with high accuracy, but the processing time becomes long because the calculation amount is enormous. The ultrasonic diagnostic apparatus has a short time from generation of an image based on a scan of a diagnostic site by ultrasonic waves to display based on a signal collected by the scan, and can collect and display medical images in a so-called real time. Therefore, it is suitable for observation of heart movement and blood flow. However, if the amount of calculation for detecting the position of the myocardium becomes enormous and the processing time becomes long, there is a problem that it is impossible to observe the movement of the heart in real time.

JP 2000-217818 A

  The present invention solves the above-described problem, and an object thereof is to provide a medical image processing apparatus, an ultrasonic diagnostic apparatus, and a medical image processing program that can easily and rapidly extract the contour of a diagnostic region. .

  According to the first aspect of the present invention, search path setting means for setting a path starting from a predetermined point on a medical image, and sequentially changing the position of a predetermined range including a plurality of pixels along the path from the start point. A weighted addition processing means for adding a predetermined weight to the pixel value of each pixel included in the predetermined range at each position and adding the weighted pixel value; and a value added by the weighted addition processing means Boundary determining means for determining a position in a predetermined range where the value of the boundary is equal to or greater than a predetermined value as a boundary position of a desired tissue, and a drawing means for drawing the boundary position determined by the boundary determining means on a display means This is a medical image processing apparatus.

  According to a sixth aspect of the present invention, search path setting means for setting a path starting from a predetermined point on the medical image, assigning an opacity corresponding to the size of the pixel value to each pixel of the medical image, Ray tracing processing means for emitting a ray along the path from the start point and obtaining the intensity of the ray that attenuates according to the opacity every time it passes through each pixel; and for the ray obtained each time it passes through each pixel Boundary determining means for determining the position of a pixel whose intensity is equal to or less than a predetermined intensity as a position of a boundary of a desired tissue; and a drawing means for drawing the position of the boundary determined by the boundary determining means on a display means This is a medical image processing apparatus.

  The invention according to claim 7 is a search path setting means for setting a path starting from a predetermined point on a medical image, and a cumulative addition for accumulating and adding pixel values of each pixel along the path from the start point Processing means, boundary determination means for determining the position of the pixel at which the addition value by the cumulative addition processing means is equal to or greater than a predetermined value, as a boundary position of a desired tissue, and the boundary position determined by the boundary determination means A medical image processing apparatus comprising: a drawing unit that draws the image on a display unit.

  The invention according to claim 13 is an ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, and generates an image of the subject based on the reflected wave. Search path setting means for setting a path starting from a predetermined point on the image, and sequentially changing the position of a predetermined range including a plurality of pixels along the path from the start point to the predetermined range at each position. Weighted addition processing means for adding a predetermined weight to the pixel value of each pixel included, and adding the weighted pixel values; and a predetermined value in which the value added by the weighted addition processing means is greater than or equal to a predetermined value Boundary determining means for determining the position of the range as a boundary position of a desired tissue; and drawing means for superimposing the boundary position determined by the boundary determining means on the image and drawing on the display means. Characteristic An ultrasonic diagnostic apparatus to.

  The invention according to claim 14 is an ultrasonic diagnosis in which an ultrasonic wave is transmitted to a subject, a reflected wave from the subject is received, a heart image is generated based on the reflected wave, and displayed on a display means. A search path setting means for setting a path starting from a predetermined point inside the heart image, and sequentially changing the position of a predetermined range including a plurality of pixels along the path from the start point; Weighted addition processing means for adding a predetermined weight to the pixel value of each pixel included in the predetermined range at each position and adding the weighted pixel value, and the value added by the weighted addition processing means Boundary determination means for determining the position of a predetermined range that is equal to or greater than a predetermined value as the position of the cardiac muscle boundary of the heart, and the position of the cardiac muscle boundary determined by the boundary determination means is superimposed on the image of the heart Display hand An ultrasonic diagnostic apparatus characterized by having a drawing means for drawing the.

  According to a nineteenth aspect of the present invention, there is provided a search route setting function for taking a medical image into a computer and setting a route starting from a predetermined point on the medical image, and a predetermined including a plurality of pixels along the route. A weighted addition processing function that sequentially changes the position of the range from the start point, gives a predetermined weight to the pixel value of each pixel included in the predetermined range at each position, and adds the weighted pixel value; A boundary determination function for determining a position within a predetermined range where the value of addition by the weighted addition processing function is equal to or greater than a predetermined value as a boundary position of a desired tissue, and a boundary position determined by the boundary determination function as display means A medical image processing program characterized by executing a drawing function for drawing.

  According to the present invention, it is possible to extract and display the outline of the diagnostic region simply and at high speed.

[First Embodiment]
The configuration of the contour extraction unit (medical image processing apparatus) according to the first embodiment of the present invention will be described with reference to FIGS. 1 and 2. FIG. 1 is a block diagram showing a schematic configuration of an ultrasonic diagnostic apparatus according to the first embodiment of the present invention. FIG. 2 is a block diagram showing the configuration of the contour extraction unit according to the first embodiment of the present invention.

  The ultrasonic diagnostic apparatus according to this embodiment is characterized by the contour extracting unit 1, and the configuration other than the contour extracting unit 1 is the same as that of a conventional ultrasonic diagnostic apparatus. Further, the contour extraction unit 1 may be detached from the ultrasonic diagnostic apparatus and used as a medical image processing apparatus separately from the ultrasonic diagnostic apparatus. In this embodiment, the contour extraction unit 1 (medical image processing device) is provided in the ultrasonic diagnostic apparatus. However, the contour extraction unit is included in a medical image diagnostic device other than the ultrasonic diagnostic device such as an X-ray CT apparatus or an MRI apparatus. 1 (medical image processing apparatus) may be provided.

  The ultrasonic probe 2 includes a one-dimensional ultrasonic probe in which a plurality of ultrasonic transducers are arranged in a predetermined direction (scanning direction) as an example, or a two-dimensional configuration in which ultrasonic transducers are arranged in a matrix (lattice). An ultrasonic probe is used.

  The transmission / reception unit 3 includes a transmission unit and a reception unit. The transmission / reception unit 3 supplies an electrical signal to the ultrasonic probe 2 to generate an ultrasonic wave, and receives an echo signal received by the ultrasonic probe 2. Data output from the transmission / reception unit 3 is output to the signal processing unit 4.

  The B-mode processing unit 41 visualizes echo amplitude information and generates B-mode ultrasonic raster data from the echo signal. The CFM processing unit 42 visualizes the moving blood flow information and generates color ultrasonic raster data. The storage unit 5 temporarily stores and holds the ultrasonic raster data generated by the signal processing unit 4.

  A DSC 6 (Digital Scan Converter: digital scan converter) converts ultrasonic raster data into image data represented by orthogonal coordinates in order to obtain an image represented by an orthogonal coordinate system (scan conversion process). Then, the image data is output from the DSC 6 to the display unit 8, and an image based on the image data is displayed on the display unit 8. For example, the DSC 6 generates tomographic image data as two-dimensional information based on the B-mode ultrasonic raster data, and outputs the tomographic image data to the display unit 8. The display unit 8 displays a tomographic image based on the tomographic image data.

  In this embodiment, image data such as tomographic image data output from the DSC 6 is output to the storage unit 7 and temporarily stored and held.

  The contour extraction unit 1 (medical image processing apparatus) reads image data from the storage unit 7 and extracts the contour of a desired diagnostic region from the image. The contour extracting unit 1 extracts the contour of a desired diagnostic region based on the pixel values of the pixels constituting the image. In the first embodiment, the contour extraction unit 1 adds the pixel values by weighting the pixel values of each pixel included in the predetermined section (range), and based on the addition value obtained by the addition, It is determined whether or not the boundary of the desired diagnostic region is included in the section (range).

  Hereinafter, the configuration and processing contents of the contour extraction unit 1 (medical image processing apparatus) will be described with reference to FIGS. FIG. 3 is a schematic diagram for explaining the setting of the start point of the search path for performing the pixel value weighted addition process. FIG. 4 is a schematic diagram showing a search path for performing weighted addition processing of pixel values. FIG. 5 is a diagram illustrating a section in which pixel value weighted addition processing is performed. FIG. 6 is a diagram showing the extracted contour and tomographic image.

  In this embodiment, the case where the diagnosis site is the heart and tomographic image data (B-mode tomographic image data) as two-dimensional information is collected as image data will be described. For example, as shown in FIG. 3A, it is assumed that tomographic images of the two-chamber cross section of the heart are collected and displayed on the display unit 8.

  As shown in FIG. 3A, in the state where the tomographic image of the two-chamber cross section of the heart, which is the diagnostic site, is displayed on the display unit 8, as shown in FIG. When the end point S1 and the end point S2 are specified using (not shown), the start point setting unit 11 receives the coordinates of the end point S1 and the end point S2, and connects the end point S1 and the end point S2, as shown in FIG. The minutes are divided at predetermined intervals. Information indicating the predetermined interval is stored in the setting information storage unit 16 in advance, and the start point setting unit 11 connects the end point S1 and the end point S2 based on the interval stored in the setting information storage unit 16. Split. The operator may arbitrarily specify the number of divisions. In this embodiment, since the purpose is to extract the outline of the myocardium, the operator designates two points in the heart chamber.

  In the example shown in FIG. 3C, the start point setting unit 11 divides a line segment connecting the end point S1 and the end point S2 at equal intervals by the division points P1 to P5. These division points P1 to P5 are the starting points of the search path for performing pixel value weighted addition processing.

  In this embodiment, the operator designates the end point S1 and the end point S2. However, a line segment may be set in advance with the preset positions as the end point S1 and the end point S2. In this case, the line segment is displayed on the display unit 8 and the operator moves or tilts the ultrasonic probe 2 so that the line segment is displayed in the heart chamber. Furthermore, the operator may arbitrarily determine the length of the line connecting the end point S1 and the end point S2 and the position of the end point S1 and the end point S2. The start point setting unit 11 divides the line segment connecting the end point S1 and the end point S2 at equal intervals. However, the start point setting unit 11 may not be divided at equal intervals. For example, the interval between the division points may be stored in the setting information storage unit 16, and the start point setting unit 11 may divide the line segment connecting the end point S1 and the end point S2 according to the interval. As described above, even when the line segment is set in advance or the division interval is changed, the processing content by the contour extraction unit 1 does not change.

  When the search path setting unit 12 receives the coordinates of each division point from the start point setting unit 11, the search path setting unit 12 sets a line perpendicular to the line segment connecting the end point S1 and the end point S2 with each division point as the start point. This vertical line becomes a path for performing weighted addition processing of pixel values. FIG. 4A shows an example of a vertical line set by the search route setting unit 12. FIG. 4A shows one perpendicular line drawn from one division point as a starting point. Note that a vertical line is also set in the direction opposite to the vertical line shown in FIG. In the example shown in FIG. 4, only the perpendicular line starting from one division point is shown, but the search path setting unit 12 is a perpendicular line starting from the division points P1 to P5 determined by the start point setting unit 11. Set.

  As shown in FIG. 4B, the weighted addition processing unit 13 sets a section 100 having a predetermined length on the perpendicular set by the search path setting unit 12, and the pixels of each pixel included in the section 100. Add values with weights. The weighting coefficient for the weighted addition process is stored in advance in the setting information storage unit 16. The weighted addition processing unit 13 performs weighted addition processing according to the following equation (1).

(Weighted addition processing formula)
A (z) = Σ _n {f (n) × P (z + n)} Expression (1)
f (n) ≧ 0
Σ _n {f (n)} = 1
Here, A (z): addition value, f (n): weighting factor, P (z + n): pixel value, z: position of the section 100 in the perpendicular direction with the start point as the origin (for example, the end of the section 100) Pixel position), n: position of pixel in section 100

  As shown in FIGS. 4C and 4D, the weighted addition processing unit 13 moves the section 100 along the perpendicular L, and performs weighting using the pixel values of the pixels included in the section 100 after the movement. Addition processing is performed. For example, the weighted addition processing unit 13 performs weighted addition processing while moving the section 100 along the vertical line L pixel by pixel. Then, the addition value A (z) obtained by the weighted addition processing unit 13 is output to the boundary determination unit 14.

  The boundary determination unit 14 compares the addition value A (z) obtained by the weighted addition processing unit 13 with a preset threshold value T (T> 0), and the addition value A (z) is equal to or greater than the threshold value T. A predetermined point included in a certain section is determined as a boundary point of the myocardium. Note that the threshold value T is a value obtained empirically. For example, the boundary determination unit 14 sets a middle point or an end point of a section where the addition value A (z) is equal to or greater than the threshold value T as a myocardial boundary point. This threshold value T is stored in advance in the setting information storage unit 16. The boundary determination unit 14 outputs information indicating the coordinates of the boundary point to the drawing unit 15.

  Here, processing contents by the weighted addition processing unit 13 and the boundary determination unit 14 will be described with reference to FIG. As shown in FIGS. 5A and 5B, the weighted addition processing unit 13 sets a section 100 for performing weighted addition processing on the vertical line, and the pixel values of the pixels included in the section 100 are described above. Weighting is performed according to the equation (1), and the pixel values of the respective pixels are added. Then, the weighted addition processing unit 13 adds the weights to the pixel values of the pixels included in the section 100 while moving the section 100 along the vertical line L one pixel at a time from the start point. In the example shown in FIGS. 5A and 5B, the weighted addition processing unit 13 sets five pixels arranged along the vertical line L as one section 100, and sets the pixel values of the five pixels included in the section 100. Add with weight. In this example, five pixels are defined as one section, but weighted addition processing may be performed with five or more or five or less pixels as one section. Further, the weighted addition processing unit 13 may move the section 100 by 2 pixels or 3 pixels.

  And the boundary determination part 14 compares the addition value A (z) calculated | required by the weighting addition process part 13 with the preset threshold value T, and the area where the addition value A (z) became more than the threshold value T Are determined as boundary points of the myocardium (tissue). For example, the boundary determination unit 14 sets the middle point of the section as the boundary point of the myocardium. In this example, the midpoint of the section is the boundary point, but a point other than the midpoint may be the myocardial (tissue) boundary point. For example, the end point of the section may be the boundary point of the myocardium (tissue).

  As described above, the myocardium (tissue) shown in FIG. 5A is present across a plurality of pixels by performing the weighted addition process over the section of a predetermined length. Therefore, the added value A (z) varies greatly at the boundary of the myocardium (tissue). On the other hand, regarding the noise shown in FIG. 5B, assuming that the noise does not exist across a plurality of pixels, the added value A (z) does not change greatly with the noise. Therefore, by appropriately setting the threshold value T, it is possible to detect the desired tissue boundary by distinguishing the desired tissue boundary and noise based on the added value A (z).

  In addition, it is necessary to set a range wider than the noise width as a target section for the weighted addition process. In the example shown in FIG. 5B, since the noise is within one pixel, for example, by adding 5 pixels as a target section of the weighted addition process, the addition value A (z) caused by the noise and the organization The tissue boundary can be detected by distinguishing the resulting added value A (z).

  The weighted addition processing unit 13 performs weighted addition processing along each vertical line starting from the dividing points P1 to P5, and the boundary determination unit 14 determines the addition value A (z) and threshold T obtained by the weighted addition processing. Based on, find the boundary point on each perpendicular. Then, the boundary determination unit 14 outputs the coordinates of the boundary points on each perpendicular to the drawing unit 15. As described above, the weighted addition processing unit 13 and the boundary determination unit 14 extract a plurality of boundary points and output information indicating the coordinates of each boundary point to the drawing unit 15.

  When the drawing unit 15 receives information indicating the coordinates of each boundary point from the boundary determination unit 14, the drawing unit 15 draws an outline of a desired tissue (myocardium) by connecting the boundary points. At this time, the drawing unit 15 superimposes the extracted contour on the tomographic image of the desired tissue (myocardium) output from the DSC 6 and causes the display unit 8 to display it. FIG. 6 shows an example of the extracted contour. In FIG. 6, the extracted contour is represented by a dotted line for convenience.

  The start point setting unit 11, the search route setting unit 12, the weighted addition processing unit 13, the boundary determination unit 14, and the drawing unit 15 described above may be configured by hardware or may be configured as software. For example, the calculation unit of the contour extraction unit 1 is configured by a CPU, and the calculation unit reads a medical image processing program from a storage unit (not shown) and executes the medical image processing program, whereby the start point setting unit 11, the search route You may make it perform the function of the setting part 12, the weighting addition process part 13, the boundary determination part 14, and the drawing part 15. FIG.

  In addition, the ultrasonic diagnostic apparatus 1 includes an operation unit (not shown) for designating the end point S1 and the end point S2 and inputting various setting conditions.

(Operation)
Next, a series of operations by the contour extraction unit 1 (medical image processing apparatus) according to the first embodiment of the present invention will be described with reference to FIG. FIG. 7 is a flowchart showing a series of operations by the contour extraction unit (medical image processing apparatus) according to the first embodiment of the present invention.

(Step S01)
First, the operator adjusts the position and inclination of the ultrasonic probe 2 so that a desired tomographic image is displayed on the display unit 8, and further adjusts image quality parameters and the like to display a desired diagnostic region. It is made to draw in the part 8. In this embodiment, a case will be described in which the heart is a diagnostic site and a tomographic image of a two-chamber cross section of the heart is displayed on the display unit 8 as shown in FIG.

(Step S02)
Next, as shown in FIG. 3B, the operator designates the end point S1 and the end point S2 using an operation unit (not shown). In this embodiment, in order to extract the outline of the myocardium, the end point S1 and the end point S2 are designated in the long axis direction in the heart chamber.

(Step S03)
When the end point S1 and the end point S2 are designated in step S02, the start point setting unit 11 receives the coordinates of the end point S1 and the end point S2, and as shown in FIG. 3C, a line segment connecting the end point S1 and the end point S2. Are divided at predetermined intervals. For example, the start point setting unit 11 divides a line segment connecting the end point S1 and the end point S2 at equal intervals by the division points P1 to P5.

  In this embodiment, the operator specifies the end point S1 and the end point S2, but a line segment having a predetermined length may be set in advance. In this case, the line segment is displayed on the display unit 8 and the operator moves or tilts the ultrasonic probe 2 so that the line segment is displayed in the heart chamber. Further, the start point setting unit 11 may divide the line segment at a predetermined interval set in advance without dividing the end point S1 and the end point S2 into equal intervals.

(Step S04)
Next, in step S04, when the search path setting unit 12 receives the coordinates of the dividing points from the starting point setting unit 11, the starting points S1 and S2, as shown in FIG. Set a line perpendicular to the line connecting. This vertical line becomes a path for performing weighted addition processing of pixel values. FIG. 4A shows one perpendicular line starting from one division point and extending from the division point. The search path setting unit 12 includes division points P <b> 1 to P <b> 1 set by the start point setting unit 11. A perpendicular line starting from P5 is set.

(Step S05)
In step S05, as shown in FIG. 4B, the weighted addition processing unit 13 sets a section 100 having a predetermined length on the perpendicular set by the search route setting unit 12, and is included in the section 100. Using the pixel value of the pixel, weighted addition processing is performed according to the above-described equation (1).

(Steps S06, S07)
In step S06, the boundary determination unit 14 compares the addition value A (z) obtained by the weighted addition processing unit 13 with a preset threshold value T. When the addition value A (z) is equal to or greater than the threshold T (step S06, Yes), the boundary determination unit 14 determines a predetermined point in the section where the addition value A is equal to or greater than the threshold T as a myocardium (tissue). (Step S07). Then, the boundary determination unit 14 outputs information indicating the coordinates of the boundary point to the drawing unit 15.

  For example, as shown in FIGS. 5A and 5B, the weighted addition processing unit 13 sets a section 100 including five pixels as a target section for weighted addition processing, and sets the five pixels included in the section 100. The pixel value is added with a weighting factor.

  And the boundary determination part 14 compares the addition value A (z) calculated | required by the weighting addition process part 13 with the preset threshold value T, and the area where the addition value A (z) became more than the threshold value T Are determined as boundary points of the myocardium (tissue). In this embodiment, the boundary determination unit 14 sets the midpoint of the section 100 where the addition value A (z) is equal to or greater than the threshold value T as the boundary point of the myocardium (tissue). Further, as points other than the intermediate point, for example, the end point of the section 100 may be a boundary point of the myocardium (tissue).

  As described above, by performing the weighted addition process over the section 100 having a predetermined length, the addition value A (z) greatly changes at the myocardial (tissue) boundary shown in FIG. In the noise shown in b), the added value A (z) does not change greatly. Therefore, by appropriately setting the threshold T, it is possible to appropriately detect the desired tissue boundary by distinguishing the desired tissue boundary and noise based on the added value A (z).

  When the addition value A is less than the threshold value T (step S06, No), as shown in FIGS. 4C and 4D, the weighted addition processing unit 13 moves to the section 100 while moving the section 100 along the vertical line L. A weighted addition process is performed using the pixel values of the included pixels. For example, the weighted addition processing unit 13 moves the section 100 one pixel at a time, adds a weight to the pixel values of the pixels included in the section 100 after the movement, and adds the value A (z) for the section 100. Is calculated (step 05). In this embodiment, the weighted addition processing unit 13 moves the section 100 by one pixel along the perpendicular L, and performs weighted addition processing on five pixels included in the section 100 after the movement, so that the section 100 is processed. The added value A (z) is calculated. The boundary determination unit 14 compares the added value A (z) with the threshold value T (step S06). If the added value A is equal to or greater than the threshold value T, a point included in the section 100 is determined as the boundary of the myocardium (tissue) A point is determined (step S07).

  As described above, a predetermined point included in a section in which the addition value A (z) first becomes equal to or greater than the threshold T in the search from the start point is set as a boundary point.

  Then, the weighted addition processing unit 13 performs weighted addition processing for each vertical line starting from the dividing points P1 to P5, and the boundary determination unit 14 performs myocardial based on the added value A (z) obtained by the weighted addition processing. The boundary point of (organization) is determined, and the coordinates of the point determined as the boundary point are output to the drawing unit 15. That is, the weighted addition processing unit 13 and the boundary determination unit 14 detect the boundary point on each perpendicular by repeating the processing from step S04 to step S07 for each perpendicular starting from the dividing points P1 to P5. . Thereby, a plurality of boundary points are detected, and information indicating the coordinates of each boundary point is output to the drawing unit 15.

(Step S08)
In step S08, the drawing unit 15 receives the information indicating the coordinates of the boundary point from the boundary determination unit 14, and draws the outline of the diagnosis site (myocardium) by connecting the boundary points as shown in FIG. At this time, the drawing unit 15 causes the display unit 8 to display the extracted outline superimposed on the myocardial tomographic image output from the DSC 6.

  As described above, according to the contour extraction unit 1 (medical image processing apparatus) according to this embodiment, the amount of information used for calculation and the number of times of calculation do not increase. Can be displayed.

(First modification)
Next, a first modification of the contour extraction unit (medical image processing apparatus) according to the first embodiment will be described with reference to FIG. FIG. 8 is a schematic diagram showing another example of a search path for performing pixel value weighted addition processing. In the example described above, the starting point of the search path is set by setting a line segment inside the myocardium. However, in this modified example, one point is specified inside the myocardium, and the search path starts from that point. Set.

  For example, as shown in FIG. 8A, the operator designates a certain point in a state where a tomographic image of a two-chamber cross section of the heart that is a diagnostic site is displayed on the display unit 8. The start point setting unit 11 sets a point specified by the operator as the start point, and the search route setting unit 12 sets a plurality of lines (search routes) extending radially from the start point. Setting information indicating the number and direction of radially extending lines (search routes) is stored in advance in the setting information storage unit 16, and the search route setting unit 12 includes a plurality of setting information stored in the setting information storage unit 16. Set the line (search route).

  Similarly to the above-described embodiment, the weighted addition processing unit 13 sets a section (range) of a predetermined length, and performs weighted addition processing using the pixel values of the pixels included in the section (range). In this modification, the weighted addition processing unit 13 moves the section (range) along a radially extending line (search path) as shown in FIG. 8B, and the pixels included in the section (range). Are added with weights. Similar to the above-described embodiment, the weighted addition processing unit 13 performs the weighted addition processing while moving the section one pixel at a time, for example.

  Similar to the above-described embodiment, the boundary determination unit 14 compares the addition value A (z) obtained by the weighted addition processing unit 13 with a preset threshold value T, and the addition value A (z) A predetermined point included in a section that is equal to or greater than the threshold T is determined as a myocardial boundary point. For example, the middle point of the section is set as a myocardial boundary point. The boundary determination unit 14 outputs information indicating the coordinates of the boundary point to the drawing unit 15.

  The weighted addition processing unit 13 and the boundary determination unit 14 perform boundary point extraction processing along a plurality of search paths set by the search path setting unit 12, and send information indicating the coordinates of each boundary point to the drawing unit 15. Output. The drawing unit 15 receives the information indicating the coordinates of each boundary point from the boundary determination unit 14 and draws the outline of the diagnosis site (myocardium) by connecting the boundary points as shown in FIG.

  As in this modification, even if one point is specified and weighted addition processing is performed along a line extending radially from the starting point, the amount of information used for the calculation and the number of calculations are not increased. It is possible to extract and display the outline of the diagnostic region easily and at high speed. Note that a preset position may be set as the start point without the operator specifying the start point.

(Second modification)
Next, a second modification of the contour extraction unit (medical image processing apparatus) according to the first embodiment will be described with reference to FIG. FIG. 9 is a diagram illustrating another example of pixel value weighted addition processing. In the second modification, as shown in FIG. 9A, a method of appropriately detecting the boundary point of the myocardium when there is a thin tissue such as a valve in addition to the myocardium will be described.

  In such a case, the length of the section (range) in which the weighted addition processing unit 13 performs the weighted addition processing is lengthened, and the weighting coefficient for each pixel is changed.

  When there is no tissue such as a valve, the weighted addition processing unit 13 sets a section 100 for performing weighted addition processing so that, for example, 7 pixels are included as shown in FIG. Are determined so as to be symmetric with respect to the pixels in the section 100. For example, the weighted addition processing unit 13 sets the weighting factors to a, b, c, and d, sets the weighting factor for the center pixel to “d”, sets the weighting factor for the adjacent pixel to “c”, and sets the weighting to the adjacent pixel. The coefficient is “b”, the weight coefficient for the end pixel is “a”, and the weight coefficient is determined so that the weight coefficient for the pixels in the section 100 is symmetric. Then, the weighted addition processing unit 13 obtains the added value A (z) in each section 100 according to the above-described equation (1).

  On the other hand, in the second modification, the weighted addition processing unit 13 sets the section 101 for performing the weighted addition processing so that, for example, 13 pixels are included as shown in FIG. The weighting coefficients are determined so that the weighting coefficients for the pixels are symmetric with respect to the pixels in the section 101. Further, the weighted addition processing unit 13 performs weighted addition processing on the pixels at predetermined intervals. For example, the weighting coefficient is set to “0” every other pixel and the weighted addition process is performed.

  For example, the weighting addition processing unit 13 sets the weighting factors as a, b, c, and d, sets the weighting factor for the center pixel to “d”, and sets the weighting factor for the adjacent pixel to “0”. Then, the weighted addition processing unit 13 sets the weighting coefficient for each pixel to “c”, “0”, “b”, “0”, and “a” toward the end of the section. In this way, the weighting coefficient is determined so that the weighting coefficient for each pixel is symmetric among the pixels in the section, and the weighting coefficient is set to “0” every other pixel. These weighting factors are stored in advance in the setting information storage unit 16. In this modification, the weighting factor is set to “0” every other pixel, but the present invention is not limited to every other pixel, and the weighting factor may be set to “0” every predetermined interval. For example, the weight coefficient may be set to “0” every two pixels.

  Then, the weighted addition processing unit 13 performs the weighted addition processing similarly to the first embodiment described above, and the boundary determination unit 14 compares the added value A (z) obtained by the weighted addition processing with the threshold value T. Then, a predetermined point included in a section where the added value A (z) first becomes equal to or greater than the threshold value T is set as a boundary point of the myocardium (tissue). Then, the weighted addition processing 13 and the boundary determination unit 14 perform weighted addition processing and boundary point detection along each perpendicular line, and the drawing unit 15 is determined by the boundary determination unit 14 as shown in FIG. The outline of the myocardium is drawn by connecting the boundary points.

  As described above, by increasing the length of one section in which weighted addition processing is performed and setting the weighting coefficient to “0” every other pixel, the added value A greatly changes in the vicinity of the boundary for a wide tissue such as the myocardium. However, in a thin tissue such as a valve, the change in the added value A is small. Therefore, by setting the threshold T to an appropriate value, it is possible to distinguish tissue such as the myocardium from tissue such as the valve, and it is possible to detect only the desired tissue (myocardium) and draw the contour. It becomes.

  In the second modification, the end point S1 and the end point S2 are set. However, as in the first modification example, the start point of one point is designated, and along the line extending radially from the start point of the one point. A weighted addition process may be performed.

  In this embodiment, the outline of the tissue is extracted from the tomographic image data of the two-dimensional information. However, the outline of the tissue can also be extracted from the volume data as the three-dimensional information. In this case, the search route setting unit 12 sets the search route in the three-dimensional space, and the weighted addition processing unit 13 weights the voxel values included in a predetermined section along the search route set in the three-dimensional space. Add with. The boundary determination unit 14 compares the added value with a preset threshold value to determine whether or not a tissue boundary is included in the section. If the added value is equal to or greater than the threshold value, the boundary determination unit 14 determines a predetermined position included in the section as a tissue boundary. As described above, the volume data as the three-dimensional information can be drawn by detecting the boundary of the desired tissue, similarly to the tomographic image data of the two-dimensional information.

  Moreover, although this embodiment demonstrated the case where the outline of a myocardium was drawn, as a diagnostic site | part, you may be organs other than a heart.

[Second Embodiment]
Next, a contour extraction unit (medical image processing apparatus) according to a second embodiment of the present invention will be described with reference to FIGS. FIG. 10 is a block diagram showing the configuration of the contour extraction unit according to the second embodiment of the present invention. FIG. 11 is a schematic diagram illustrating an image having a portion with a low luminance value. FIG. 12 is a schematic diagram for explaining processing for obtaining a boundary of a portion having a low luminance value.

  In the second embodiment, a case will be described in which the contour of a desired diagnostic region is extracted from an image in which a part of the myocardium (tissue) is not fully drawn. As in the first embodiment, the diagnostic site is the heart and the image data is tomographic image data (B-mode tomographic image data), but an organ other than the heart may be the diagnostic site, and the image data is three-dimensional. The image data may be used.

  In an ultrasonic diagnostic apparatus, an ultrasonic wave may not enter a region of interest due to an obstacle such as a bone. In such a case, as shown in FIG. , The tissue of that part may not be drawn sufficiently.

  In such a case, for example, as shown in FIG. 11B, when weighted addition processing is performed along the vertical lines L1 and L3, the addition value A becomes equal to or greater than the threshold value T at the boundary point of the myocardium (tissue). Although the boundary point of the myocardium (tissue) can be appropriately extracted, even if the weighted addition processing is performed along the perpendicular line L2, the luminance value of a part of the myocardium on the perpendicular line L2 is low. ) Cannot be extracted properly. In the second embodiment, in order to solve this problem, the configuration of the contour extraction unit is changed.

  As illustrated in FIG. 10, the contour extraction unit 1A (medical image processing apparatus) according to the second embodiment is similar to the contour extraction unit 1 according to the first embodiment in that a start point setting unit 11, a search route setting unit, 12, a weighted addition processing unit 13, a boundary determination unit 14, a drawing unit 15, and a setting information storage unit 16. Furthermore, the contour extraction unit 1A according to the second embodiment includes a first distance calculation unit 17, a difference calculation unit 18, a determination unit 19, and a correction unit 20 in order to solve the above problem.

  Similarly to the first embodiment, when the end point S1 and the end point S2 are designated, the start point setting unit 11 divides a line segment connecting the end point S1 and the end point S2 at a predetermined interval, and sets the start point of the search route. Set.

  The search route setting unit 12 sets a perpendicular line with the division point set by the start point setting unit 11 as a start point. Further, the search route setting unit 12 sets an auxiliary line inclined at a predetermined angle with respect to the perpendicular. For example, as shown in FIG. 12A, the search path setting unit 12 sets a perpendicular line L2 perpendicular to the line segment connecting the end point S1 and the end point S2, and assists inclined at a predetermined angle with respect to the perpendicular line L2. Lines L4 and L5 are set. The inclination angles of the auxiliary lines L4 and L5 are stored in the setting information storage unit 16 in advance. The operator can arbitrarily change the inclination angle. For example, the operator confirms the range of the portion with the low luminance value by observing the tomographic image displayed on the display unit 8 so that the auxiliary lines L4 and L5 are not included in the portion with the low luminance value. Determine the tilt angle. Thus, by confirming the tomographic image and determining the inclination angle, it is possible to set the auxiliary lines L4 and L5 in a portion having a high luminance value.

  Similar to the first embodiment, the weighted addition processing unit 13 sets a section (range) of a predetermined length on the perpendicular set by the search path setting unit 12, and the pixels included in the section (range) Are added with weights. In the second embodiment, as shown in FIG. 12B, the weighted addition processing unit 13 sets a section 100 having a predetermined length on the vertical line L2, and further on the auxiliary line L4 and the auxiliary line L5. Also, a section 111 and a section 112 having a predetermined length are set, and the pixel values of the pixels included in these sections (ranges) are weighted and added. The weighted addition processing unit 13 performs the weighted addition processing while moving the section 100 along the vertical line L2 by one pixel, for example. The weighted addition processing unit 13 performs weighted addition processing while moving the section 111 along the auxiliary line L4 pixel by pixel, and performs weighted addition processing while moving the section 112 along the auxiliary line L5.

  As in the first embodiment, the boundary determination unit 14 compares the addition value A (z) obtained by the weighted addition processing unit 13 with a preset threshold value T, and the addition value A (z) First, a predetermined point included in a section (range) that is equal to or greater than the threshold value is determined as a cardiac muscle boundary point. In the second embodiment, weighted addition processing is performed along the perpendicular line L2, the auxiliary line L4, and the auxiliary line L5, and the boundary points on the respective lines are obtained. Here, a boundary point on the perpendicular line L2 is defined as a boundary point A, a boundary point on the auxiliary line L4 is defined as a boundary point B, and a boundary point on the auxiliary line L5 is defined as a boundary point C. In this embodiment, since the perpendicular line L2 is set on a portion where the luminance value of the tomographic image is low, the boundary point A on the perpendicular line L2 does not indicate an appropriate boundary of the myocardium. It becomes.

  The first distance calculation unit 17 obtains the distance between the boundary point detected by the boundary determination unit 14 and the start point. In the second embodiment, since the temporary boundary point A on the perpendicular line L2, the boundary point B on the auxiliary line L4, and the boundary point C on the auxiliary line L5 are obtained, the first distance calculating unit 17 Finds the distance between each boundary point and the starting point. For example, the distance between the temporary boundary point A on the perpendicular line L2 and the starting point is D1, the distance between the boundary point B on the auxiliary line L4 and the starting point is D2, and the boundary point C on the auxiliary line L5 is Let D3 be the distance to the starting point. The first distance calculation unit 17 obtains distances D1, D2, and D3 from the coordinates of the start point and the coordinates of each boundary point.

  As shown in FIGS. 12B and 12C, the boundary points on the auxiliary line L4 and the auxiliary line L5 indicate appropriate boundary points of the tissue (myocardium), but the temporary boundary point A on the vertical line L2 Does not indicate an appropriate boundary point of the tissue (myocardium), the distance D1 is longer than the distances D2 and D3.

  The difference calculation unit 18 receives the distances D1, D2, and D3 obtained by the first distance calculation unit 17, obtains a difference between each distance, and obtains an absolute value of the difference. Specifically, the difference calculation unit 18 obtains Abs (D1-D2), Abs (D2-D3), and Abs (D3-D1). Here, Abs (X) is a function that gives the absolute value of the variable X. The absolute value of the difference between each distance obtained by the difference calculation unit 18 is output to the determination unit 19.

  Based on the absolute value obtained by the difference calculation unit 18, the determination unit 19 determines a point that appropriately indicates the myocardial (tissue) boundary among the boundary points A, B, and C. Since the myocardium has a smooth shape, for example, when the boundary points of the myocardium are appropriately detected on all the perpendicular lines L2 and the auxiliary lines L4 and L5, the distances D1, D2, and D3 are Is expected to be close. Accordingly, when the boundary points of the myocardium are properly detected on all the lines, the values of Abs (D1-D2), Abs (D2-D3), and Abs (D3-D1) are all small values. It is estimated that In this case, the determination unit 19 determines that all boundary points A, B, and C are appropriate boundary points of the myocardium (tissue). For example, the determination unit 19 compares the absolute value of the difference with a preset threshold value, and if the absolute values of all the differences are less than or equal to the threshold value, all the boundary points A, B, and C are myocardium (tissue). Is determined to be an appropriate boundary point (true boundary point). That is, if the values of Abs (D1-D2), Abs (D2-D3), and Abs (D3-D1) are less than or equal to the threshold value, the determination unit 19 determines that all boundary points A, B, and C are myocardium (tissue). ) Is an appropriate boundary point (true boundary point).

  On the other hand, for example, when the boundary point of the myocardium (tissue) is not properly detected on one line, two of the three absolute values are relatively large. In this case, one of the absolute values of the differences is greater than the threshold value, and the determination unit 19 determines that any one of the boundary points A, B, and C is an appropriate boundary point of the myocardium (tissue). Judge that it is not (true boundary point). In this case, the determination unit 19 determines that the boundary point of the combination of absolute values that is the smallest value among the three absolute values is an appropriate boundary point.

  For example, the boundary point B on the auxiliary line L4 and the boundary point C on the auxiliary line L5 are appropriate boundary points (true boundary points) of the myocardium (tissue), and the boundary point A on the perpendicular line L2 is the myocardium (tissue). ) Is not an appropriate boundary point (true boundary point), the distance D1 between the start point and the boundary point A is larger than the distances D2 and D3. Therefore, Abs (D1-D2) and Abs (D3-D1) have a larger value than Abs (D2-D3), and Abs (D2-D3) has a minimum value. Therefore, when Abs (D2-D3) is the minimum value, the boundary point B on the auxiliary line L4 and the boundary point C on the auxiliary line L5 are appropriate boundary points (true boundary points) of the myocardium (tissue). Will be shown. Therefore, the determination unit 19 determines that the boundary point of the combination of absolute values that is the minimum value among the three absolute values is an appropriate boundary point (true boundary point). In this embodiment, since Abs (D2-D3) is the minimum value, the determination unit 19 determines that the boundary point B on the auxiliary line L4 and the boundary point C on the auxiliary line L5 are appropriate boundary points of the myocardium (tissue). Judged to be (true boundary point).

  The correction unit 20 receives information indicating the coordinates of appropriate boundary points (true boundary points) from the determination unit 19 and obtains the midpoint of these boundary points. In this embodiment, since the boundary point B on the auxiliary line L4 and the boundary point C on the auxiliary line L5 indicate appropriate boundary points (true boundary points) of the myocardium (tissue), the correcting unit 20 Information indicating the coordinates of B and the boundary point C is received from the determination unit 19, and the coordinates of the intermediate point between the boundary point B and the boundary point C are obtained. The correction unit 20 outputs information indicating the coordinates of the boundary point B, the boundary point C, and the intermediate point to the drawing unit 15. This intermediate point is the boundary point of the myocardium (tissue) on the perpendicular line L2.

  Similar to the first embodiment, the drawing unit 15 draws the outline of the myocardium (tissue) by connecting the boundary points. At this time, the drawing unit 15 draws the outline of the myocardium by connecting the corrected boundary points.

  As described above, according to the ultrasonic diagnostic apparatus according to this embodiment, the outline of the myocardium (tissue) can be appropriately depicted even if the depiction of a part of the myocardium (tissue) is incomplete. .

  As in the first embodiment, the calculation unit of the contour extraction unit 1A is configured by a CPU, and the calculation unit reads a medical image processing program from a storage unit (not shown) and executes the medical image processing program. The start point setting unit 11, the search route setting unit 12, the weighted addition processing unit 13, the boundary determination unit 14, the drawing unit 15, the first distance calculation unit 17, the difference calculation unit 18, the determination unit 19, and the correction unit 20. The function may be executed.

(Operation)
Next, a series of operations by the ultrasonic diagnostic apparatus (contour extraction unit 1A) according to the second embodiment of the present invention will be described with reference to FIG. FIG. 13 is a flowchart showing a series of operations by the ultrasonic diagnostic apparatus according to the second embodiment of the present invention.

(Step S20)
First, the operator adjusts the position and inclination of the ultrasonic probe 2 so that a tomographic image of a two-chamber cross section of the heart is displayed on the display unit 8 as shown in FIG.

(Step S21)
Next, as shown in FIG. 12A, the operator designates the end point S1 and the end point S2 using an operation unit (not shown). Similarly to the first embodiment, in order to extract the outline of the myocardium, the end point S1 and the end point S2 are designated in the long axis direction in the heart chamber.

(Step S22)
When the end point S1 and the end point S2 are specified in step S21, the start point setting unit 11 receives the coordinates of the end point S1 and the end point S2, and divides a line segment connecting the end point S1 and the end point S2 at a predetermined interval. To do.

(Step S23)
Next, in step S23, when the search path setting unit 12 receives the coordinates of the division points from the start point setting unit 11, the search path setting unit 12 sets a line perpendicular to the line segment connecting the end points S1 and S2 with each division point as the start point. To do. Furthermore, the search route setting unit 12 sets an auxiliary line inclined at a predetermined angle with respect to the perpendicular. For example, as shown in FIG. 12A, the search path setting unit 12 sets a perpendicular line L2 perpendicular to the line segment connecting the end point S1 and the end point S2, and assists inclined at a predetermined angle with respect to the perpendicular line L2. Lines L4 and L5 are set.

(Step S24)
In step S24, the weighted addition processing unit 13 sets a section 100 having a predetermined length on the perpendicular L2 set by the search route setting unit 12, as shown in FIG. 12B, and is included in the section 100. Using the pixel value of the pixel, weighted addition processing is performed according to the above-described equation (1). Furthermore, the weighted addition processing unit 13 sets sections 111 and 112 having predetermined lengths also on the auxiliary lines L4 and L5, and performs weighted addition processing using pixel values of pixels included in these sections. The added value obtained by the weighted addition processing unit 13 is output to the boundary determination unit 14.

(Step S25, Step S26)
In step S <b> 25, the boundary determination unit 14 compares the added value obtained by the weighted addition processing unit 13 with a preset threshold value T. When the added value is equal to or greater than the threshold value T (Yes in step S25), the boundary determining unit 14 determines a predetermined point in the section where the added value A is initially equal to or greater than the threshold value T as the boundary of the myocardium (tissue). A point is determined (step S26). In the second embodiment, the weighted addition processing unit 13 performs weighted addition processing on the perpendicular line L2, the auxiliary line L4, and the auxiliary line L5, and the boundary determination unit 14 is based on the added value obtained by the weighted addition processing. Determine the boundary point of the myocardium (tissue).

  When the addition value A is less than the threshold value T (step S25, No), the weighted addition processing unit 13 performs weighted addition processing using the pixel values of the pixels included in each section while moving each section along each line. If the added value A is equal to or greater than the threshold value T, a point included in the section is determined as the myocardial (tissue) boundary (step S26).

(Step S27)
In step S <b> 27, the first distance calculation unit 17 obtains the distance between the boundary point detected by the boundary determination unit 14 and the start point. In the second embodiment, the first distance calculation unit 17 includes a distance D1 between the boundary point A on the perpendicular L2 and the start point, a distance D2 between the boundary point B on the auxiliary line L4 and the start point, A distance D3 between the boundary point C on the auxiliary line L5 and the start point is obtained.

(Step S28)
In step S28, the difference calculation unit 18 receives the distances D1, D2, and D3 obtained by the first distance calculation unit 17, obtains a difference between each distance, and further obtains an absolute value of the difference. Specifically, the subtraction processing unit 18 obtains Abs (D1-D2), Abs (D2-D3), and Abs (D3-D1).

(Step S29)
In step S <b> 29, the determination unit 19 determines a point that appropriately indicates the myocardial (tissue) boundary based on the absolute value obtained by the subtraction processing unit 18. First, the determination unit 19 compares the absolute value of the difference with a preset threshold value. If the absolute values of all the differences are equal to or less than the threshold value, all the boundary points A, B, and C are myocardial (tissue). Is determined to be an appropriate boundary point (true boundary point).

  On the other hand, when any one of the absolute values of the differences is larger than the threshold, the determination unit 19 determines that one of the boundary points A, B, and C is an appropriate boundary point (true) of the myocardium (tissue). Is not the boundary point). In this case, the determination unit 19 determines that the boundary point of the combination of absolute values that is the minimum value among the three absolute values is an appropriate boundary point (true boundary point) of the myocardium (tissue).

  In the example shown in FIG. 12, since Abs (D2-D3) has the minimum value, the determination unit 19 determines that the boundary point B on the auxiliary line L4 and the boundary point C on the auxiliary line L5 are appropriate for the myocardium (tissue). Judged as a boundary point (true boundary point).

(Step S30)
In step S <b> 30, the correction unit 20 receives information indicating the coordinates of appropriate boundary points (true boundary points) from the determination unit 19 and obtains the midpoint of these boundary points. For example, when it is determined that the boundary point B and the boundary point C indicate an appropriate boundary (true boundary point) of the myocardium (tissue), the correction unit 20 coordinates the intermediate point between the boundary point B and the boundary point C. Ask for. This intermediate point becomes a new boundary point of the myocardium (tissue) on the perpendicular line L2.

  Instead of obtaining the coordinates of the intermediate point between the boundary point B and the boundary point C, the correction unit 20 obtains an average value of the distance D2 from the start point to the boundary point B and the distance D3 from the start point to the boundary point C. The average value may be a distance D1 ′, and a point separated from the starting point along the vertical line L2 by the distance D1 ′ may be a new boundary point on the vertical line L2.

(Step S31)
In step S31, as in the first embodiment, the drawing unit 16 draws the outline of the myocardium (tissue) by connecting a plurality of detected boundary points.

  As described above, even when the luminance value of a part of the tissue is low and the tissue of the part is not sufficiently drawn, by detecting and interpolating the boundary points around the tissue, It becomes possible to draw an outline appropriately.

  Also in the second embodiment, as in the first embodiment, a tissue contour may be extracted from volume data as three-dimensional information.

[Third Embodiment]
Next, a contour extraction unit (medical image processing apparatus) according to a third embodiment of the present invention will be described with reference to FIGS. FIG. 14 is a block diagram showing a configuration of a contour extracting unit according to the third embodiment of the present invention. FIG. 15 is a schematic diagram for explaining processing for obtaining a boundary of a portion having a low luminance value.

  In the third embodiment, as in the second embodiment, a case will be described in which the contour of a desired diagnostic region is extracted from an image in which a part of the myocardium is incompletely rendered.

  The contour extracting unit 1B (medical image processing apparatus) according to the third embodiment is characterized in that a smoothing processing unit 21 is provided in addition to the contour extracting unit 1 according to the first embodiment. The smoothing processing unit 21 reads image data (tomographic image data) from the storage unit 7 and applies a smoothing filter to a predetermined range of the image. The smoothing filter operated by the smoothing processing unit 21 may be a two-dimensional filter or a one-dimensional filter.

  For example, as shown in FIG. 15A, when the luminance value of a part of the myocardium (tissue) is low, the smoothing processing unit 21 applies a smoothing filter to the image data, and FIG. As shown, improves myocardial (tissue) continuity.

  Then, as in the first embodiment, the start point is set by the start point setting unit 11, and a perpendicular extending from the start point is set by the search route setting unit 12. For example, as shown in FIG. 15C, perpendicular lines L1, L2, and L3 are set. Then, similarly to the first embodiment, the weighted addition processing unit 13 and the boundary determination unit 14 detect the boundary point of the myocardium (tissue), and the drawing unit 15 connects the detected boundary point to connect the detected myocardium (tissue). Draw an outline.

  When the smoothing filter is applied to the image data (tomographic image data), as shown in FIG. 15D, the boundary of the myocardium (tissue) after the smoothing process is the same as the boundary of the myocardium (tissue) before the smoothing process. Although it becomes dull in comparison, the boundary point of the myocardium (tissue) can be detected by adjusting the value of the threshold value T. For example, by setting the threshold value T relatively high, the boundary point of the myocardium (tissue) can be detected. Note that the dullness depends on the smoothing range.

  Note that the entire image data may be smoothed, or the range specified by the operator may be smoothed. For example, a smoothing filter is applied to a range including a portion having a low luminance value.

  By performing smoothing processing as described above, it is possible to draw the outline of the tissue appropriately even when the luminance value of a part of the tissue is low and the tissue of that part is not sufficiently drawn It becomes.

  As in the first embodiment, the calculation unit of the contour extraction unit 1B is configured by a CPU, and the calculation unit reads a medical image processing program from a storage unit (not shown) and executes the medical image processing program. Thus, the functions of the start point setting unit 11, the search route setting unit 12, the weighted addition processing unit 13, the boundary determination unit 14, the drawing unit, and the smoothing processing unit 21 may be executed.

  Further, the smoothing processing unit 21 may be provided in the contour extraction unit 1A according to the second embodiment.

[Fourth Embodiment]
Next, a contour extraction unit (medical image processing apparatus) according to a fourth embodiment of the present invention will be described with reference to FIGS. FIG. 16 is a block diagram showing a configuration of a contour extracting unit according to the fourth embodiment of the present invention. FIG. 17 is a schematic diagram illustrating a search path for performing the cumulative addition process.

  The contour extraction unit 1C (medical image processing apparatus) according to the fourth embodiment includes a cumulative addition processing unit 22 instead of the weighted addition processing unit 13 of the contour extraction unit 1 according to the first embodiment. The point is a feature. The configuration other than the cumulative addition processing unit 22 is the same as the configuration of the contour extraction unit 1 according to the first embodiment.

  As shown in FIG. 17A, the cumulative addition processing unit 22 accumulates and adds pixel values of pixels existing on the line set by the search path setting unit 12, and determines a boundary value by accumulating and adding the values. To the unit 14.

  The boundary determination unit 14 compares the cumulative addition value received from the cumulative addition processing unit 22 with a preset threshold value, and the cumulative addition value becomes equal to or greater than the threshold value as shown in FIG. The pixel is determined as the boundary of the myocardium (tissue). The boundary determination unit 14 outputs information indicating the coordinates of the detected boundary point of the myocardium (tissue) to the drawing unit 15. The threshold value is stored in the setting information storage unit 16. This threshold can be determined empirically.

  Then, the cumulative addition processing unit 22 and the boundary determination unit 14 extract the boundary point of the myocardium (tissue) by performing cumulative addition processing on the plurality of lines set by the search route setting unit 12. The drawing unit 15 draws the outline of the myocardium (tissue) by connecting a plurality of boundary points extracted by the cumulative addition processing unit 22 and the boundary determination unit 14.

  As described above, instead of performing weighted addition processing on pixel values, even if cumulative addition processing is performed, tissue boundaries can be appropriately detected and drawn.

  The search route setting method for performing the cumulative addition process is the same as the method in the first embodiment. For example, a line segment connecting the end point S1 and the end point S2 may be divided, and a perpendicular line starting from the division point may be used as a search path, or only one start point may be designated and a line extending radially from the start point may be used as a search path. good.

  Similarly to the first embodiment, the calculation unit of the contour extraction unit 1C is configured by a CPU, and the calculation unit reads a medical image processing program from a storage unit (not shown) and executes the medical image processing program. Thus, the functions of the start point setting unit 11, the search route setting unit 12, the cumulative addition processing unit 22, the boundary determination unit 14, and the drawing unit 15 may be executed.

  When the luminance value of a part of the tissue is low and the part of the tissue is not sufficiently drawn, the boundary point may be interpolated as in the contour extracting unit 1A according to the second embodiment. Smoothing processing may be performed as in the contour extraction unit 1B according to the third embodiment.

[Fifth Embodiment]
Next, a contour extraction unit (medical image processing apparatus) according to a fifth embodiment of the present invention will be described with reference to FIGS. FIG. 18 is a block diagram showing a configuration of a contour extracting unit according to the fifth embodiment of the present invention. FIG. 19 is a schematic diagram for explaining the ray tracing process.

  The contour extraction unit 1D (medical image processing apparatus) according to the fifth embodiment includes a ray tracing unit 23 instead of the weighted addition processing unit 13 of the contour extraction unit 1 according to the first embodiment. Is a feature. The configuration other than the ray tracing unit 23 is the same as the configuration of the contour extracting unit 1 according to the first embodiment.

  The contour extraction unit 1D (medical image processing apparatus) according to the fifth embodiment detects the boundary of the myocardium (tissue) by applying the concept of volume rendering for generating a three-dimensional image.

Volume rendering has the concept of opacity. The concept is to define opacity corresponding to the voxel value of each voxel. When the light beam is irradiated to the volume data in which the opacity is defined, the intensity of the light beam is attenuated according to the opacity whenever it passes through each voxel. The attenuation of the light beam is expressed by, for example, the following formula (2).
Initial value of light intensity: I ₀
Opacity: α (0 ≦ α ≦ 1)
Light intensity: I (z + Δz) = (1−α) × I (z) (2)
I (0) = I ₀
z: Position of the pixel with the origin as the origin The opacity α corresponds to the pixel value (or voxel value) as shown in FIG. Further, the opacity α may be determined using a lookup table or the like.

  The ray tracing unit 23 defines the opacity α corresponding to the pixel value of the pixels constituting the image data, and moves from the start point set by the start point setting unit 11 to the direction of the line set by the search path setting unit 12. Each time a light beam is emitted and passes through pixels on the line, the intensity of the light beam is attenuated according to the above equation (2). Then, the ray tracing unit 23 outputs the intensity of the ray obtained every time one pixel passes to the boundary determining unit 14.

  The boundary determination unit 14 receives the intensity of the light beam output from the light beam tracking unit 23 and compares it with a preset threshold value S. Then, the boundary determination unit 14 determines a pixel where the intensity of the light beam output from the light beam tracking unit 23 is initially equal to or less than the threshold value S as a myocardial (tissue) boundary. The threshold value S is stored in the setting information storage unit 16 in advance.

  Then, the ray tracing unit 23 performs ray tracing processing for a plurality of lines set by the search path setting unit 12, and the boundary determining unit 14 extracts a myocardial (tissue) boundary point for each line. The drawing unit 15 draws the outline of the myocardium (tissue) by connecting a plurality of boundary points extracted by the ray tracing unit 23 and the search path setting unit 12.

  As described above, it is also possible to appropriately detect the tissue boundary and perform drawing by setting the opacity for each pixel and performing the ray tracing process.

  Note that the search path setting method for performing the ray tracing process is the same as that in the first embodiment. For example, a line segment connecting the end point S1 and the end point S2 may be divided, and a perpendicular line starting from the division point may be used as a search path, or only one start point may be designated and a line extending radially from the start point may be used as a search path. good.

  As in the first embodiment, the calculation unit of the contour extraction unit 1D is configured by a CPU, and the calculation unit reads a medical image processing program from a storage unit (not shown) and executes the medical image processing program. Thus, the functions of the start point setting unit 11, the search path setting unit 12, the ray tracing unit 23, the boundary determination unit 14, and the drawing unit 15 may be executed.

  When the luminance value of a part of the tissue is low and the part of the tissue is not sufficiently drawn, the boundary point may be interpolated as in the contour extracting unit 1A according to the second embodiment. Smoothing processing may be performed as in the contour extraction unit 1B according to the third embodiment.

[Sixth Embodiment]
Next, an outline extraction unit (medical image processing apparatus) according to a sixth embodiment will be described with reference to FIGS. FIG. 20 is a block diagram showing a configuration of a contour extracting unit according to the sixth embodiment of the present invention. FIG. 21 is a schematic diagram for explaining the averaging process.

  The contour extracting unit 1E (medical image processing apparatus) according to the sixth embodiment includes a second distance calculating unit 24 and an average value calculating unit 25 in addition to the contour extracting unit 1 according to the first embodiment. The feature is that it has. The configuration other than the second distance calculation unit 24 and the average value calculation unit 25 is the same as the configuration of the contour extraction unit 1 according to the first embodiment.

  The second distance calculation unit 24 obtains a distance between the start point set by the start point setting unit 11 and the boundary point detected by the boundary determination unit 14. The average value calculation unit 25 calculates an average value of the distances calculated by the second distance calculation unit 24. The average value calculation unit 25 obtains, for example, an average value of distances between adjacent boundary points. When the drawing unit 15 receives the average value of the distance from the average value calculation unit 25, the drawing unit 15 sets a point separated from the start point by the distance of the average value along the search direction as a new boundary point, and connects the new boundary points. Draw outline of myocardium (tissue)

  As described above, by averaging the distance from the starting point to each boundary point, it is possible to smoothly draw the boundary line of the myocardium (tissue).

  Note that the second distance calculation unit 24 and the average value calculation unit 25 may be installed in the contour extraction unit according to the second to fifth embodiments. Even when the second distance calculation unit 24 and the average value calculation unit 25 are installed in the contour extraction unit according to the second to fifth embodiments, as in the sixth embodiment, the myocardium (tissue) The boundary line can be drawn smoothly.

1 is a block diagram showing a schematic configuration of an ultrasonic diagnostic apparatus according to a first embodiment of the present invention. It is a block diagram which shows the structure of the outline extraction part which concerns on 1st Embodiment of this invention. It is a schematic diagram for demonstrating the setting of the starting point of the search path | route which performs the weighted addition process of a pixel value. It is a schematic diagram which shows the search path | route which performs the weighted addition process of a pixel value. It is a figure which shows the area which performs the weighting addition process of a pixel value. It is a schematic diagram which shows the extracted outline and tomogram. It is a flowchart which shows a series of operation | movement by the outline extraction part (medical image processing apparatus) which concerns on 1st Embodiment of this invention. It is a schematic diagram which shows another example of the search path | route which performs the weighted addition process of a pixel value. It is a figure which shows another example of the weighting addition process of a pixel value. It is a block diagram which shows the structure of the outline extraction part which concerns on 2nd Embodiment of this invention. It is a schematic diagram which shows the image with a part with a low luminance value. It is a schematic diagram for demonstrating the process which calculates | requires the boundary of the part with a low luminance value. It is a flowchart which shows a series of operation | movement by the ultrasonic diagnosing device which concerns on 2nd Embodiment of this invention. It is a block diagram which shows the structure of the outline extraction part which concerns on 3rd Embodiment of this invention. It is a schematic diagram for demonstrating the process for calculating | requiring the boundary of the part with a low luminance value. It is a block diagram which shows the structure of the outline extraction part which concerns on 4th Embodiment of this invention. It is a schematic diagram which shows the search path | route which performs an accumulation addition process. It is a block diagram which shows the structure of the outline extraction part which concerns on 5th Embodiment of this invention. It is a schematic diagram for demonstrating a ray tracing process. It is a block diagram which shows the structure of the outline extraction part which concerns on 6th Embodiment of this invention. It is a schematic diagram for demonstrating an averaging process.

Explanation of symbols

1, 1A, 1B, 1C, 1D, 1E Contour extraction unit 11 Start point setting unit 12 Search route setting unit 13 Weighted addition processing unit 14 Boundary determination unit 15 Drawing unit 16 Setting information storage unit 17 First distance calculation unit 18 Difference calculation Unit 19 Determination unit 20 Correction unit 21 Smoothing processing unit 22 Cumulative addition processing unit 23 Ray tracing unit 24 Second distance calculation unit 25 Average value calculation unit

Claims (21)

Search route setting means for setting a route starting from a predetermined point on the medical image;
The position of a predetermined range including a plurality of pixels along the path is sequentially changed from the start point, and a predetermined weight is given to the pixel value of each pixel included in the predetermined range at each position, and the weight is applied. Weighted addition processing means for adding the obtained pixel values;
Boundary determination means for determining the position of a predetermined range where the value of addition by the weighted addition processing means is equal to or greater than a predetermined value as the position of the boundary of the desired tissue;
Drawing means for drawing the position of the boundary determined by the boundary determination means on a display means;
A medical image processing apparatus comprising: The search route setting means sets a plurality of routes with a plurality of points on the medical image as individual start points,
The weighted addition processing means sequentially changes the position of the predetermined range for each of the plurality of paths from the individual start points, and applies the pixel value of each pixel included in the predetermined range at each position for each of the plurality of paths. A predetermined weight and add the weighted pixel values,
The boundary determination means determines the position of a predetermined range where the value of the addition is equal to or greater than a predetermined value for each of the plurality of paths, determines the position as the position of the boundary of the desired tissue,
The medical image processing apparatus according to claim 1, wherein the drawing unit draws the boundary position determined for each of the plurality of routes on the display unit. The search route setting means sets a plurality of routes starting from one point on the medical image,
The weighted addition processing means sequentially changes the position of the predetermined range from the start point for each of the plurality of paths, and sets the predetermined value for the pixel value of each pixel included in the predetermined range at each position for each of the plurality of paths. And add the weighted pixel values,
The boundary determination means obtains a position of a predetermined range where the value of the addition becomes a predetermined value or more for each of the plurality of paths, determines the position as the position of the boundary of the desired tissue,
The medical image processing apparatus according to claim 1, wherein the drawing unit draws the boundary position determined for each of the plurality of routes on the display unit.   The boundary determination means determines a pixel at the center or at an end among pixels included in a predetermined range in which the value of the addition is equal to or greater than a predetermined value as the boundary position of the desired tissue. The medical image processing apparatus according to any one of claims 1 to 3.   The weighted addition processing means sets a pixel value to 0 every predetermined interval of a plurality of pixels included in the predetermined range, adds a predetermined weight to other pixel values, and adds the weighted pixel values The medical image processing apparatus according to claim 1, wherein the medical image processing apparatus is a medical image processing apparatus. Search route setting means for setting a route starting from a predetermined point on the medical image;
An opacity corresponding to the magnitude of the pixel value is assigned to each pixel of the medical image, a light beam is emitted from the starting point along the path, and the light beam attenuates according to the opacity every time it passes through each pixel. Ray tracing processing means for obtaining,
Boundary determination means for determining the position of the pixel where the intensity of the light beam obtained each time passing through each pixel is equal to or less than a predetermined intensity as the position of the boundary of the desired tissue;
Drawing means for drawing the position of the boundary determined by the boundary determination means on a display means;
A medical image processing apparatus comprising: Search route setting means for setting a route starting from a predetermined point on the medical image;
Cumulative addition processing means for accumulating and adding pixel values of each pixel along the path from the start point;
Boundary determination means for determining the position of the pixel where the value of the addition by the cumulative addition processing means is a predetermined value or more as the position of the boundary of the desired tissue;
Drawing means for drawing the position of the boundary determined by the boundary determination means on a display means;
A medical image processing apparatus comprising: First distance calculating means for obtaining a distance between the position of the boundary determined by the boundary determining means and the start point for the plurality of paths;
Difference calculating means for obtaining an absolute value of the difference between the distances of adjacent boundary positions;
A determination unit that determines a position of a boundary where the absolute value of the difference is equal to or less than a predetermined value as a true boundary position;
Further comprising
The medical image processing apparatus according to claim 2, wherein the drawing unit draws the position of the true boundary on the display unit. A correction means for obtaining an average of the coordinates of the true boundary position and setting the position of the average coordinate as a new boundary position;
9. The medical image processing apparatus according to claim 8, wherein the drawing unit draws the true boundary position and the new boundary position on the display unit.   The medical image processing apparatus according to claim 1, wherein the medical image is an image that has been subjected to a smoothing process.   11. The medical image according to claim 1, wherein the drawing unit draws the position of the boundary determined by the boundary determination unit on the display unit by superimposing the position on the medical image. Processing equipment. Second distance calculating means for obtaining a distance between the position of the boundary determined by the boundary determining means and the start point for the plurality of paths;
Average value calculating means for calculating an average of distances obtained by the second distance calculating means;
Further comprising
12. The drawing unit according to claim 2, wherein the drawing unit draws the display unit as a new boundary position at a position separated from the starting point by the average distance along the route. The medical image processing apparatus described in 1. An ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, and generates an image of the subject based on the reflected wave,
Search route setting means for setting a route starting from a predetermined point on the image;
The position of a predetermined range including a plurality of pixels along the path is sequentially changed from the start point, and a predetermined weight is given to the pixel value of each pixel included in the predetermined range at each position, and the weight is applied. Weighted addition processing means for adding the obtained pixel values;
Boundary determination means for determining the position of a predetermined range where the value of addition by the weighted addition processing means is equal to or greater than a predetermined value as the position of the boundary of the desired tissue;
Drawing means for superimposing the position of the boundary determined by the boundary determination means on the image and drawing on the display means;
An ultrasonic diagnostic apparatus comprising: An ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, generates an image of the heart based on the reflected wave, and displays the image on a display unit,
Search path setting means for setting a path starting from a predetermined point inside the image of the heart;
The position of a predetermined range including a plurality of pixels along the path is sequentially changed from the start point, and a predetermined weight is given to the pixel value of each pixel included in the predetermined range at each position, and the weight is applied. Weighted addition processing means for adding the obtained pixel values;
Boundary determining means for determining the position of a predetermined range where the value of addition by the weighted addition processing means is equal to or greater than a predetermined value as the position of the boundary of the myocardium of the heart;
Drawing means for superimposing the position of the myocardial boundary determined by the boundary determination means on the image of the heart, and drawing on the display means;
An ultrasonic diagnostic apparatus comprising: An ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, and generates an image of the subject based on the reflected wave,
Search route setting means for setting a route starting from a predetermined point on the image;
Assign an opacity corresponding to the magnitude of the pixel value to each pixel of the image, emit a light ray from the start point along the path, and reduce the intensity of the light ray that attenuates according to the opacity every time it passes through each pixel. Ray tracing processing means to be obtained;
Boundary determination means for determining the position of the pixel where the intensity of the light beam obtained each time passing through each pixel is equal to or less than a predetermined intensity as the position of the boundary of the desired tissue;
Drawing means for drawing the position of the boundary determined by the boundary determination means on a display means;
An ultrasonic diagnostic apparatus comprising: An ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, generates an image of the heart based on the reflected wave, and displays the image on a display unit,
Search path setting means for setting a path starting from a predetermined point inside the image of the heart;
An opacity corresponding to the magnitude of the pixel value is assigned to each pixel of the heart image, a light ray is emitted from the starting point along the path, and is attenuated according to the opacity as it passes through each pixel. Ray tracing processing means for determining the intensity;
Boundary determining means for determining, as the position of the cardiac muscle boundary of the heart, the position of the pixel at which the intensity of the light ray obtained each time passing through each pixel is equal to or lower than a predetermined intensity;
Drawing means for superimposing the position of the myocardial boundary determined by the boundary determination means on the image of the heart, and drawing on the display means;
An ultrasonic diagnostic apparatus comprising: An ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, and generates an image of the subject based on the reflected wave,
Search route setting means for setting a route starting from a predetermined point on the image;
Cumulative addition processing means for accumulating and adding pixel values of each pixel along the path from the start point;
Boundary determination means for determining the position of the pixel where the value of the addition by the cumulative addition processing means is a predetermined value or more as the position of the boundary of the desired tissue;
Drawing means for drawing the position of the boundary determined by the boundary determination means on a display means;
An ultrasonic diagnostic apparatus comprising: An ultrasonic diagnostic apparatus that transmits an ultrasonic wave to a subject, receives a reflected wave from the subject, generates an image of the heart based on the reflected wave, and displays the image on a display unit,
Search path setting means for setting a path starting from a predetermined point inside the image of the heart;
Cumulative addition processing means for accumulating and adding pixel values of each pixel along the path from the start point;
Boundary determining means for determining the position of the pixel at which the value of the addition by the cumulative addition processing means is equal to or greater than a predetermined value as the position of the boundary of the myocardium of the heart;
Drawing means for superimposing the position of the myocardial boundary determined by the boundary determination means on the image of the heart, and drawing on the display means;
An ultrasonic diagnostic apparatus comprising: On the computer,
A search path setting function for capturing a medical image and setting a path starting from a predetermined point on the medical image;
The weighted pixels are obtained by sequentially changing the position of a predetermined range including a plurality of pixels along the path from the start point and assigning a predetermined weight to the pixel value of each pixel included in the predetermined range at each position. A weighted addition processing function for adding values;
A boundary determination function for determining a position of a predetermined range where the value of addition by the weighted addition processing function is a predetermined value or more as a position of a boundary of a desired tissue;
A drawing function for drawing the position of the boundary determined by the boundary determination function on a display means;
A medical image processing program characterized in that On the computer,
A search path setting function for capturing a medical image and setting a path starting from a predetermined point on the medical image;
An opacity corresponding to the magnitude of the pixel value is assigned to each pixel of the medical image, a light beam is emitted from the starting point along the path, and the light beam attenuates according to the opacity every time it passes through each pixel. Ray tracing processing function for
A boundary determination function for determining a position of a pixel where the intensity of the light beam obtained each time passing through each pixel is equal to or lower than a predetermined intensity as a boundary position of a desired tissue;
A drawing function for drawing the position of the boundary determined by the boundary determination function on a display means;
A medical image processing program characterized in that On the computer,
A search route setting function for setting a route starting from a predetermined point on the medical image;
A cumulative addition processing function for accumulating and adding pixel values of each pixel along the path from the start point;
A boundary determination function for determining the position of the pixel where the value of the addition by the cumulative addition processing function is a predetermined value or more as the position of the boundary of the desired tissue;
A drawing function for drawing the position of the boundary determined by the boundary determination function on a display means;
A medical image processing program characterized in that

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