JP2012232061A - Method, program, and apparatus for specifying bone region - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method, a program, and an apparatus for specifying a bone region, which facilitate obtaining objective measurement data not depending on the operation of an operator.SOLUTION: A radiographic inspection apparatus 1 includes: a smoothing unit 5 for smoothing image data at least once and obtaining smoothed image data; a first binarization unit 7 for obtaining first binarized data obtained by binarizing the smoothed image data with a first threshold; a second binarization unit 9 for obtaining second binarized data obtained by binarizing the smoothed image data with a second threshold different from the first threshold; an outline extracting unit 11 for specifying the positions of two forked parts between fingers from the first binarized data; a bone extracting unit 13 for specifying the positions of two forked parts between bones from the second binarized data; and a centering unit 15 for setting a specific region surrounded by the positions of the two forked parts between the fingers and the positions of the two forked parts between the bones.

Description

  The present invention relates to a bone region specifying method, a bone region specifying program, and a bone region specifying device for specifying a bone region for radiographic image data.

  Conventionally, the MD method for measuring the bone mineral content at the midpoint of the second metacarpal bone using an X-ray image has been widely used. This is done by taking X-rays with the standard substance on the back of the hand, comparing the density of the transverse pattern passing through the midpoint of the second metacarpal bone with the standard substance, and converting it to the thickness of the standard substance. This is a method for calculating an index. Patent Document 1 listed below discloses a bone measuring apparatus that quantitatively measures the direction of the bone canal of a bone to be examined in order to improve the reproducibility of the measurement value. According to this bone measuring apparatus, a reference point is manually designated in the vicinity of the center of the bone canal at the center of the second metacarpal bone through an external input device for an image obtained by radiography, and the auxiliary that passes through the reference point Lines are automatically generated. Then, an observation area is set above the reference point with reference to the auxiliary line, and the angle of the auxiliary line is automatically adjusted so that the symmetry of the projection profile in the observation area is maximized. Further, based on the adjusted auxiliary line, the bone bottom and the bone head of the second metacarpal bone are manually measured through the external input device.

JP 2007-151609 A

  However, in the conventional bone measuring apparatus as described above, the reference point at the center of the second metacarpal bone is manually designated by the measurer, and the measurement target range is set based on the reference point. It becomes complicated and it is difficult to obtain objective measurement data.

  Therefore, the present invention has been made in view of such problems, a bone region specifying method, a bone region specifying program capable of easily obtaining objective measurement data that does not depend on the operation of the measurer, It is another object of the present invention to provide a bone region specifying device.

  In order to solve the above problems, a bone region specifying method of the present invention is a bone region specifying method for specifying a region including a metacarpal bone using image data obtained on the basis of a radiographic image. A smoothing step of performing at least one smoothing process to obtain at least one smoothed image data, and obtaining first binarized data obtained by binarizing the smoothed image data with a first threshold value A first binarization step, a second binarization step for obtaining second binarization data obtained by binarizing the smoothed image data with a second threshold different from the first threshold, The position of the first finger crotch between the first finger and the second finger and the position of the second finger crotch between the first finger and the third finger are A contour extraction step specified from the binarized data, a position of the first crotch portion between the first metacarpal bone bottom and the second metacarpal bone bottom, and the first A bone extraction step for identifying a position of the second bone crotch portion between the metacarpal bone bottom and the third metacarpal bone bottom from the second binarized data; a first finger crotch portion; An area setting step of setting a specific area surrounded by the position of the second finger crotch part and the positions of the first bone crotch part and the second bone crotch part.

  Alternatively, the bone region specifying program of the present invention is a bone region specifying program for specifying a region including a metacarpal bone using image data obtained on the basis of a radiographic image. Smoothing means for performing at least one smoothing process to obtain at least one smoothed image data; first to obtain first binarized data obtained by binarizing the smoothed image data with a first threshold value; Binarizing means, second binarizing means for obtaining second binarized data obtained by binarizing the smoothed image data with a second threshold different from the first threshold, first finger and first The position of the first finger crotch between the two fingers and the position of the second finger crotch between the first finger and the third finger are obtained from the first binarized data. Contour extracting means to be identified, a position of a first bone crotch between the first metacarpal bone bottom and the second metacarpal bone bottom, and A bone part extracting means for specifying the position of the second crotch part between the first metacarpal bone base and the third metacarpal bone base from the second binarized data, and the first finger crotch And a region setting means for setting a specific region surrounded by the positions of the first and second crotch parts and the positions of the first and second crotch parts.

  Alternatively, the bone region specifying device of the present invention is a bone region specifying device that specifies a region including a metacarpal bone using image data obtained based on a radiographic image, and is at least once for the image data. Smoothing means for performing smoothing processing to obtain at least one smoothed image data, and first binary data for obtaining first binarized data obtained by binarizing the smoothed image data with a first threshold value A second binarizing unit that obtains second binarized data obtained by binarizing the smoothed image data with a second threshold different from the first threshold; a first finger; The position of the first finger crotch between the two fingers and the position of the second finger crotch between the first finger and the third finger are obtained from the first binarized data. A contour extraction means to be identified; a position of the first crotch portion between the first metacarpal bone bottom and the second metacarpal bone bottom; and the first metacarpal bone bottom and third Bone part extraction means for specifying the position of the second bone crotch part between the metacarpal bone bottom and the second binarized data, and the positions of the first finger crotch part and the second finger crotch part And a region setting means for setting a specific region surrounded by the positions of the first bone crotch and the second bone crotch.

  According to such a bone region specifying method, a bone region specifying program, or a bone region specifying device, the smoothed image data obtained by smoothing the image data is binarized using two different threshold values, and the first and Second binarized data is generated, the positions of the first and second finger crotch portions are specified based on the first binarized data, and the first and second binarized data are determined based on the second binarized data. The position of the 2 bone crotch part is specified, and a specific region surrounded by the specified four positions is set. As a result, a region including the metacarpal bone of the first finger is stably and automatically set, and measurement data relating to various examinations for radiographic images such as bone mineral density measurement can be obtained based on the region. . As a result, objective measurement data can be easily acquired without requiring complicated operations.

  In the smoothing step, first smoothed image data obtained by performing smoothing processing once on the image data, and second smoothed image data obtained by performing smoothing processing once more on the first smoothed image data. In the first binarization step, the first smoothed image data is binarized to obtain the first binarized data, and in the second binarization step, the second binarization process It is preferable to obtain second binarized data by binarizing the smoothed image data. In this way, the position of the finger crotch is reliably detected from the contour of the skin, and the position of the bone crotch is reliably detected from the contour of the bone. It is set more stably.

  In the smoothing step, third smoothed image data obtained by performing smoothing processing once on the image data and fourth smoothed image data obtained by performing smoothing processing twice on the image data are obtained. In the first binarization step, the first smoothed image data is obtained by binarizing the third smoothed image data, and in the second binarization step, the fourth smoothed image is obtained. It is also preferable to obtain second binarized data by binarizing the data. In this case, the position of the finger crotch is reliably detected from the contour of the skin and the position of the bone crotch is reliably detected from the contour of the bone. Set stably.

  Further, in the smoothing step, fifth smoothed image data obtained by performing the smoothing process twice on the image data is obtained, and in the first binarizing step, the fifth smoothed image data is binarized. It is also preferable to obtain the first binarized data by performing the binarization process on the fifth smoothed image data in the second binarization step. It is. In this way, the position of the finger crotch and the position of the bone crotch are detected based on one smoothed image data, so the processing is simplified and the amount of calculation is reduced.

  Further, the outer shape extraction step includes the step of specifying the pixel position that protrudes most in the predetermined coordinate axis direction of the pixel group having the same value in the fixed region with respect to the first binarized data, and the first binarization. The process of tracking the position of the boundary of the pixel group from the pixel position for data, and extracting two positions in the tracking order from the boundary position, which are maximum values in the opposite direction to the predetermined coordinate axis direction, It is also preferable to include a step of determining the two extracted positions as the positions of the first finger crotch and the second finger crotch. If such a configuration is adopted, the tip position of the middle finger is specified based on the first binarized data, the contour of the finger is tracked from the tip position, and the first and second finger crotch portions are tracked from the tracking result. Since the position is determined, stable finger crotch detection is possible.

  Furthermore, the bone portion extraction step includes a step of setting all pixel values of peripheral pixels in the second binarized data to the first value, and a pixel value included in the second binarized data is the second value. Identifying a start point pixel closest to the corner of the peripheral pixel and setting the pixel value of the end point pixel adjacent to the pixel to the second value, and targeting the second binarized data The step of tracking the boundary of the pixel group having the second value from the start point pixel to the end point pixel, the step of extracting the position having the maximum value in the predetermined coordinate axis direction from the tracking result, It is also preferable to include a step of determining two positions selected based on the tracking order as the positions of the first bone crotch and the second bone crotch. In this case, the start point pixel and the end point pixel are set at the end of the pixel group including the hand bone in the second binarized data, and the outline of the pixel group is tracked using these pixels. Since the positions of the first and second bone crotch portions are determined, stable bone crotch detection is possible.

  According to the present invention, objective measurement data that does not depend on the operation of the measurer can be easily obtained.

1 is a functional block diagram showing a schematic configuration of an X-ray image inspection apparatus according to a preferred embodiment of the present invention. (A) is a figure which shows the image of the 1st smoothing image data produced | generated by the smoothing part of FIG. 1, (b) is the image of the 2nd smoothing image data produced | generated by the smoothing part of FIG. FIG. It is a figure which shows the image of the 1st binarization data produced | generated for 1st smoothing image data shown to Fig.2 (a). It is a figure which shows the image of the 2nd binarization data produced | generated for 2nd smoothing image data shown in FIG.2 (b). It is a flowchart which shows the procedure of the bone mineral content measurement process performed by the X-ray image inspection apparatus of FIG. It is a flowchart which shows the detailed procedure of the external shape extraction process performed by the external shape extraction part of FIG. It is a figure which shows the image of the image data of the process target of the external shape extraction part of FIG. It is a figure which shows the image of the image data of the process target of the external shape extraction part of FIG. It is a flowchart which shows the detailed procedure of the bone part extraction process performed by the bone part extraction part of FIG. It is a figure which shows the image of the image data of the process target of the bone part extraction part of FIG. It is a figure which shows the image of the image data of the process target of the bone part extraction part of FIG. It is a flowchart which shows the detailed procedure of the axis alignment process performed by the axis alignment process part of FIG. It is a figure which shows the image of the image data of the process target of the axis alignment process part of FIG. It is a figure which shows the image of the image data of the process target of the axis alignment process part of FIG. It is a figure which shows the image of the image data of the process target of the axis alignment process part of FIG. It is a figure which shows the image of the image data of the process target of the axis alignment process part of FIG. It is a figure which shows the image of the image data of the process target of the axis alignment process part of FIG. It is a figure which shows the image of the image data of the process target of the axis alignment process part of FIG. It is a flowchart which shows the detailed procedure of the metacarpal bone position estimation process performed by the metacarpal bone position estimation part of FIG. It is a figure which shows an example of the kernel of the filter used by metacarpal bone position estimation processing. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the image of the image data of the process target of the metacarpal bone position estimation part of FIG. It is a figure which shows the hardware constitutions of the computer for performing the program recorded on the recording medium. It is a perspective view of a computer for executing a program stored in a recording medium.

  Hereinafter, preferred embodiments of a bone region specifying method and a bone region specifying device according to the present invention will be described in detail with reference to the drawings. In the description of the drawings, the same or corresponding parts are denoted by the same reference numerals, and redundant description is omitted.

  FIG. 1 is a functional block diagram showing a schematic configuration of an X-ray image inspection apparatus 1 which is a bone region specifying apparatus according to a preferred embodiment of the present invention. The X-ray image inspection apparatus 1 shown in FIG. 1 is an information processing apparatus for acquiring image data obtained based on an X-ray transmission image and measuring the bone mineral content with reference to the image data. This image data is an X-ray transmission image obtained by simultaneously X-raying an aluminum standard substance formed so that its thickness changes in one direction and the hand of the subject to be inspected, in a digital format such as bitmap format or JPEG format. It is converted to data. The image data is input to the X-ray image inspection apparatus 1 via a communication network, a recording medium such as a CD-ROM, a DVD, and a semiconductor memory. Here, the image data is recorded on an imaging plate on which an X-ray transmission image is recorded by photographing an X-ray film on which the X-ray transmission image is captured with a digital camera or using a dedicated reading device (not shown). It is generated by obtaining a photostimulable fluorescent image by laser irradiation.

  As shown in FIG. 1, the X-ray image inspection apparatus 1 includes, as functional components, a shading correction unit 3, a smoothing unit (smoothing means) 5, a first binarization unit (first binary). 7), a second binarization unit (second binarization unit) 9, an outer shape extraction unit (outer shape extraction unit) 11, a bone part extraction unit (bone part extraction unit) 13, and an axial processing unit ( (Region setting means) 15, metacarpal bone position estimation unit 17, and measurement value calculation unit 19. Hereinafter, the function of each component will be described.

  The shading correction unit 3 performs shading correction on the input image data, and corrects luminance unevenness of the image data. Specifically, the shading correction unit 3 smoothes the pixel data by applying a 9 × 9 median filter to the image data, and calculates the average luminance value in the left and right fixed areas in the frame of the smoothed image data. Calculate each. Further, the shading correction unit 3 calculates a correction curve using the difference between the two calculated average luminance values, and applies the first shading correction to the entire smoothed image data using the correction curve. Then, the shading correction unit 3 samples the background region excluding the region of the hand and the standard material in the image data subjected to the shading correction as described above along the horizontal line and the vertical line, and based on the sampling value. The horizontal and vertical correction curves are calculated using a second-order least square method, and a shading correction image is generated using the calculated correction curves. The shading correction unit 3 obtains image data subjected to the second shading correction by subtracting the shading correction image from the image data subjected to the first shading correction.

The smoothing unit 5 receives the image data after shading correction from the shading correction unit 3 and performs a smoothing process on the image data. That is, the smoothing unit 5 performs noise removal by applying a 9 × 9 median filter to image data, and then applies a 9 × 9 average filter once to the image data. First smoothed image data subjected to the smoothing process is generated. Further, the smoothing unit 5 generates second smoothed image data that has been subjected to the smoothing process twice in total by applying the 9 × 9 average value filter to the first smoothed image data once more. 2A shows an example of the first smoothed image data generated by the smoothing unit 5, and FIG. 2B shows an example of the second smoothed image data generated by the smoothing unit 5. Show. As described above, in the two smoothed image data, pixel values are set for each coordinate determined by the coordinate axes X and Y along the frame, and the standard material arranged along the Y-axis direction at the center of the frame. And the left and right hand images H _L and H _R arranged so that the fingertip is directed in the −Y-axis direction with the reference material interposed therebetween. Moreover, as can be seen by comparing the two smoothed image data, in the first smoothed image data image H _L of the right and left _hands, the boundary between the portion and the background image of the skin of the H _R is appeared clearly . In contrast, the image H _L of the right and left hands in the second smoothed image _data, H boundary between the portion and the background image of the skin of the _R blurred by further smoothing process, the image H _L of the right and left _hands, H The boundary between _R 's hand bone and the skin portion appears more clearly. This is because the degree of reduction in the resolution of the image data changes depending on the number of times the smoothing unit 5 performs the smoothing process. Therefore, the image H _L of the right and left _hands, when specifying the position of the finger crotch part between the boundary between the portion and the background image of the skin of H _R between the finger and the finger, facilities at least one smoothing position of the bone crotch between the smoothed image data based on, also, the image H _L of the right and left _hands, from the boundary between the hand bones and parts of the skin of the H _R and metacarpal bottom and metacarpal bottom When specifying the smoothing image data, it is better to use smoothed image data that has been subjected to smoothing processing at least twice. In this case, the position of the finger crotch and the position of the bone crotch can be accurately specified.

The first binarization unit 7 uses the first threshold value V _TH1 set in advance for the first smoothed image data output from the smoothing unit 5, and sets the first pixel value of each coordinate. The binarization is performed by replacing the binarized data (first binarized data) according to the comparison result with the threshold value _VTH1 . Such first threshold value V _TH1, the image H _L of the right and left hands in the image _data, proper values, such as the skin portion of the H _R can from the background image embossed is configured preselected . FIG. 3 shows an example of the first binarized data generated for the first smoothed image data shown in FIG. In this case, is replaced pixel value area _{A 1} of the background image "0", the area _{A HL1, A HR1} of the image of the left and right hands to the pixel value "1".

The second binarization unit 9 targets the second smoothed image data output from the smoothing unit 5 and uses a second threshold value V _TH2 that is different from the preset first threshold value V _TH1. Then, binarization is performed by replacing the pixel value of each coordinate with binarized data (second binarized data) according to the comparison result with the second threshold value _VTH2 . Such second threshold V _TH2, the image H _L of the right and left hands in the image _data, a hand bone portions of H _R is an appropriate value that can be highlighted from the skin portion is set preselected . For example, when a negative image in which the pixel value increases in the order of the background region, the skin portion, and the hand bone portion is the target, the second threshold value V _TH2 is set to a value larger than the first threshold value V _TH1. The Conversely, when a positive image in which the pixel value decreases in the order of the background region, the skin portion, and the hand bone portion, the second threshold value V _TH2 is set to a value smaller than the first threshold value V _TH1. Is done. FIG. 4 shows an example of the second binarized data generated for the second smoothed image data shown in FIG. In this case is replaced by the background image and pixel values of the area A ₂ except for the hand bones of the left and right hand "0", the area A _HL2 of hand bone portions of the left and right _hands, A _HR2 pixel value "1" .

The outer shape extraction unit 11 targets the first binarized data output from the first binarization unit 7 between the second finger (index finger) of the left hand and the third finger (middle finger) of the left hand. The first finger crotch portion position P _F1 and the second finger crotch portion position P _F2 between the second finger (index finger) of the left hand and the first finger (thumb) of the left hand are specified. . In addition, the bone extraction unit 13 targets the second binarized data output from the second binarization unit 9 and uses the second metacarpal base of the left hand and the third metacarpal base of the left hand. the first and the position P _F3 bone crotch portion located between the position P _F4 of the second bone crotch portion located between the second metacarpal bone bottom and left of the first metacarpal bone bottom of the left hand Is identified.

The centering processing unit 15 includes a region surrounded by the two positions P _F1 and P _F2 specified by the contour extraction unit 11 and the two positions P _F3 and P _F4 specified by the bone extraction unit 13. Set. Further, the axis alignment processing unit 15 performs alignment of the second metacarpal bone of the left hand with respect to the set region in the image data that has been subjected to the shading correction by the shading correction unit 3.

  The metacarpal bone position estimation unit 17 refers to the image data that has been subjected to shading correction by the shading correction unit 3 on the basis of the axis that has been axised by the axising processing unit 15, and determines the top position of the second metacarpal bone. Estimate the bottom position. The top position of the second metacarpal means the position of the distal end (bone head) of the second metacarpal, and the bottom position of the second metacarpal refers to the proximal end (bone) of the second metacarpal. This means the position of the bottom.

The measurement value calculation unit 19 determines an intermediate point between the top position and the bottom position estimated by the metacarpal bone position estimation unit 17, and sets a rectangular analysis region centered on the intermediate point. Further, the measurement value calculation unit 19 reads several (30 to 40) projection profiles that intersect with the bone longitudinal direction of the analysis region from the image data that has been subjected to the shading correction by the shading correction unit 3. Then, the measurement value calculating unit 19 detects the offset amount G _S from the background pixel value between edge points of both ends in the projection profiles, distances D between the integrated value ShigumaG _S edge points of the detection value G _S Then, this value ΣG _S / D is further converted into the thickness of aluminum as a standard material and calculated as a bone density parameter used for bone mineral content evaluation. The measurement value calculator 19 outputs the calculated value ΣG _S / D to an external output device such as a display or a printer or external data.

  Next, the bone mineral content measuring method executed by the X-ray image inspection apparatus 1 of the present embodiment will be described, and the bone region specifying method of the present embodiment will be described in detail.

  FIG. 5 is a flowchart showing the procedure of the bone mineral content measurement process executed by the X-ray image inspection apparatus 1. First, when image data is input from the outside to the X-ray image inspection apparatus 1, the shading correction unit 3 performs shading correction on the image data (step S01). The shading-corrected image data is subjected to a smoothing process by the smoothing unit 5 to generate first smoothed image data and second smoothed image data (step S02). Thereafter, the first binarized unit 7 binarizes the first smoothed image data, thereby generating first binarized data (step S03). Further, the second binarized unit 9 binarizes the second smoothed image data, thereby generating second binarized data (step S04).

Next, the outer shape extraction unit 11 performs the outer shape extraction process on the first binarized data, thereby specifying the positions P _F1 and P _{F2 of} the first and second finger crotch portions. (Step S05). Further, the bone portion extraction unit 13 performs the bone portion extraction process on the second binarized data, thereby specifying the positions P _F3 and P _{F4 of} the first and second bone crotch portions. (Step S06). Thereafter, an area surrounded by the four positions P _F1 , P _F2 , P _F3 , and P _F4 is set in the image data that has been subjected to the shading correction by the axis alignment processing unit 15. An axising process for calculating the axis of the metacarpal bone is executed (step S07).

  Then, the metacarpal bone position estimating unit 17 estimates the top position and the bottom position of the second metacarpal bone by referring to the image data that has been subjected to the shading correction based on the centered axis (step). S08, metacarpal bone position estimation process). Thereafter, the measurement value calculation unit 19 sets an analysis region based on the midpoint between the top position and the bottom position in the image data that has been subjected to the shading correction, and by reading the pixel value of the analysis region, the bone density parameter is set. Calculated (step S09). Finally, the bone density parameter calculated by the measurement value calculation unit 19 is output to the outside (step S10).

  FIG. 6 is a flowchart showing a detailed procedure of the contour extraction process executed by the contour extraction unit 11, and FIGS. 7 to 8 are diagrams showing images of image data to be processed by the contour extraction unit 11.

In this outline extraction process, first, the upper left in the first binary data (hereinafter, + X-axis direction to the right direction, the + Y-axis direction and the downward direction.) Is rectangular fixing region A ₃ is set for ( step S101), in the fixed area _{a 3,} the coordinates of the uppermost pixel position a pixel value of "1" is searched as a front end position _{P 1} of the third finger (middle finger) (step S102, FIG. 7) . That is, the position P ₁ is searched as the pixel position most projecting in the -Y-axis direction of a region A _HL1 is a pixel group having the same pixel value of "1".

Next, the boundary of the pixel position of the region A _HL1 left hand image of the first binary data is, from the front end position P ₁ of the third finger is tracked clockwise, the index of the order of tracked position is tracked The information is temporarily stored together with the information (step S103, FIG. 8). Thereafter, determined from among the tracked boundary position, the maximum value and a position of the Y-axis direction is extracted in the order of tracing, those youngest number among the extracted position as the position P _F1 of the first finger crotch (Step S104). Furthermore, those Wakaban the second among the extracted position is determined as the position P _F2 of the second finger crotch (step S105).

  FIG. 9 is a flowchart showing a detailed procedure of the bone extraction process executed by the bone extraction unit 13, and FIGS. 10 to 11 are diagrams showing images of image data to be processed by the bone extraction unit 13. .

In this bone part extraction process, first, all the peripheral pixels along the frame in the second binarized data are set to the pixel value “0” (step S201). Then, the coordinates of the pixel value of "1" is located in the most lower left in the second binary data is identified as the position P ₂ of the start point pixel. The position P _2, of the pixels of the pixel value of "1" is identified by searching the closest to the peripheral edge pixels located in the lower left corner of the frame. Furthermore, the coordinates of pixels adjacent to the lower side of the starting pixel is identified as the position P ₃ of the end point pixel, the pixel values of the end pixel is set to "1" (step S202, FIG. 10). These positions P ₂ and P ₃ are used as a start point and an end point in the boundary tracking process of the region A _HL2 of the hand bone part.

Next, the pixel position of the boundary of the area A _HL2 of the left hand bone image having a pixel value "1" in the second binary data is, from the position P ₂ of the start point pixel to the position P ₃ of the end pixels clockwise The position of the tracked boundary line in the order of the fifth metacarpal, the fourth metacarpal, the third metacarpal, the second metacarpal, and the first metacarpal is It is temporarily stored together with the index information (step S203, FIG. 11 (a)). Thereafter, the tracked boundary position is smoothed with the coordinate values in the Y-axis direction (FIG. 11B). This smoothing is performed by moving average, and its window size is a fixed value.

Further, the positions of four points that are maximum values in the Y-axis direction are extracted from the positions of the smoothed boundary lines (step S204). Next, as the third in the order of tracking of the extracted position singled out, while being determined as the position P _F3 of the first bone crotch, exits select the fourth one in the order of track It is, is determined as the position _{P F4} of the second bone crotch (step S205). Here, when the position determination of the hip crotch portion fails in step S205, the process returns to the process of step S04 of FIG. 5 to change the second threshold value _VTH2 and repeat the second binarization process again. . In this case, if the second threshold value V _TH2 is changed with a predetermined change width and binarization data is generated up to a predetermined upper limit number of times, but the position determination of the bone crotch portion fails, the error processing is performed. Interrupted.

  FIG. 12 is a flowchart showing a detailed procedure of the axis alignment processing executed by the axis alignment processing unit 15, and FIGS. 13 to 18 are diagrams showing images of image data to be processed by the axis alignment processing unit 15.

  In this axial alignment process, first, a smoothing process is performed by applying a 9 × 9 median filter to image data that has been subjected to shading correction (step S301). Next, a 7 × 7 dynamic binarization process using a fixed threshold is performed on the image data (step S302, FIG. 13A). Next, the 5 × 5 median filter is applied to the dynamically binarized image data three times to perform smoothing processing on the image data (step S303, FIG. 13B).

Further, the four positions P _F1 , P _F2 , P _F3 , and P _F4 specified by the external extraction process (step S05 in FIG. 5) and the bone part extraction process (step S06) are included in the smoothed image data. It is set (step S304, FIG. 14). Then, after calculating the positions obtained by dividing the two points positions P _F2 and P _F4 and between the two points positions P _F1 and P _{F3 by} a fixed ratio (fixed ratio), the two calculated positions Are referred to toward the inner side of the frame along a line connecting the two positions, and positions P ₄ and P ₅ at which the pixel values change from “0” to “1” are searched as tracking start points (step S305). , FIG. 14). The pixel search direction at this time is inclined obliquely with respect to the X axis. Therefore, a position at which the pixel value changes from “1” to “0” from the first searched position toward the outside along the X axis so that the tracking start point can be applied as the start point of the 4-connected boundary search. It is preferable to search again and determine the position as a tracking start point.

Thereafter, the boundary lines of the images A _E1 and A _E2 of the left and right edge portions of the second metacarpal in the smoothed image data are tracked from the tracking start point (step S306, FIG. 15). At this time, the image A _{E1 at the} left edge is tracked clockwise, and the image A _E2 at the right edge is tracked counterclockwise. Furthermore, the point sequence of the boundary line of the tracked left edge is re-tracked from the end of the tracking sequence in reverse order to the tracking sequence, and the sequence of points L from the top position point P ₆ at which the Y coordinate is minimized to the tracking start point ₁ is specified (FIG. 16A). In addition, the point sequence of the tracked left edge boundary line is tracked from the top of the tracking order, and after searching for the bottom position point P ₇ where the Y coordinate is maximum, the sequence is reversed from the end of the boundary line sequence. re tracked, the point sequence L ₂ from the end to the point P ₇ of bottom position specified in (FIG. 16 (b)). Then, after the identified point sequences L ₁ and L ₂ are combined, the pixel data of each pixel at the upper and lower ends is deleted, so that a line outside the left edge portion of the second metacarpal is extracted. . Similarly, the line outside the right edge portion of the second metacarpal bone is extracted with the direction of tracking as the reverse rotation.

Next, the extracted lines L ₃ and L ₄ of the left and right edge portions are shaped (step S307). That is, the upper and lower end portions L ₅ and L ₆ are deleted, leaving the common range W ₁ in the Y-axis direction, so that both lines L ₃ and L ₄ have a common length in the Y-axis direction. (FIG. 17A). Furthermore, with respect to the point sequence constituting both lines L ₃ and L ₄ , the shaping process is performed so as to leave only the outermost point among the points of the same Y coordinate and delete the remaining points (FIG. 17 ( b)).

Further, the second metacarpal bone is centered based on the shaped lines L ₃ and L ₄ of the left and right edge portions (step S308, FIG. 18). Specifically, the midpoint between the lines L ₃ and L ₄ of the edge portion is calculated with each Y coordinate, and a point sequence composed of these midpoints is constructed. Thereafter, coefficients a and b are calculated by linear curve fitting based on the point sequence data, and a linear function y = ax + b that approximates the point sequence is derived. In the coordinate system of the image data, the direction below the Y axis is the direction in which the Y coordinate increases. Therefore, in order to prevent the inclination (coefficient a) from becoming infinite, the X axis and the Y axis are transposed to obtain the coefficients a, Calculation of b is performed.

  FIG. 19 is a flowchart showing a detailed procedure of the metacarpal bone position estimation process executed by the metacarpal bone position estimation unit 17, and FIG. 20 is a filter coefficient matrix used in the metacarpal bone position estimation process. FIGS. 21 to 28 are diagrams illustrating an example of a certain kernel, and FIGS. 21 to 28 are diagrams illustrating images of image data to be processed by the metacarpal bone position estimation unit 17.

  In this metacarpal bone position estimation process, first, the upper edge of the image data is emphasized by applying a 9 × 5 edge enhancement filter to the image data subjected to the shading correction (step S401, FIG. 21). FIG. 20 shows an example of a kernel that is a matrix of filtering coefficients of the 9 × 5 edge enhancement filter used at this time. Furthermore, the lower edge of the image data is enhanced by applying a 9 × 5 edge enhancement filter to the image data that has been subjected to the shading correction (step S401, FIG. 22). At this time, as the kernel of the 9 × 5 edge enhancement filter, a kernel obtained by inverting the sign of each coefficient in the kernel shown in FIG. 20 is used.

Next, 9 × 9 dynamic binarization processing is performed on the two image data subjected to the edge enhancement processing with an appropriate threshold value (fixed value) (step S402). Then, in the two image data subjected to the dynamic binarization processing, the pixel value in the common range W ₁ detected in step S307 is replaced with “0”, thereby the common range W in the image data. ₁ is cleared (step S403). Further, a smoothing process is performed by applying a 3 × 3 median filter to the two binarized image data (step S404, FIGS. 23A and 23B). Here, the median filter is applied once to the binarized image data (top position detection image data) with the upper edge enhanced, and the binarized image data (bottom position detection image with the lower edge enhanced). The median filter is applied twice to (data).

Thereafter, the top position of the second metacarpal bone is searched for the smoothed top position detection image data (step S405). Specifically, the search starting point to the intermediate line L ₇ of the common range W1 is set, the window range W ₂ of the number of fixed-pixel to the left of the axis L ₈ which is put the shaft in the axial centering process is set ( FIG. 24). Next, a pixel upward is searched along the window range W ₂ in the axial L _8, a position which varies from "0" to the pixel value "1" is searched. At this time, a range W _{4 obtained} by adding a range W ₃ having the same width as the common range W _{1 to} the upper half of the common range W ₁ is set as a search range, and when the end of the search range is reached, the searched pixel Are excluded from further processing. The position where the pixel value changes from “1” to “0” is stored in the projection list AR ₁ indicating a list of the positions, and the number of connected pixels in the horizontal direction is calculated by referring to the stored projection list AR _1. (FIG. 25). In this case, the consecutive number of pixels having a pixel value “1” adjacent to each other in the X-axis direction with the difference in the Y coordinate values being equal to or smaller than a certain value is calculated as the number of connected pixels.

Then, a large connected pixels of the connection number is searched from the axis L ₈ in the left direction, connected pixels AR ₂ is found first is selected among the number of connected pixels calculated. If there is a pixel on the axis L ₈ in the connected pixels AR _2, the position P ₈ is determined as the top position of the second metacarpal bone. On the other hand, connected pixels AR without pixel on the axis L ₈ is in _2, and, if Y coordinate value equivalence of pixels less than a predetermined number, the axis L with the same Y-coordinate value as a pixel closest to the axis L ₈ position _{P 9} on the ₈ is determined as the top position of the second metacarpal bone (Figure 26). This is because the number of sample points of the connected pixels is insufficient for the curve fitting process. Further, connected pixels AR without pixel on the axis L ₈ is in _2, and, if the Y-coordinate value equivalent of the pixel exceeds the predetermined number, the set of connected pixels are curve fitting a quadratic equation, calculation It is the position P ₁₀ of the intersection between the approximate curve C1 and axis L ₈ has is determined as the top position of the second metacarpal bone (Figure 27).

In the same manner as in the above procedure, the bottom position of the second metacarpal bone is searched for the smoothed bottom position detection image data (step S406). Specifically, the search starting point to the intermediate line L ₉ of the common range W1 is set, the window range W ₅ left fixed number of pixels of the axis L ₈ which is put the shaft in the axial centering process is set ( FIG. 28). Next, the pixel is searched downward along the axis L ₈ in the window range W _5, and the position where the pixel value changes from “1” to “0” is searched. At this time, a range W _{7 obtained} by adding a range W ₆ having the same width as the common range W _{1 to} the lower half of the common range W ₁ is set as a search range, and when the end of the search range is reached, the searched pixel Are excluded from further processing. The position where the pixel value changes from “1” to “0” is stored in the projection list AR ₃ indicating the position list, and the number of connected pixels in the horizontal direction is calculated by referring to the stored projection list AR _3. The

Then, a large connected pixels of the connection number is searched from the axis L ₈ in the left direction, connected pixels found first is selected among the calculated connected number of pixels. If there is a pixel on the axis L ₈ in the connected pixels AR _2, the position P ₈ is determined as a bottom position of the second metacarpal bone. On the other hand, when the pixel on the axis L ₈ is not in the connected pixels AR _2, the set of connected pixels are curve fitting by a linear equation, the position P ₁₁ of the intersection of the approximate line and the axis L ₈ calculated , Determined as the bottom position of the second metacarpal bone. At this time, if the calculated coefficient of the primary expression is positive, the first-side curve fitting is performed again by exchanging the head side and the end side of the X coordinate of the projection list. As a result, the coefficient of the linear expression is made negative.

  Hereinafter, a bone region specifying program that causes a computer to operate as the X-ray image inspection apparatus 1 will be described.

  The bone region specifying program according to the embodiment of the present invention is provided by being stored in a recording medium. Examples of the recording medium include a floppy (registered trademark) disk, a CD-ROM, a DVD, a ROM, or a recording medium, or a semiconductor memory.

  FIG. 29 is a diagram illustrating a hardware configuration of a computer for executing a program recorded in a recording medium, and FIG. 30 is a perspective view of the computer for executing a program stored in the recording medium. The computer includes various data processing devices such as a server device that includes a CPU and performs processing and control by software, and a personal computer.

  As shown in FIG. 29, the computer 30 includes a reading device 12 such as a floppy (registered trademark) disk drive device, a CD-ROM drive device, a DVD drive device, and a working memory (RAM) 14 in which an operating system is resident. , A memory 16 for storing a program stored in the recording medium 10, a display device 18 such as a display, a mouse 20 and a keyboard 22 as input devices, a communication device 24 for transmitting and receiving data and the like, and execution of the program CPU 26 for controlling the above. When the recording medium 10 is inserted into the reading device 12, the computer 30 can access the bone region specifying program stored in the recording medium 10 from the reading device 12. It becomes possible to operate as the line image inspection apparatus 1.

  As shown in FIG. 30, the bone region specifying program may be provided via a network as a computer data signal 41 superimposed on a carrier wave. In this case, the computer 30 can store the bone region specifying program received by the communication device 24 in the memory 16 and execute the bone region specifying program.

According to the X-ray image inspection apparatus 1 described above and the bone region specifying method using the same, a region including the second metacarpal bone is stably and automatically set, and bone mineral content is measured based on the region. Measurement data relating to various examinations for radiation images such as the above are obtained. As a result, objective measurement data can be easily obtained without requiring complicated operations such as manual setting of reference points. In particular, in this embodiment, based on the first binarized data generated from the first smoothed image data, the two finger crotch positions P _F1 and P _F2 are reliably detected from the skin contour. At the same time, based on the second binarized data generated from the second smoothed image data, the positions P _F3 and P _F4 of the bone crotch are reliably detected from the contour of the bone. The region including is set more stably.

  Further, according to the outer shape extraction process by the outer shape extraction unit 11, the tip position of the middle finger is specified based on the first binarized data, the contour of the finger is tracked from the tip position, and two results are obtained from the tracking result. Since the position of the finger crotch is determined, the finger crotch can be detected stably.

  Further, by the bone part extraction processing by the bone part extraction unit 13, the start point pixel and the end point pixel are set at the end of the pixel group including the hand bone in the second binarized data, and the pixel group is set using these pixels. Since the contours of the two bones are tracked and the positions of the two hips are determined from the tracking results, stable bone hips can be detected.

  In addition, this invention is not limited to embodiment mentioned above. That is, in the smoothing process of the above embodiment (step S02 in FIG. 5), instead of generating the first and second smoothed pixel data in series, the smoothing process is performed once on the image data. Third smoothed image data (smoothed image data corresponding to the first smoothed image data) is generated, and the fourth smoothed image data (second smoothed) is subjected to the smoothing process twice on the image data in parallel therewith. Smoothed image data corresponding to the smoothed image data) may be generated. In this case, in the first binarization process (step S03), the third smoothed image data is binarized, and in the second binarization process (step S04), the fourth smoothed image data is binarized. Is done. Even in this case, since the bone part is extracted based on the smoothed image data subjected to the smoothing process at least twice, the first bone crotch part and the second bone crotch part can be accurately identified. The region including the second metacarpal bone is stably set.

  Further, in the smoothing process of the above embodiment (step S02 in FIG. 5), instead of generating the first and second smoothed pixel data in series, the smoothing process is performed twice on the image data. Only the applied fifth smoothed image data (the smoothed image data corresponding to the second smoothed image data and the fourth smoothed image data) may be generated. In this case, in the first binarization process (step S03), the fifth smoothed image data is binarized, and in the second binarization process (step S04), the fifth smoothed image data is binarized. Is done. In this way, since the position of the finger crotch and the position of the bone crotch are detected based on one smoothed image data, the processing is simplified and the amount of calculation is reduced. In addition, since the bone part extraction is performed based on the smoothed image data subjected to at least two smoothing processes, the first bone crotch part and the second bone crotch part can be accurately identified. The area including the hand bone is set stably.

  In the X-ray image inspection apparatus 1 and the bone region specifying method using the same in the present embodiment, the region including the second metacarpal bone is automatically detected. Other areas such as (metacarpal bone of the third finger) and fourth metacarpal bone (metacarpal bone of the fourth finger) may be automatically detected.

  DESCRIPTION OF SYMBOLS 1 ... X-ray image inspection apparatus, 5 ... Smoothing part (smoothing means), 7 ... 1st binarization part (1st binarization means), 9 ... 2nd binarization part (2nd) , 11... Outer shape extraction unit (outer shape extraction unit), 13... Bone part extraction unit (bone part extraction unit), 15.

Claims (8)

A bone region specifying method for specifying a region including a metacarpal bone using image data obtained based on a radiographic image,
A smoothing step in which smoothing means performs at least one smoothing process on the image data to obtain at least one smoothed image data;
A first binarization step in which first binarization means obtains first binarized data obtained by binarizing the smoothed image data with a first threshold;
A second binarization step in which a second binarization unit obtains second binarization data obtained by binarizing the smoothed image data with a second threshold different from the first threshold; ,
The outer shape extraction means includes a position of the first finger crotch between the first finger and the second finger, and a position of the second finger crotch between the first finger and the third finger. An outer shape extraction step for specifying a position from the first binarized data;
The bone portion extraction means includes a position of the first crotch portion between the first metacarpal bone bottom and the second metacarpal bone bottom, and the first metacarpal bone bottom and the third metacarpal bone. A bone extraction step for identifying the position of the second bone crotch between the bottom and the second binarized data;
The region setting means sets a specific region surrounded by the positions of the first and second crotch portions and the positions of the first and second crotch portions. An area setting process;
A bone region specifying method comprising: In the smoothing step, first smoothed image data obtained by performing smoothing processing once on the image data and second smoothing obtained by performing smoothing processing once more on the first smoothed image data. To obtain the converted image data,
In the first binarization step, the first binarized data is obtained by binarizing the first smoothed image data,
In the second binarization step, the second binarized data is obtained by binarizing the second smoothed image data.
The bone region specifying method according to claim 1. In the smoothing step, third smoothed image data obtained by performing smoothing processing once on the image data, and fourth smoothed image data obtained by performing smoothing processing twice on the image data. Get,
In the first binarization step, the first binarized data is obtained by binarizing the third smoothed image data,
In the second binarization step, the second binarized data is obtained by binarizing the fourth smoothed image data.
The bone region specifying method according to claim 1. In the smoothing step, a fifth smoothed image data obtained by performing the smoothing process twice on the image data is obtained,
In the first binarization step, the first binarized data is obtained by binarizing the fifth smoothed image data,
In the second binarization step, the second binarized data is obtained by binarizing the fifth smoothed image data.
The bone region specifying method according to claim 1. The outer shape extraction step includes
Specifying the pixel position most protruding in the predetermined coordinate axis direction of the pixel group having the same value in the fixed region for the first binarized data;
Tracking the position of the boundary of the pixel group from the pixel position for the first binarized data;
Two positions having local maximum values in the opposite direction to the predetermined coordinate axis direction are extracted from the boundary positions in the tracking order, and the extracted two positions are the first finger crotch portion and the second finger position. Determining the position of the finger crotch of
The bone region specifying method according to any one of claims 1 to 4, characterized by comprising: The bone part extraction step includes
Setting all the pixel values of peripheral pixels in the second binarized data to the first value;
Among the pixels whose pixel values of the second binarized data are the second values, the start point pixel closest to the corner of the peripheral pixel is specified, and the pixel value of the end point pixel adjacent to the pixel is set as the first pixel value. Setting the value to 2;
Tracing the boundary of the pixel group having the second value from the start point pixel to the end point pixel for the second binarized data;
Extracting a position having a maximum value in a predetermined coordinate axis direction from the result of the tracking;
Determining two positions selected based on the order of tracking among the extracted positions as the positions of the first bone crotch and the second bone crotch;
The bone region specifying method according to any one of claims 1 to 5, characterized by comprising: A bone region specifying program for specifying a region including a metacarpal bone using image data obtained based on a radiographic image,
Computer
Smoothing means for performing at least one smoothing process on the image data to obtain at least one smoothed image data;
First binarization means for obtaining first binarized data obtained by binarizing the smoothed image data with a first threshold;
Second binarization means for obtaining second binarized data obtained by binarizing the smoothed image data with a second threshold different from the first threshold;
The position of the first finger crotch between the first finger and the second finger and the position of the second finger crotch between the first finger and the third finger are An external shape extracting means for specifying the binarized data of 1;
The position of the first hip crotch between the first metacarpal floor and the second metacarpal floor, and between the first metacarpal floor and the third metacarpal floor A bone extraction means for specifying the position of the second bone crotch from the second binarized data; the positions of the first finger crotch and the second finger crotch; and the first Area setting means for setting a specific area surrounded by the position of the hip crotch and the second bone crotch,
A bone region specifying program characterized by functioning as A bone region specifying device for specifying a region including a metacarpal bone using image data obtained based on a radiographic image,
Smoothing means for performing at least one smoothing process on the image data to obtain at least one smoothed image data;
First binarizing means for obtaining first binarized data obtained by binarizing the smoothed image data with a first threshold;
Second binarization means for obtaining second binarized data obtained by binarizing the smoothed image data with a second threshold different from the first threshold;
The position of the first finger crotch between the first finger and the second finger and the position of the second finger crotch between the first finger and the third finger are An external shape extracting means for specifying the binarized data of 1;
The position of the first hip crotch between the first metacarpal floor and the second metacarpal floor, and between the first metacarpal floor and the third metacarpal floor A bone extraction means for specifying the position of the second bone crotch from the second binarized data;
Area setting means for setting a specific area surrounded by the positions of the first and second finger crotch parts and the positions of the first and second bone crotch parts;
A bone region specifying device comprising: