JP2010131201A - Device, method and program for detecting anatomical feature point of human body structure - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To execute diagnosis with higher precision by improving reproducibility of the position of an anatomical feature point of a human body structure such as the femoral head center in a medical image. <P>SOLUTION: This device for detecting an anatomical feature point of the human body structure includes: an edge detecting section which detects an edge expressing the profile shape of the human body structure from a processing object image including the human body structure; an approximation section approximating the edge expressing the profile shape of the human structure with a closed curve or a closed region; a feature point detecting section detecting the center of gravity of the closed curve or the closed region as the anatomical feature point of the human body structure; and a display section displaying the detection results, the edge expressing the profile shape of the human body structure, and/or the closed curve or the closed region obtained by the approximation section and/or the anatomical feature point. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an apparatus and method for detecting an anatomical feature point of a human body structure, and a program, and more particularly to a measurement support technique in orthopedics for detecting the femoral head center.

  Conventionally, diagnosis of diseases such as osteoarthritis in a hip joint or a knee joint has been performed mainly by X-ray images. At this time, in order to make a doctor's examination / judgment more accurate, it is necessary to provide objective diagnosis information on the position of anatomical feature points such as the femoral head center.

  On the other hand, conventionally, for example, an image obtained by imaging a diagnosis target such as the pelvis is displayed on the display unit, and for example, a reference line for measuring body distortion and an object such as a parallel line for drawing the object are drawn. Information is input from the input unit, this object is drawn on the image displayed on the display unit, a value indicating a geometric relationship between the drawn objects is calculated, and used for a doctor's diagnosis Is known (see, for example, Patent Document 1).

Here, the input information input from the input unit is a point on the image manually input by a user (doctor or the like), and the object is drawn using the position information of the point input by the user as it is.
JP 2007-151742 A

  However, for example, one of the evaluation values used in the examination of the hip joint region is the CE edge (Center Edge Angle), which is based on positional information such as the femoral head center, the outer end of the acetabulum, and the lower left and right tear marks. Of the positional information for calculating the CE angle, the femoral head center is defined as the center of a certain structure. Therefore, there is no mark for indicating the position on the image. As described above, in the method in which the user manually inputs the position information, the position of the femoral head center and the like varies depending on the input user and the measurement timing, etc., and accurate diagnosis cannot be performed. is there.

  The present invention has been made in view of such circumstances, and improves the reproducibility of the position of anatomical feature points of a human body structure such as the femoral head center in a medical image, thereby enabling a more accurate diagnosis. An object of the present invention is to provide an anatomical feature point detection apparatus, method, and program for a human body structure.

  In order to achieve the object, an invention according to claim 1 is directed to an edge detection unit that detects an edge representing a contour shape of a human body structure from a processing target image including the human body structure, and a contour shape of the human body structure. An approximation unit that approximates an edge representing a closed curve or a closed region, a feature point detection unit that detects a centroid of the closed curve or closed region as an anatomical feature point of the human body structure, and the human body that is the detection result A human body comprising: an edge representing a contour shape of a structure and / or a display section for displaying the closed curve or closed region obtained by the approximating section and / or the anatomical feature point An apparatus for detecting an anatomical feature point of a structure is provided.

  Thereby, the variation when the user directly inputs the anatomical feature points of the human body structure can be suppressed, and the reproducibility can be improved.

  In addition, according to a second aspect of the present invention, the display unit displays the detection result so as to overlap the processing target image.

  In this way, the success or failure of the detection result can be confirmed by displaying the detection result of the anatomical feature point of the human body structure superimposed on the processing target image.

  Moreover, as shown in claim 3, the anatomical feature point detection device for a human body structure according to claim 1 or 2, wherein the display unit displays the processing target image and the displayed processing. Input receiving means for receiving an input of a predetermined point in the human body structure in the target image is provided, and an edge representing the contour shape of the human body structure is detected based on the predetermined point.

  As described above, it is possible to automatically detect an edge representing the contour shape of the human body structure by simply designating an arbitrary point in the human body structure.

  According to a fourth aspect of the present invention, in the anatomical feature point detecting device for a human body structure according to the third aspect, the predetermined point that receives input by the input receiving means is the anatomical feature point. The edge detecting unit is a radial straight line centered on the substantially identical point input into the human body structure in the displayed processing target image, and the other edge on the straight line. A point where the pixel density changes more greatly than a point is detected as a point constituting an edge representing the contour shape of the human body structure.

  Moreover, as shown in claim 5, in the anatomical feature point detection device for a human body structure according to claim 3, the predetermined point that receives input by the input receiving means is an outline shape of the human body structure. One or more points representing the edge, and one or more points representing the edge are used to detect an edge representing the contour shape of the human body structure.

  According to a sixth aspect of the present invention, the edge detection unit automatically detects an edge representing the contour shape of the human body structure from the processing target image.

  In this way, for example, by using a known edge detection technique in image processing, an edge representing the contour shape of a human body structure can be detected completely automatically.

  According to a seventh aspect of the present invention, the approximating unit approximates the edge with the closed curve or the closed region based on one or more points received from the input receiving unit.

  In this way, the user can semi-automatically detect the edge by inputting a plurality of points on the edge from the input means.

  Moreover, as shown in claim 8, the anatomical feature point detection device for a human body structure according to any one of claims 1 to 7, further comprising: recalculation of the closed curve or closed region and the anatomy Means for instructing re-detection of a characteristic feature point, and in response to an instruction from the means for instructing re-calculation and re-detection, the approximating unit performs re-calculation of the closed curve or closed region, and the feature point detecting unit The anatomical feature point is redetected based on the recalculated closed curve or closed region.

  As described above, the detection accuracy can be further improved by correcting the detection result as necessary.

  Further, as shown in claim 9, when the anatomical feature point detection device for a human body structure according to claim 8 further comprises an input receiving means for receiving an input of a predetermined point, the approximating unit Is characterized in that the recalculation of the closed curve or closed region is performed using the points on the edge that are added or modified by receiving an input from the input receiving means.

  As described above, when the detection result is corrected, the detection accuracy can be further increased by manual input by the user.

  According to a tenth aspect of the present invention, the closed curve is an ellipse.

  In this way, by using an ellipse as a closed curve that approximates an edge, it becomes easy to calculate subsequent anatomical feature points by using the display of the equation.

  The anatomical feature point may be a femoral head center point.

  Thereby, especially this invention can be applied suitably to the disease in a hip joint.

  Similarly, in order to achieve the object, the invention according to claim 12 includes a step of detecting an edge representing a contour shape of a human body structure from a processing target image including the human body structure, A step of approximating an edge representing a contour shape with a closed curve or a closed region, a step of detecting a centroid of the closed curve or the closed region as an anatomical feature point of the human body structure, and the human body structure which is the detection result And a step of displaying the closed curve or the closed region obtained by the approximation unit and / or the anatomical feature point. An anatomical feature point detection method is provided.

  Thereby, the variation when the user directly inputs the anatomical feature points of the human body structure can be suppressed, and the reproducibility can be improved.

  According to a thirteenth aspect of the present invention, the displaying step displays the detection result so as to overlap the processing target image.

  In this way, the success or failure of the detection result can be confirmed by displaying the detection result of the anatomical feature point of the human body structure superimposed on the processing target image.

  Moreover, as shown in claim 14, in the anatomical feature point detection method for a human body structure according to claim 12 or 13, wherein the displaying step displays the processing target image, and further the display A step of inputting a predetermined point into the human body structure in the processed image to be processed, wherein the step of detecting the edge includes a predetermined point input into the human body structure in the displayed processing target image A point where the pixel density changes on a radial line centered on the line is larger than other points on the line as a point constituting an edge representing the contour shape of the human body structure. And

  As a result, it is possible to automatically detect an edge representing the contour shape of the human body structure by simply designating an arbitrary point in the human body structure.

  According to a fifteenth aspect of the present invention, the step of detecting the edge automatically detects an edge representing a contour shape of the human body structure from the processing target image.

  Thereby, for example, by using an edge detection technique in known image processing, an edge representing the contour shape of the human body structure can be detected completely automatically.

  Further, according to claim 16, in the approximating step, the edge is approximated by the closed curve or the closed region based on the point on the detected edge based on the point input in the inputting step. It is characterized by doing.

  Thus, the edge can be detected semi-automatically by the user inputting a plurality of points on the edge from the input means.

  Moreover, as shown in claim 17, the anatomical feature point detection method for a human body structure according to any one of claims 14 to 16, further comprising a step of instructing recalculation of the closed curve or the closed region. And the step of approximating recalculates the closed curve or closed region based on the recalculation instruction, and the step of detecting the feature point includes the recalculated closed curve or closed region. The anatomical feature points are redetected based on the above.

  Thereby, the detection accuracy can be further improved by correcting the detection result as necessary.

  Further, according to the present invention, the approximating step performs the recalculation of the closed curve or closed region by using the points on the edge added in the inputting step.

  As described above, when the detection result is corrected, the detection accuracy can be further increased by manual input by the user.

  According to a nineteenth aspect of the present invention, the closed curve is an ellipse.

  In this way, by using an ellipse as a closed curve that approximates an edge, it becomes easy to calculate subsequent anatomical feature points by using the display of the equation.

  The anatomical feature point may be the femoral head center.

  Thereby, especially this invention can be applied suitably to the disease in a hip joint.

  Similarly, in order to achieve the object, the invention according to claim 21 detects the edge representing the contour shape of the human body structure from the processing target image including the human body structure, A step of approximating an edge representing a contour shape with a closed curve or a closed region; a step of detecting a centroid of the closed curve or closed region as an anatomical feature point of the human body structure; and the human body structure which is the detection result A method for detecting an anatomical feature point of a human body structure comprising: an edge representing a contour shape of the human body and / or a step of displaying the closed curve or the closed region obtained by the approximation unit and / or the anatomical feature point A program characterized by causing a computer to execute is provided.

  As described above, according to the present invention, variation when a user directly inputs anatomical feature points of a human body structure can be suppressed, and reproducibility thereof can be improved.

  Hereinafter, an apparatus and method for detecting an anatomical feature point of a human body structure and a program according to the present invention will be described in detail with reference to the accompanying drawings.

  FIG. 1 is a block diagram showing a schematic configuration of an embodiment of an anatomical feature point detection apparatus for a human body structure according to the present invention.

  As shown in FIG. 1, an anatomical feature point detection apparatus 1 (hereinafter simply referred to as a feature point detection apparatus 1) for a human body structure according to this embodiment mainly includes an image input unit 10, an image processing unit 12, It comprises an approximation unit 14, a feature point detection unit 16, a measurement value calculation unit 18, an information input unit 20, and a display unit 22.

  The image input unit 10 inputs X-ray image data obtained by imaging a patient's examination site. The method of inputting X-ray image data to the image input unit 10 is not particularly limited.

  For example, the X-ray image data may be obtained as a radiographic image (CR image) including an image of a bone part (for example, a femur) using a CR (Computed Radiographic) system. That is, in an imaging apparatus, X-rays emitted from an X-ray tube are irradiated toward a patient as a subject, and X-rays transmitted through the subject are incident on an imaging plate having a stimulable phosphor to transmit a transmitted radiation image. May be accumulated and recorded as energy information, and the transmitted radiation image may be read from the imaging plate on which the transmitted radiation image is accumulated and recorded and input to the image input unit 10.

  The image input unit 10 may input X-ray image data from a digital X-ray imaging apparatus equipped with an FPD (Flat-Panel Detector), or X-ray image data from an image server via a network. X-ray image data may be input from a recording medium such as a CD-ROM.

  The image processing unit 12 receives the X-ray image data input from the image input unit 10 and performs predetermined image processing on the X-ray image data. As will be described in detail later, for example, an edge of a human body structure such as a femoral head A detection process is performed.

  The approximating unit 14 approximates an edge of a human body structure such as a femoral head detected by the image processing unit 12 with a certain curve (a closed curve or a part of a closed curve). As will be described in detail later, for example, in the case of a femoral head, an ellipse is most preferably used as a closed curve that approximates the edge of the head.

  The feature point detection unit 16 detects anatomical feature points of the human body structure. When the approximating unit 14 approximates the edge of the human body structure with a certain closed curve, for example, the anatomical feature point is detected by obtaining the center of gravity of the region surrounded by the closed curve. As will be described in detail later, in the case of the femoral head, the head center is detected as an anatomical feature point. For example, when the head is approximated by an ellipse, the center (center of gravity) of the ellipse is detected as the head center.

  The measurement value calculation unit 18 calculates a predetermined measurement value of the human body structure by using one candidate measurement point. For example, in the case of a hip joint, the predetermined measurement value includes a CE angle (Center Edge Angle), a Sharp angle, an AHI (Acetabular Head Index), and the like.

  The information input unit 20 is configured such that the user views the image displayed on the display unit 22 and inputs a point that seems to be a point on the edge of the human body structure to the image processing unit 12, Input a point that seems to be an anatomical feature point roughly, or if the approximation result displayed on the display unit 22 is not expected to the approximating unit 14, instructs the approximation to be performed again, Various other instructions for the system are input. The information input unit 20 is configured by an operation member for normal input such as a keyboard and a mouse, for example, but is not limited thereto.

  The display unit 22 has a display screen such as an LCD, and displays a medical image such as an X-ray image input from the image input unit 10 and subjected to predetermined processing by the image processing unit 12. On the display screen of the display unit 22, a closed curve that approximates the edge of the human body structure detected by the approximation unit 14, an anatomical feature point of the human body structure detected by the feature point detection unit 16, and the like are further displayed. Overlaid on the display. The display unit 22 displays the measurement value calculated by the measurement value calculation unit 18.

  A user such as a doctor can make a diagnosis by looking at the display screen of the display unit 22. Although not shown, the feature point detection apparatus 1 is a printer that prints out an image or the like displayed on the display screen, a storage device that stores various data, or a recording that records these data on various recording media. Preferably means are provided.

  Hereinafter, the operation of the present embodiment will be described in detail.

  FIG. 2 is a flowchart showing a process flow of the human body anatomical feature point detection method according to the present embodiment. For example, a case where the center of the femoral head is detected from an X-ray image of a hip joint will be described as an example.

  First, in step S100 in FIG. 2, a measurement target image is input from the image input unit 10. As described above, there are various methods for inputting the image data, and the method is not particularly limited. The input measurement target image (X-ray image data) is sent to the image processing unit 12, subjected to predetermined image processing, and displayed on the display screen of the display unit 22.

  FIG. 3 shows an example of the measurement target image displayed on the display screen. As shown in FIG. 3, the measurement target image that has just been input is a hip joint front image in which the femoral head is shown.

  Next, in step S110, the image processing unit 12 detects the femoral head edge.

  Therefore, for example, as shown in FIG. 4A, an image obtained by cutting out a local region in which the femoral head is captured is displayed on the display unit 22. There are various methods for creating such a local region image. For example, there is a method in which a rough head center position is input from the information input unit 20 and the vicinity thereof is cut out.

  Further, there are various methods for detecting the edge of the bone head from an image obtained by cutting out the local region of the bone head as shown in FIG. 4A, and the method is not particularly limited. As one method, for example, as shown in FIG. 4B, a half line D is drawn radially around an arbitrary point such as a rough center point C in the bone head, and the concentration change on the half line D is changed. A large point E may be searched and the point E may be used as an edge. At this time, the user inputs the rough center point or arbitrary point in the bone head from the information input unit 20.

  Alternatively, a method of extracting edges by applying a general edge extraction filter such as a Sobel filter or a Laplacian filter to the image of FIG.

  Next, in step S120 in FIG. 2, the edge obtained above is approximated by a closed curve. In particular, an ellipse is used here as a closed curve that approximates an edge, but other curves may be used.

  FIG. 5 shows a method of approximating an edge with an ellipse.

  First, as shown in FIG. 5A, a plurality of points E1 (x1, y1), E2 (x2, y2), E3 (x3, y3),..., En on the edge Ed detected above. The user specifies (xn, yn) from the information input unit 20.

  Note that these points are not designated on the edge Ed as described above, but the user can look at the image displayed on the display unit 22 and detect the edge candidate points from the information input unit 20 without detecting the edge Ed. You may enter as

  An expression of an ellipse that approximates the edge Ed (or an ellipse on which an edge candidate point rides) is given as follows.

{(X−xc) cos θ + (y−yc) sin θ} ² / a ²
+ {(X−xc) sin θ− (y−yc) cos θ} ² / b ² −1 = 0
Here, as shown in FIG. 5C, (xc, yc) is the coordinates of the center of the ellipse, a is the major axis, b is the minor axis, and θ is the rotation angle of the major axis and minor axis around the center. ing. In FIG. 5C, for the sake of explanation, the ellipse is considerably deformed and displayed for easy understanding, but the actual approximate ellipse has a shape that is very close to a circle.

  Let the left side of the above expression be f (xc, yc, θ, a, b, x, y).

  Then, the following equation is calculated for the point Ei (xi, yi) (i = 1,..., N) on each edge.

g (xi, yi) = √ [| f (xc, yc, θ, a, b, xi, yi) |]
Here, the symbol | * | is the absolute value of *, and √ [*] represents the square root of [*].

  Here, Thr is set as a predetermined threshold value, and the number N of points (or edge candidate points) Ei (xi, yi) on the edge satisfying g (xi, yi) <Thr is calculated.

  If the point Ei (xi, yi) is on the ellipse, f (xc, yc, θ, a, b, x, y) = 0, so g (xi, yi) = 0. In general, the value of g (xi, yi) represents the deviation of the point Ei (xi, yi) from the circumference of the ellipse. The larger the number N of points at which this is smaller than the predetermined threshold Thr, the larger the ellipse f ( xc, yc, θ, a, b, x, y) = 0 is a good approximation of the edge Ed.

  Therefore, the number N of points Ei (xi, yi) where g (xi, yi) <Thr, the value obtained by dividing the number N by the area of the ellipse, and g (xi, yi) (i = 1 to N) The sum of numbers multiplied by the reciprocal of the distance from the approximate ellipse is calculated as an approximate evaluation value.

  Then, an ellipse that approximates the edge Ed as shown in FIG. 5B is obtained by searching for a parameter that maximizes the evaluation value while changing each parameter such as xc, yc, θ, a, and b. Ep is detected.

  Here, the threshold value Thr is not particularly limited. For example, the threshold value Thr may be 5% to 10% of the major axis or minor axis of the ellipse.

  Next, in step S130 of FIG. 2, the center point of the bone head is calculated. As shown in FIG. 5 (b) above, since the ellipse Ep approximating the edge Ed of the head is detected, the center point C of the head is set as the center of the approximate ellipse Ep (the same as the center of gravity). Calculated.

  Next, in step S140, these detection results are displayed overlaid on the display screen image of the display unit 22.

  Next, in step S150, the user looks at the result displayed on the display unit 22 and determines whether the approximate ellipse is acceptable. If the result is satisfactory, the head center point detection process is terminated. If there are a large number of points Ei (xi, yi) on the edge that are greatly deviated from the approximate ellipse Ep detected above, the approximation result is corrected in the next step S160.

  That is, the point on the contour of the bone head region that should be passed on the display screen of the display unit 22 is designated from the information input unit 20. For example, you may click with a mouse | mouth etc. Then, while changing the parameters xc, yc, θ, a, and b again so that the evaluation value becomes higher as it passes closer to the point, the evaluation standard of the approximate ellipse is changed and recalculated. As a new evaluation value, for example, a value obtained by dividing the evaluation value calculated above by dividing the distance between the currently specified point and the approximate ellipse can be considered. Let the ellipse with the maximum evaluation value be a new approximate ellipse.

  When a new approximate ellipse is detected, the head center is detected as the center of the approximate ellipse in step S170, and the result is displayed again in step S180.

  In the case of approximating an edge with an ellipse in this way, the approximation accuracy may be increased by gradually increasing the resolution from a low-resolution image.

  In the example described above, the user designates a point that seems to be a rough center point in the bone head or an arbitrary point, and then automatically draws a half line radially from that point and approximates it with an ellipse. The edge may be approximated by a closed curve other than an ellipse. In this case, the head center is detected as the center of gravity of the closed region surrounded by the closed curve. Alternatively, the detection may be performed fully automatically until the center of the head is calculated by ellipse approximation from the edge detection and the center of the head is calculated. At this time, the edge may be approximated by a closed curve other than an ellipse, and the center of gravity of the closed region surrounded by the closed curve may be automatically calculated.

  Alternatively, without automatically approximating with a closed curve in this way, after the user manually inputs a plurality of candidate points on the edge to form an approximate shape of the edge, the coordinates of that point on the image are automatically obtained and A so-called semi-automatic method for detecting the center of the head as the center of gravity of the coordinates may be used.

  Further, when the edge Ed of the femoral head does not exist for the reason that the femoral side of the femoral head has no edge candidate point, as shown by the broken line 30 in FIG. 6A, the edge Ed is shown in FIG. 6B. As described above, the portion without the edge Ed candidate point is replaced with the straight line L, and the head Ed is constituted by a part of the ellipse Ep and the straight line L.

  As described above, when the bone head region is a region surrounded by a part of the ellipse Ep and the straight line L, the center (center of gravity) of this region is considered to be shifted from the center C of the approximate ellipse Ep obtained above. . In this case, for example, the point C ′ slightly shifted on the short axis from the center C of the approximate ellipse Ep is considered to be the center of the bone head. This point is calculated, for example, as the center of gravity of the region surrounded by a part of the approximate ellipse Ep and the straight line L. Alternatively, the amount of shift of the center on the axis of the ellipse may be determined from the ratio of the length of the straight line L to a part of the approximate ellipse Ep (discontinuity of the ellipse Ep).

  As described above, in this embodiment, the shape (edge) of the femoral head is approximated by a closed curve (ellipse) or a part thereof or a closed region as an example of a human body structure, and the region (closed region) surrounded by the closed curve is approximated. The center of gravity is detected as the center of the human body structure. The detection result is displayed as an overlay on the input image.

  When the femoral head center point C is detected as described above, the measurement value calculation unit 18 calculates the CE angle using this. That is, as shown in FIG. 3, the CE angle is an angle formed by a straight line orthogonal to a straight line connecting the left and right tear mark lower ends P1 and P2 and a straight line connecting the acetabular outer end point Q and the femoral head center point C. Calculated as α.

  Therefore, according to this embodiment, since the edge is approximated and the center is detected based on the edge, the case where the user directly inputs the center of the human body structure (femoral head) as in the conventional case. In comparison, variations in the center point position due to manual input for each user can be suppressed.

  As a result, since the reproducibility of the femoral head center point position is improved, the reproducibility of the CE angle measurement is also improved, and a more accurate diagnosis is possible.

  Furthermore, since the approximate shape of the human body structure and its center point are overlaid on the input image, the success or failure of the center point detection can be confirmed, so the center point detection accuracy can be improved by correcting the center point detection as necessary. This can be further improved.

  Further, the anatomical feature point detection apparatus for a human body structure according to the present embodiment is controlled by a program stored in a memory attached to a control unit (not shown). That is, a program that executes a method for detecting an anatomical feature point of a human body structure is read from the memory by the control unit, and, for example, the femoral head edge is detected from an X-ray image of a hip joint, and the center of the femoral head is detected. Is detected.

  In addition, this program is not limited to what is stored in the memory attached to a control part in this way, For example, the memory comprised so that this program can be attached or detached to this feature point detection apparatus, such as a PC card and CD-ROM The information may be recorded on a medium (removable medium) and read into the apparatus via an interface corresponding to the removable medium.

  The human body structure anatomical feature point detection apparatus and method and the program according to the present invention have been described in detail above, but the present invention is not limited to the above examples, and the scope of the present invention is not deviated. Of course, various improvements and modifications may be made.

It is a block diagram which shows schematic structure of one Embodiment of the anatomical feature point detection apparatus of the human body structure which concerns on this invention. It is a flowchart which shows the flow of a process of the anatomical feature point detection method of the human body structure which concerns on this embodiment. It is explanatory drawing which shows the example of the measurement object image displayed on the display screen. (A) is explanatory drawing which shows the image which cut out the local area | region where the femoral head displayed on the display part was imaged, (b) is explanatory drawing which shows an example of edge detection. (A)-(c) is explanatory drawing which shows the method of approximating an edge with an ellipse. (A), (b) is explanatory drawing which shows the detection method of the center at the time of approximating an edge using a part of ellipse.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Anatomical feature point detection apparatus of a human body structure, 10 ... Image input part, 12 ... Image processing part, 14 ... Approximation part, 16 ... Feature point detection part, 18 ... Measurement value calculation part, 20 ... Information input part , 22 ... display section

Claims (21)

An edge detection unit for detecting an edge representing the contour shape of the human body structure from the processing target image including the human body structure;
An approximation unit that approximates an edge representing the contour shape of the human body structure with a closed curve or a closed region; and
A feature point detection unit for detecting the centroid of the closed curve or closed region as an anatomical feature point of the human body structure;
A display unit for displaying the edge representing the contour shape of the human body structure as the detection result and / or the closed curve or the closed region obtained by the approximation unit and / or the anatomical feature point;
An apparatus for detecting an anatomical feature point of a human body structure, comprising:   The said display part displays the said detection result on the said process target image, and displays the anatomical feature point detection apparatus of the human body structure of Claim 1 characterized by the above-mentioned. An apparatus for detecting an anatomical feature point of a human body structure according to claim 1 or 2,
The display unit displays the processing target image,
Input receiving means for receiving an input of a predetermined point in the human body structure in the displayed processing target image;
An apparatus for detecting an anatomical feature point of a human body structure, wherein an edge representing a contour shape of the human body structure is detected based on the predetermined point. In the anatomical feature point detection apparatus for a human body structure according to claim 3,
The predetermined point for receiving input by the input receiving means is substantially the same point as the anatomical feature point,
The edge detection unit has a pixel density larger than other points on the radial line centered on a substantially same point input into the human body structure in the displayed processing target image. An apparatus for detecting an anatomical feature point of a human body structure, wherein a changing point is detected as a point constituting an edge representing an outline shape of the human body structure. In the anatomical feature point detection apparatus for a human body structure according to claim 3,
The predetermined point for receiving input by the input receiving means is one or more points representing an edge representing the contour shape of the human body structure,
An apparatus for detecting an anatomical feature point of a human body structure, wherein an edge representing an outline shape of the human body structure is detected by using one or more points representing the edge.   The anatomical feature point detection of a human body structure according to claim 1 or 2, wherein the edge detection unit automatically detects an edge representing an outline shape of the human body structure from the processing target image. apparatus.   The anatomy of a human body structure according to claim 3, wherein the approximating unit approximates the edge with the closed curve or a closed region based on one or more points received from the input receiving unit. Feature point detector.   The anatomical feature point detection device for a human body structure according to any one of claims 1 to 7, further comprising means for instructing recalculation of the closed curve or closed region and redetection of the anatomical feature point The approximating unit recalculates the closed curve or closed region according to an instruction from the recalculation and redetection instruction unit, and the feature point detecting unit performs the recalculated closed curve or closed region. An anatomical feature point detection device for a human body structure, wherein the anatomical feature point is redetected based on the above.   The anatomical feature point detection device for a human body structure according to claim 8, wherein the approximation unit further includes a recalculation of the closed curve or the closed region when the input unit receives an input of a predetermined point. An anatomical feature point detection device for a human body structure, wherein an input from the input receiving means is received and the points on the edge added or modified are used.   The anatomical feature point detection device for a human body structure according to any one of claims 1 to 9, wherein the closed curve is an ellipse.   The apparatus for detecting an anatomical feature point of a human body structure according to any one of claims 1 to 10, wherein the anatomical feature point is a femoral head center point. Detecting an edge representing a contour shape of a human body structure from a processing target image including the human body structure;
Approximating an edge representing the contour shape of the human body structure with a closed curve or a closed region;
Detecting a center of gravity of the closed curve or closed region as an anatomical feature point of the human body structure;
Displaying the edge representing the contour shape of the human body structure as the detection result and / or the closed curve or the closed region and / or the anatomical feature point obtained by the approximation unit;
An anatomical feature point detection method for a human body structure characterized by comprising:   The method of detecting an anatomical feature point of a human body structure according to claim 12, wherein the displaying step displays the detection result so as to overlap the processing target image.   The anatomical feature point detection method for a human body structure according to claim 12 or 13, wherein the displaying step displays the processing target image, and further the human body structure in the displayed processing target image. A step of inputting a predetermined point inside, and the step of detecting the edge is a radial straight line centered on the predetermined point input into the human body structure in the displayed processing target image, An anatomical feature of a human body structure, characterized in that a point whose pixel density changes more greatly than other points on the straight line is detected as a point constituting an edge representing the contour shape of the human body structure Point detection method.   The anatomical feature of a human body structure according to claim 12 or 13, wherein the step of detecting the edge automatically detects an edge representing an outline shape of the human body structure from the processing target image. Point detection method.   15. The approximating step is based on the point input in the inputting step, and approximates the edge with the closed curve or closed region based on a point on the detected edge. The anatomical feature point detection method of the described human body structure.   The anatomical feature point detection method for a human body structure according to any one of claims 14 to 16, further comprising a step of instructing recalculation of the closed curve or the closed region, and the approximating step includes: Based on the recalculation instruction, the closed curve or closed region is recalculated, and the feature point detecting step is configured to detect the anatomical feature point based on the recalculated closed curve or closed region. A method for detecting an anatomical feature point of a human body structure, characterized by redetection.   18. The anatomy of a human body structure according to claim 17, wherein the approximating step performs recalculation of the closed curve or closed region using the points on the edge added in the inputting step. Feature point detection method.   The anatomical feature point detection method for a human body structure according to any one of claims 12 to 18, wherein the closed curve is an ellipse.   The anatomical feature point detection method for a human body structure according to any one of claims 12 to 19, wherein the anatomical feature point is a femoral head center. Detecting an edge representing the contour shape of the human body structure from the processing target image including the human body structure;
Approximating an edge representing the contour shape of the human body structure with a closed curve or a closed region;
Detecting the closed curve or the center of gravity of the closed region as an anatomical feature point of the human body structure;
Displaying the edge representing the contour shape of the human body structure and / or the closed curve or region obtained by the approximation unit and / or the anatomical feature point as the detection result. A program for causing a computer to execute a method for detecting an anatomical feature point of a structure.

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