JP4872093B2 - Bone age estimation device, bone age estimation method, and bone age estimation program - Google Patents

Description

  The present invention relates to a bone age estimation device, a bone age estimation method, and a bone age estimation program for estimating a bone age. In particular, the present invention relates to a bone age estimation apparatus, a bone age estimation method, and a bone age estimation program for estimating a bone age based on an X-ray image transmitted through a bone.

  Conventionally, various techniques for measuring bone age have been developed. Conventional techniques include the following methods.

(1) DXA Method In the DXA method (Dual energy X-ray Absorbometry, dual energy X-ray absorption measurement method), two X-rays having different energies are irradiated on the body, and X-rays transmitted through the body are detected. Then, the bone density is calculated based on the X-ray detection result and the X-ray absorption characteristics of the bone tissue and soft tissue. Bone age is measured based on the calculated bone density. Currently, bone density measurement using the DXA method is widely used (see, for example, Non-Patent Document 1).

(2) Ultrasonic measurement method In the ultrasonic measurement method, ultrasonic waves are transmitted to the subject's body, and the sound velocity and attenuation rate of the ultrasonic waves inside the bone are determined based on the received wave signal of the ultrasonic waves that have passed through the body. Ask. These are used as an evaluation index of bone age or bone symptoms (for example, see Non-Patent Document 2).

"Study on the determination of lumbar bone mineral density by DXA method-posterior element bone mineral quantity and its age difference", Satoshi Hiramatsu, Doctoral Dissertation, Gifu University, September 1995 “Precautions for bone age measurement in Japanese and children using an ultrasonic bone age measuring device (Bonage)”, Hirofumi Kintaka, Bulletin of Kanoya University of Physical Education No. 36, 2007

The conventional technology has the following problems.
(1) First, when taking an X-ray photograph by the DXA method or the like, the luminance of the X-ray cannot be kept completely constant in time. For this reason, an error occurs in the exposure amount for each X-ray film. Due to the difference in the exposure amount, a measurement error occurs in the X-ray transmittance of the specimen calculated from the imaging result, and therefore in the bone density or bone age.

  (2) In both the DXA method and the ultrasonic measurement method, a measurement error occurs due to a bone measurement site, a distance from the measurement device to the sample at the time of measurement, a difference in measurement environment, or the like.

  (3) Furthermore, both the DXA method and the ultrasonic measurement method have complicated measurement methods. Therefore, both methods take time for the measurement process. In other words, the system using either method is not responsive.

  The present invention has been made to solve the above problems. It is an object of the present invention to provide a bone age estimation device, a bone age estimation method, and a bone age estimation program capable of accurately estimating a bone age based on an X-ray image of an X-ray transmitted through a bone by a simple procedure. And

  According to one aspect of the present invention, there is provided a bone age estimation device, an image acquisition means for acquiring image data corresponding to X-rays transmitted through a bone, and a first area for designating a first region of the image data. Region specifying means, first extraction means for extracting the brightest pixel having the highest luminance from the pixels in the first area, and a second area having a predetermined size including the brightest pixel in the image data. Second region designating means for designating, second extraction means for extracting a plurality of bright pixels having a luminance equal to or higher than a threshold value corresponding to the maximum luminance from the pixels of the second region, and bone density of bone And an estimation means for estimating the bone age of the bone based on the distribution characteristics of the plurality of bright pixels that change in accordance with.

  Preferably, the estimating means obtains the maximum distance and the minimum distance from the brightest pixel to each bright pixel, and estimates the bone age based on a ratio of the minimum distance to the maximum distance.

  More preferably, the estimation means estimates the bone age higher as the ratio of the minimum distance to the maximum distance is lower.

  Preferably, the first area includes a plurality of designated areas, the first extraction unit extracts the brightest pixels for each designated area, and the second area includes the brightest pixels of each designated area. A plurality of processing regions, wherein the second extraction unit extracts a bright pixel for each processing region, and the estimation unit obtains the distribution characteristics of the bright pixels in each processing region, and based on the statistics of the distribution characteristics, Is estimated.

  Preferably, the first area designating unit sets the first area in an area corresponding to the bone marrow of the bone.

  Preferably, the second area designating unit designates an area centered on the brightest pixel as the second area.

  Preferably, the image acquisition means includes a scanner for scanning a film on which an X-ray image of an X-ray transmitted through the bone is recorded.

  Preferably, the image acquisition means includes an X-ray source that outputs X-rays, and an X-ray detector that detects X-rays output from the X-ray source and transmitted through the bone.

  According to another aspect of the present invention, there is provided a bone age estimation method, the step of acquiring image data corresponding to X-rays transmitted through a bone, the step of designating a first region of the image data, Extracting the brightest pixel having the highest luminance from the pixels in the region; designating a second region of a predetermined size including the brightest pixel in the image data; and among the pixels in the second region The bone age of the bone is estimated based on the step of extracting a plurality of bright pixels having a luminance equal to or higher than the threshold corresponding to the maximum luminance from the distribution characteristics of the plurality of bright pixels that change according to the bone density of the bone And a step of performing.

  According to still another aspect of the present invention, there is provided a bone age estimation program, the step of acquiring image data corresponding to X-rays transmitted through a bone, the step of designating a first region of the image data, Extracting the brightest pixel having the highest luminance from the pixels in the region, designating the second region of a predetermined size including the brightest pixel in the image data, and the pixels of the second region Based on the step of extracting a plurality of bright pixels having a luminance equal to or higher than the threshold corresponding to the maximum luminance from the inside, and the distribution characteristics of the plurality of bright pixels changing according to the bone density of the bone, And causing the computer to execute the estimating step.

  The bone age estimation apparatus (or bone age estimation method, bone age estimation program) according to the present invention extracts the brightest brightest pixel from the designated region in the X-ray image data of the X-ray transmitted through the bone. . Further, the bone age estimation device extracts pixels having a luminance equal to or higher than a threshold corresponding to the luminance of the brightest pixel from a region having a predetermined size including the brightest pixel. Then, the bone age estimation device estimates the age of the bone based on the extracted pixel distribution characteristics. Therefore, according to the present invention, the bone age can be accurately estimated by a simple procedure based on the X-ray image transmitted through the bone.

It is a figure showing the composition of the inspection system concerning a 1st embodiment. It is a figure which shows the hardware constitutions of a computer in a block diagram format. It is a figure which shows the functional structure of a computer by a block diagram form. It is a figure which shows the flow of the process performed when the test | inspection system which concerns on 1st Embodiment estimates bone age in a flowchart format. It is a figure which shows an example of a bone image. It is a figure which shows an example of the screen containing a thumbnail display. It is a figure which shows the flow of the process which an image process part performs in a flowchart format. It is a figure for demonstrating the specific example of cut image data. It is a figure which shows an example of a reconstruction image. It is a figure which shows the flow of the process which an age estimation part performs in a flowchart format. It is a figure which shows the specific example of the position of the extracted pixel, a pixel value, the distance from a center, and distance ratio. It is a figure which shows the distance ratio calculated | required about the 1st measurement data. It is the figure which showed the calculation result of the distance ratio shown in FIG. 12 in the graph format. It is the figure which showed the sum total of distance ratio in the graph format. It is a figure for demonstrating 2nd measurement data extraction. It is a figure which shows the distance ratio calculated | required about the 2nd measurement data. It is a figure which shows collectively the average value over all the extraction points of the distance ratio calculated | required about each sample. It is the figure which showed the value shown in FIG. 17 in the graph format. It is a figure which shows collectively the average value over the point 2 and the point 3 of the distance ratio calculated | required about each sample. It is the figure which showed the value shown in FIG. 19 in the graph format. It is a figure which shows the structure of the test | inspection system which concerns on 2nd Embodiment. It is a figure which shows the flow of the process performed when a test | inspection system estimates a bone age in a flowchart format.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description, the same parts are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed description thereof will not be repeated.

[First Embodiment]
<System configuration>
With reference to FIG. 1, the outline | summary of the test | inspection system 1 for bone age estimation based on this Embodiment is demonstrated. FIG. 1 is a diagram showing a configuration of an inspection system 1 according to the first embodiment. The inspection system 1 includes a computer 10, a scanner 20, and a cable 30.

  The cable 30 connects the computer 10 and the scanner 20. The cable 30 is, for example, a USB (Universal Serial Bus) cable or a LAN (Local Area Network) cable. However, the computer 10 and the scanner 20 exchange data via the cable 30. However, the computer 10 and the scanner 20 may be connected by other methods. For example, the computer 10 and the scanner 20 may perform wireless communication using radio waves, infrared rays, light, or the like.

  The scanner 20 reads an X-ray film 40 on which an X-ray image by X-rays transmitted through a bone is recorded, and outputs image data corresponding to the read X-ray film 40. Hereinafter, the image data output by the scanner 20 as a result of the scanner 20 reading the X-ray film 40 is referred to as “X-ray image data”.

  In the present embodiment, as the X-ray film 40, an X-ray image recorded with ultra soft X-rays is used. Ultra soft X-rays are close to ultraviolet rays, have a short wavelength, and have an energy as low as about several tens eV. Ultra-soft X-rays are suitable for X-ray imaging of the human body because of their low energy. However, the X-rays used for recording on the X-ray film 40 are not limited to ultrasoft X-rays.

  The scanner 20 is a transmissive scanner that can appropriately read an image recorded on the X-ray film 40. However, the scanner 20 may be of a reflective type. The scanner 20 is not particularly limited to this. For example, BMP / DIP (Windows (registered trademark) Bitmap format), JPG / JPEG / JPE (JPEG Format format), PNG (Portable Network Graphic format), TIF A scan image of an image format such as / TIFF (Tagged Image File Format format) or GIF (Composerve GIF format) is created. Preferably, the scanner creates image data of BMP / DIP, JPG / JPEG / JPE, and TIF / TIFF. More preferably, the scanner creates BMP / DIP image data.

  The computer 10 receives X-ray image data from the scanner 20 via the cable 30. Further, the computer 10 estimates the bone age of the bone imaged on the X-ray film 40 based on the X-ray image data.

  The inspection system 1 is used as follows. When estimating the bone age of the specimen, the examiner prepares an X-ray film 40 obtained by X-ray imaging of the specimen using an X-ray source. Then, the inspector causes the scanner 20 to read the X-ray film 40. Alternatively, the examiner may use the present inspection system 1 to estimate the bone age of the bone that has been imaged and stored on the stored X-ray film 40.

<Hardware configuration>
A hardware configuration of the computer 10 will be described with reference to FIG. FIG. 2 is a block diagram showing the hardware configuration of the computer 10.

  The computer 10 includes a keyboard 110, a mouse 120, a display 130, a CPU (Central Processing Unit) 140, a RAM (Random Access Memory) 150, a hard disk 160, an external interface 170, and an FD (Flexible Disc) drive 180. An optical disk drive 190, a USB connector 200, an SD (Secure Digital) drive 210, and a bus 220 that connects them together.

  The keyboard 110 and the mouse 120 accept external instructions. That is, the keyboard 110 and the mouse 120 function as input devices. The computer 10 may include other types of input devices such as a touch pad, a touch panel, or a tablet.

  The display 130 displays information inside the computer 10 to the outside. The structure of the display 130 is not particularly limited. As the display 130, for example, a cathode ray tube display, a liquid crystal display, a plasma display, or the like can be used.

  CPU 140 performs various calculations based on instructions received by keyboard 110 and mouse 120. The CPU 140 controls the operation of each unit of the computer 10.

  The RAM 150 is used as a working memory for programs executed by the CPU 140.

  The hard disk 160 stores various data. Specifically, the hard disk 160 stores a bone age estimation program 161, bone image data 162, cut-out image data 163, reconstruction data 164, and analysis result 165.

  The bone image data 162 is obtained by the scanner 20 reading the X-ray film 40. The cut image data 163 is image data of a part of the bone image data 162. The reconstruction data 164 is data generated by the program 161 during the bone age estimation process. The analysis result 165 includes the bone age obtained by the program 161. Details of these data will be described later.

  2 does not necessarily have to be stored in the hard disk 160. For example, these data may be stored in a storage medium such as the FD 182, the optical disk 192, the USB (Universal Serial Bus) flash memory 202, and the SD (Secure Digital) card 212. Further, fixed data such as the program 161 may be stored in a ROM (Read Only Memory).

  The external interface 170 connects the computer 10 and an external device. The external interface 170 includes a cable connector for the cable 30. For example, a USB connector can be used as the external interface 170. Alternatively, the wireless communication unit can be the external interface 170.

  The FD drive 180 reads data stored in the FD 182 and writes data to the FD 182.

  The optical disk drive 190 reads data stored on the optical disk 192. The optical disk 192 is a recording medium on which data is recorded using light reflectance. Examples of the optical disk 192 include CD (Compact Disc) -R, CD-RW, DVD (Digital Versatile Disc) ± R, DVD ± / RW, DVD ± RAM, and Blu-ray Disc.

  A USB terminal can be attached to and detached from the USB connector 200. The USB connector 200 exchanges data with a device connected to the USB connector 200. In particular, the USB connector 200 reads and writes data in the USB flash memory 202 connected to the USB connector 200.

  The SD drive 210 reads and writes data from the SD card 212. The SD drive 210 can also read and write data from an SDHC card (SD High Capacity) to which an adapter is attached, a miniSD card, a miniSDHC card, a microSD card, and a microSDHC card.

  The storage media that can be handled by the computer 10 are not limited to those described above. The FD drive 180, the optical disk drive 190, the USB connector 200, and the SD drive 210 are examples of interfaces for reading and writing data on a storage medium. The computer 10 may include an interface corresponding to another storage medium.

<Functional configuration>
The functional configuration of the computer 10 will be described with reference to FIG. FIG. 3 is a block diagram showing the functional configuration of the computer 10.

  Referring to FIG. 3, computer 10 includes an input unit 310, an output unit 320, an interface unit 330, a storage unit 340, and a control unit 350.

  The input unit 310 receives an instruction from the outside. Input devices such as the keyboard 110 and the mouse 120 correspond to the input unit 310.

  The output unit 320 outputs information inside the computer 10 to the outside. In the configuration illustrated in FIG. 2, the display 130 corresponds to the output unit 320. When the computer 10 includes another output device such as a speaker, such an output device also corresponds to the output unit 320.

  The interface unit 330 mediates exchange of signals or data between the computer 10 and an external device. The interface unit 330 includes an external interface 170, an FD drive 180, an optical disc drive 190, a USB connector 200, and an SD drive 210.

  The storage unit 340 stores data. Specifically, the storage unit 340 stores a program 161, bone image data 162, cut-out image data 163, reconstruction data 164, and analysis result 165. A storage medium (such as an FD 182 or an optical disk 192) or a storage device (such as an external hard disk or a storage device in an external device) connected to the RAM 150, the hard disk 160, and the computer 10 corresponds to the storage unit 240.

  The control unit 350 controls operations of the output unit 320, the interface unit 330, and the storage unit 340 based on a signal received by the input unit 310. Control unit 350 includes an image acquisition unit 351, an image processing unit 352, and an age estimation unit 358.

  The image acquisition unit 351 acquires the bone image data 162 from the outside (the scanner 20 in the present embodiment) by controlling the interface unit 330. Further, the image acquisition unit 351 stores the bone image data 162 acquired from the outside in the storage unit 340.

  The image processing unit 352 performs image processing on the bone image data 162. The image processing unit 352 also performs image processing on image data generated as a result of image processing on the bone image data 162. The image processing unit 352 includes an image cutout unit 353, a reconstruction unit 354, and an age estimation unit 358.

  The image cutout unit 353 specifies an area in the bone image data 162. The image cutout unit 353 stores the image data of the designated area in the storage unit 340 as cutout image data 163.

  The reconstruction unit 354 performs predetermined image processing on the cut image data 163 and creates reconstructed data 164 based on the cut image data 163. In addition, the reconstruction unit 354 stores the created reconstruction data 164 in the storage unit 340.

  The reconstructed data 164 is “bright” on the basis of the data of the pixel with the highest luminance (called the brightest pixel) in the cut image data 163 and the luminance of the brightest pixel included in the region including the brightest pixel. Data of a pixel to be judged (bright pixel). Details and specific examples of the reconstruction data 164 will be described later.

  The reconstruction unit 354 includes a brightest pixel extraction unit 355, a region setting unit 356, and a bright pixel extraction unit 357. The brightest pixel extraction unit 355 extracts the brightest pixel from the cut image data 163. The area setting unit 356 sets an area for extracting bright pixels. The bright pixel extraction unit 357 extracts a bright pixel from the region set by the region setting unit 356.

  The age estimation unit 358 calculates an estimated value of the target bone age recorded in the bone image data 162 based on the distribution of bright pixels in the reconstruction data 164. Then, the age estimation unit 358 stores the estimated bone age value in the storage unit 340 as the analysis result 165. Details of the bone age estimation method by the age estimation unit 358 will be described later.

  In the present embodiment, the CPU 140 that develops and executes the program 161 in the RAM 150 realizes the above-described functions of the control unit 350. However, part or all of the functions of the control unit 350 may be realized by hardware such as a dedicated circuit.

<Bone age estimation procedure>
From here, the procedure of bone age estimation by the test | inspection system 1 is demonstrated, referring FIG. FIG. 4 is a flowchart showing the flow of processing performed when the inspection system 1 according to the first embodiment estimates the bone age.

  In step S101, the inspection system 1 captures an X-ray image. Specifically, the inspection system 1 scans the X-ray film 40 with the scanner 20 and creates bone image data 162. The image acquisition unit 351 of the computer 10 receives the bone image data 162 from the scanner 20 and stores it in the storage unit 240 based on a user instruction or automatically when executing a scan.

  Note that the inspection system 1 preferably scans a plurality of X-ray films 40 in step S101. According to this procedure, the bone age can be estimated more efficiently than when the inspection system 1 scans the X-ray film 40 one by one each time the bone age is estimated.

  An example of an image based on the bone image data 162 (hereinafter referred to as “bone image” for simplicity) is shown in FIG. A bone image 500 shown in FIG. 5 is an imaging result of two bones in the joint portion. In the bone image 500, the mesh portion 510 corresponds to bone marrow. Moreover, the white area | region 520 surrounding the mesh-shaped part 510 is equivalent to bone quality.

  Returning to FIG. 4, the description will be continued. In step S103, the inspection system 1 selects bone image data 162 that is a target for obtaining bone age from the bone image data 162 acquired in step S101.

  In the present embodiment, the image acquisition unit 351 of the computer 10 selects one bone image data 162 based on a user instruction. The computer 10 displays a plurality of bone image data 162 as thumbnails so that the user can select the bone image data 162. FIG. 6 shows an example of a screen including a thumbnail display. The screen 600 shown in FIG. 6 includes bone image thumbnails 610, 620 and 630.

  If the scanner 20 has a memory for storing the scan results of the plurality of X-ray films 40 and the stored scan results can be presented to the user in a selectable manner, the user operates the scanner 20 to Bone image data 162 for determining the age may be selected. In this case, the computer 10 receives the bone image data 162 selected by the scanner 20 from the scanner 20 and stores the received bone image data 162 in the storage unit 340.

  Further, in step S101, when the inspection system 1 captures only one X-ray image, the process in step S103 is not necessary.

  Returning again to FIG. In step S105, the image processing unit 352 included in the control unit 350 performs image processing for bone age estimation on the bone image data 162 selected in step S103, and creates reconstruction data 164. Details of the image processing in step S105 will be described later.

  In step S107, the age estimation unit 358 included in the control unit 350 estimates the target bone age shown in the bone image data 162 selected in step S103 based on the reconstruction data 164. Details of the bone age estimation process in step S107 will be described later.

  In step S109, control unit 350 determines whether an instruction to end bone age estimation has been received. For example, the input unit 310 creates an end instruction based on a user input. If there is an end instruction (YES in step S109), control unit 350 ends the age estimation process. When there is no end instruction (NO in step S109), control unit 350 repeats the processing from step S103 (selection of target image).

(Image processing)
The processing performed by the image processing unit 352 in step S105 will be described in detail with reference to FIG. FIG. 7 is a flowchart showing the flow of processing performed by the image processing unit 352.

  In step S <b> 201, the image cutout unit 353 included in the image processing unit 352 acquires cutout image data 163 that is image data of a partial region (partial image) of the selected bone image data 162.

  In the present embodiment, the CPU 140 that executes the paint software realizes the function of the image cutting unit 353. That is, the user calls the bone image data 162 on the paint software. Then, the user cuts out a desired region from the bone image data 162 using the paint software. Further, the user instructs the paint software to save the cut area. Data saved by this processing is cut image data 163.

  Note that the user may create a plurality of cut image data 163 for one bone image data 162. As will be described later, it is preferable to create a plurality of cut image data 163 for one bone image data 162 in order to improve age estimation accuracy.

  A specific example of the cut image data 163 will be described with reference to FIG. FIG. 8 is a diagram for explaining a specific example of the cut image data 163.

  FIG. 8A is a diagram for explaining an example of a relationship between a bone image and a partial image. FIG. 8A shows the bone image 500 shown in FIG. 5 again. The image cutout unit 353 cuts out three partial images 810, 820, and 830 (images of a region surrounded by a white frame in the drawing) from the bone image 500.

  FIG. 8B shows an enlarged partial image (image 840) corresponding to one cut-out image data 163. As can be seen with reference to FIG. 8B, the cut-out image data 163 includes information about the structure of the bone. Bone tissue (organic matter) exists in a bright portion in the image 840. A dark part in the image 840 is a hollow region of bone. The bone shown in the cut-out image data 163 including many dark parts has a low bone density, and therefore, the bone age is likely to be high. On the other hand, the bone shown in the cut image data 163 including many bright portions has a high bone density, and therefore, the bone age is likely to be low.

  By the way, in order to accurately estimate the bone age, the region of the cut image data 163 is preferably in the region corresponding to the bone marrow as shown in FIG. 8A. This is because the age estimation unit 358 estimates the bone age based on the distribution of bone tissue in the bone marrow. The distribution of bone tissue corresponds to the distribution of high-luminance pixels in the bone image data 162. However, the bone quality that exists outside the bone marrow is also highly bright. Therefore, when the bone quality is included in the area of the cutout image data 163, the age estimation unit 358 may not be able to correctly estimate the bone age.

  In the present embodiment, the user visually recognizes the bone image and designates the area of the cut image data 163 in the area corresponding to the bone marrow. However, the computer 10 may be configured to determine the area of the cut image data 163 based on the luminance distribution of the image.

  Returning to FIG. 7, in step S <b> 203, the reconstruction unit 354 included in the image processing unit 352 determines the cut-out image data 163 to be processed later. For example, the reconstruction unit 354 selects one cut image data 163 from the plurality of cut image data 163 based on a user's selection instruction. Alternatively, the reconstruction unit 354 may automatically select one cut image data 163. For example, the reconstruction unit 354 may select the cut image data 163 having the earliest creation time.

  After step S203, the reconstruction unit 354 performs the following processing from step S205 to step S209 on the cut image data 163 selected in step S203. The reconstruction unit 354 performs the processing from step S205 to step S209 by executing a predetermined script using image processing / analysis software.

  In step S205, the brightest pixel extraction unit 355 included in the reconstruction unit 354 compares the luminance value of each pixel of the cut image data 163 selected in step S203, and the pixel having the highest luminance (the brightest pixel). ). Hereinafter, the brightness of the brightest pixel is referred to as the maximum brightness.

  In step S207, the region setting unit 356 included in the reconstruction unit 354 sets a region having a predetermined size including the brightest pixel as a processing region to be processed later. Specifically, the region setting unit 356 sets a square region centered on the brightest pixel as a processing region. Since the reconstruction unit 354 is centered on the brightest pixel, the distribution of bright pixels can be accurately obtained. However, the positional relationship between the brightest pixel and the processing region and the shape of the processing region are not limited to this.

  The size of the area may be set in advance or may be set as appropriate by the user. However, the size of the region is preferably set so that the difference in the structure of the bone tissue depending on the age appears in the image data in the region. Therefore, the size of the region is preferably set so that the region other than the bone marrow is not included in the region.

  In step S209, the bright pixel extraction unit 357 included in the reconstruction unit 354 extracts “bright pixels” included in the processing region. Specifically, the bright pixel extraction unit 357 extracts a pixel having a luminance equal to or higher than a threshold value as a “bright pixel”. Note that the bright pixel extraction unit 357 extracts pixels in descending order of luminance.

  Here, the bright pixel extraction unit 357 determines the threshold value based on the maximum luminance. That is, the threshold value is not fixed but varies according to the maximum luminance. Specifically, in the present embodiment, the bright pixel extraction unit 357 sets a value obtained by multiplying the maximum luminance by a predetermined ratio (for example, 60%) as the threshold value. The predetermined ratio may be set in advance or may be set by the user.

  Note that the threshold is not necessarily limited to the above as long as it varies according to the maximum luminance. For example, the bright pixel extraction unit 357 may set a value obtained by subtracting a predetermined value from the maximum luminance as the threshold value.

  Thus, the bright pixel extraction unit 357 extracts a bright pixel based on the threshold value corresponding to the maximum luminance. Therefore, the bright pixel extraction unit 357 can extract a bright pixel by eliminating a factor (error factor) of luminance fluctuation excluding a difference in bone density. Note that error factors include variations in the amount of exposure for each X-ray film 40 caused by temporal variations in imaging conditions, variations in the amount of exposure in one X-ray film 40 due to differences in imaging positions, and the like.

  As will be described in detail later, the age estimation unit 358 estimates the bone age based on the distribution characteristics of the bright pixels extracted in this way. Therefore, the inspection system 1 according to the present embodiment can estimate the bone age with high accuracy while suppressing the influence of the difference in luminance distribution that is not derived from the difference in bone density.

  Further, the bright pixel extraction unit 357 extracts a bright pixel from a region having a predetermined size. Therefore, the age estimation unit 358 can estimate the bone age based on the same reference even for partial images having different sizes.

  In step S211, the reconstruction unit 354 creates reconstruction data 164 based on the brightest pixel extracted in step S205 and the bright pixel extracted in step S209. The reconstruction data 164 includes the X and Y coordinates of the highest luminance pixel and the bright pixel, and the luminance. Note that the X coordinate and the Y coordinate are an example of data for specifying the position of a pixel. The inspection system 1 may output identification information (for example, a serial number corresponding to the position in the pixel) that is uniquely assigned to each pixel and can specify the position of each pixel instead of the X coordinate and the Y coordinate. .

  Furthermore, the reconstruction unit 354 stores the reconstruction data 164 in the storage unit 340 in step S211. As will be described later, the CPU 140 that executes spreadsheet software implements a part of the function of the age estimation unit 358. Therefore, the reconfiguration unit 354 converts the reconfiguration data 164 into a CSV (Comma Separated Values) format that can be handled by spreadsheet software. The reconstruction unit 354 stores the reconstruction data 164 in CSV format in the storage unit 340.

  An example of an image (reconstructed image) corresponding to the reconstruction data 164 is shown in FIG. The brightest pixel is located at the center of the reconstructed image 900. In the reconstructed image 900, a number corresponding to the order of the brightness of the bright pixels is shown at the position of each bright pixel.

  Returning to FIG. In step S213, the image processing unit 352 determines whether or not the processing from step S205 to step S211 has been performed on all partial images. If all partial images have been processed (YES in step S213), image processing unit 352 ends the image processing. If there is a partial image that has not been processed (NO in step S213), image processing unit 352 returns to the process in step S203 (image selection).

  Note that when the image cutout unit 353 creates only one cutout image data 163 from the bone image data 162, the processing in step S203 and the processing in step S213 are not necessary. When completing step S211, the image processing unit 352 ends the image processing.

(Estimation of bone age)
The flow of processing performed by the age estimating unit 358 in step S107 in FIG. 4 will be described with reference to FIG. FIG. 10 is a flowchart showing the flow of processing performed by the age estimation unit 358.

  In step S <b> 301, the age estimation unit 358 selects one of the reconstruction data 164 obtained for the bone image data 162 for estimating the bone age from the reconstruction data 164 stored in the storage unit 340. In addition, the age estimation unit 358 reads the selected reconstruction data 164 from the storage unit 340.

  In step S303, the age estimation unit 358 calculates the distance from the highest luminance point (brightest pixel) given by the following equation (*) to each measurement point (bright pixel).

(Distance from highest point of brightness to measurement point) = √ [square of (X coordinate of bright pixel−X coordinate of brightest pixel) + square of (Y coordinate of bright pixel−Y coordinate of brightest pixel) ] (*)
In the present embodiment, the coordinate of the brightest pixel is the center of the image area of the reconstruction data 164. Since the coordinates of the brightest pixel are unchanged, the program creator may give the coordinates of the brightest pixel to the formula (*) in advance.

  In step S305, the age estimation unit 358 extracts the minimum value and the maximum value of the distance from the highest point of luminance to the measurement point. Then, the age estimation unit 358 calculates an index value for bone age estimation given by the following formula (**).

(Index value) = (Minimum value of the distance from the highest point of luminance to the measuring point) / (Maximum value of the distance from the highest point of luminance to the measuring point) ... (**)
Thus, the age estimation unit 358 can calculate an index value for bone age estimation based on the simple formula (*) and formula (**). Therefore, the computer 10 can perform the processing of step S303 and step S305 in a short time. Further, the computer 10 can easily realize these processes by general-purpose spreadsheet software such as Excel (registered trademark).

  An example of the processing result of step S303 and step S305 is shown in FIG. FIG. 11 is a diagram illustrating specific examples of the extracted pixel position, pixel value, distance from the center, and index value. Each row in FIG. 11 includes, in order from the left, an identification number (No. 1 is the brightest pixel) for distinguishing the brightest pixel or bright pixel, the X coordinate of the brightest pixel or bright pixel, the brightest pixel or bright pixel. The Y coordinate, the pixel value of the brightest pixel or bright pixel, and the distance from the brightest pixel are shown. Further, the numbers under “MIN / MAX” in the rightmost column are index values of the data shown in FIG.

  In step S307, the age estimation unit 358 determines whether or not the processing from step S303 to step S307 has been performed on all reconstruction data 164 related to the bone image data 162 for estimating the bone age. When processing has been performed for all reconstruction data 164 (YES in step S307), age estimating unit 358 proceeds to processing in step S309. If the image processing unit 352 has not yet performed processing on certain reconstruction data 164 (NO in step S307), the process returns to the processing in step S301 (selection of reconstruction data 164).

  In step S309, the age estimation unit 358 estimates the bone age based on the index value. In general, bone density decreases with age. Accordingly, the index value decreases with aging. The age estimation unit 358 can obtain an estimated value of bone age using this characteristic.

  Specifically, the age estimation unit 358 obtains an estimated value of the bone age by using, for example, data representing the relationship between the index value and the bone age (referred to as correlation data). Such correlation data is obtained in advance and is stored in the storage unit 340. The age estimation unit 358 reads the correlation data from the storage unit 340, and uses the bone age associated with the index value obtained by the correlation data in step S305 as the estimated bone age value.

  In addition, correlation data shall be produced by the designer or user of the inspection system 1, for example. The designer or user creates correlation data statistically or empirically based on a plurality of sample data, and stores the created data in the storage unit 340. For example, the correlation data associates an index value within a certain range with a bone age (such as 40 to 50 years) within a certain range. Alternatively, the correlation data may be a function that associates one index value with one estimated bone age value.

  In the present embodiment, the age estimation unit 358 indicates the target bone age shown in one bone image data 162 as an index value in a plurality of reconstruction data 164 respectively corresponding to a plurality of partial images of the bone image data 162. Based on the statistics and correlation data. Here, as the “index value statistics”, an average value or a total value of the index values can be used.

  Since the age estimating unit 358 obtains an estimated value based on a plurality of index values obtained from the plurality of reconstruction data 164, the bone age is estimated with higher accuracy than in the case of estimating the bone age based on one index value. Can be estimated. However, the age estimation unit 358 may estimate the bone age based on one reconstruction data 164.

<Measurement data>
Based on actual measurement data, the validity of the bone age estimation method by the present inspection system 1 will be described.

(First measurement data)
First, an index value obtained from a bone image as shown in FIG. 8A will be described. Here, three bone images of a 21-year-old subject, 55-year-old subject, and 80-year-old subject were prepared.

  The user designates three partial regions from each bone image. The computer 10 creates cut image data for each designated partial area. As shown in FIG. 8A, the user sets three partial regions in the region in the bone marrow.

  However, since the user sets a partial area, the partial area does not exactly match the area shown in FIG. 8A. However, since this estimation method estimates the bone age by the procedure of extracting the brightest pixel, extracting the bright pixel of a predetermined size region including the brightest pixel, and estimating the age based on the distribution of the extracted bright pixels, The error of the region cut out from the bone image has almost no influence on the estimation result.

  The index values obtained for each bone image are shown in FIG. FIG. 12 is a diagram showing index values obtained for the first measurement data. FIG. 12 shows index values obtained based on the cut-out image data of extraction points (Point1, Point2, Point3) for 21-year-old, 55-year-old, and 80-year-old bone image samples (Sample 1, Sample 2, Sample 3). Is shown.

  FIG. 13 is a graph showing the calculation result of the index value shown in FIG. FIG. 13 shows nine calculation results (3 samples × 3 extraction points) for each of the age of 21, 55, and 80.

  FIG. 14 is a graph showing the sum of index values in a graph format. In FIG. 13, the total value of the calculation results of the nine index values is shown for each of 21 years old, 55 years old, and 80 years old.

  The index value is expected to decrease with increasing age. However, it is difficult to read this tendency from FIG. Even in such a case, as can be seen from FIG. 14, the bone age can be estimated by using the statistics of the index values obtained for each of the plurality of cut image data. That is, this estimation method can estimate the bone age with high accuracy by estimating the bone age using the statistics of the index values.

(Second measurement data)
Next, the second measurement data will be described. In obtaining the second measurement data, five cut image data were extracted from one bone image as shown in FIG. FIG. 15 is a diagram for explaining the second measurement data extraction. Referring to FIG. 15, when acquiring the second measurement data, the user designates five partial areas (partial areas 1510, 1520, 1530, 1540, 1550) from bone image 1500. The computer 10 creates cut image data corresponding to each partial area.

  FIG. 16 is a diagram illustrating index values obtained for the second measurement data. FIG. 16 shows index values obtained based on cut-out image data of extraction points (Points 1 to 5) for image samples of bones of 21 years old, 55 years old, and 80 years old. In FIG. 16, the index value calculated | required with each extraction point about the four samples in each age typically is shown. In practice, index values are obtained for five samples.

  FIG. 16 shows the total value and average value of the index values obtained at each point over all samples (five) (“total” and “average” below each table). Further, FIG. 16 shows, for each sample, the total value and average value of the index values over all points, the average value of the index values of point 1 and point 2, the average value of the index values of point 2 and point 3, and the point 3 And the average value of the index values of point 4 and the average value of the index values of point 4 and point 5 (such as “total” and “average” on the right side of each table).

  In FIG. 17, the average value over all the extraction points of the index value calculated | required about each sample is shown collectively. The values shown in FIG. 17 are the same as the values in the cell shaded from the upper left to the lower right in FIG. FIG. 18 is a diagram showing the values shown in FIG. 17 in a graph format. The vertical axis of the graph shown in FIG. 18 is the value shown in FIG. Since this value represents the age relatively, it is called an “age relative value”.

  In addition, about each sample, it is not necessarily required to take the average (or total) about all the extraction points. Rather, the average (total) for limited extraction points may better represent bone age. In the measurement data shown in FIG. 17, the average (or sum) over each sample for point 2 and point 3 varies greatly with age compared to the corresponding value at other points. Therefore, the average value of points 2 and 3 well represents bone age.

  FIG. 19 is a diagram collectively showing the average values over the points 2 and 3 of the index values obtained for each sample. FIG. 20 is a diagram showing the values shown in FIG. 19 in a graph format.

  In the graph shown in FIG. 18, the average value for sample 1 is far from the average value for each of the other samples. However, this is not the case with the graph shown in FIG. Therefore, by using the average value of point 2 and point 3, it is possible to estimate the bone age more accurately than obtaining the average value of all points.

  Which extraction point is used for bone age estimation can be determined based on, for example, the variation of the average (or total) index value at each extraction point depending on age.

  Specifically, for example, the ratio of the average of the index values for the youngest sample to the average of the index values for the oldest sample is obtained as “variation”. Then, a predetermined number of points are used for bone age estimation in descending order of variation. Alternatively, a point whose variation is a predetermined threshold value or more may be used for bone age estimation. Or you may decide to use for the bone age estimation the point which dispersion | variation is less than upper predetermined number, and is more than a predetermined threshold value.

  The extraction point used for the bone age estimation described above can be determined by the computer 10 or by the user.

  As another method for determining the extraction point, for example, the extraction point may be determined based on bone age estimation results for some samples whose ages are known. Specifically, first, a bone age inspector obtains an index value at a plurality of extraction points for a sample of which some ages are known before estimating the bone age of the specimen. Next, the examiner compares the estimated age of the bone based on the statistics of the index values obtained at several extraction points with the age of the sample. Then, the examiner obtains a set of extraction points whose estimated value has a strong correlation with the age of the sample. The examiner estimates the bone age of the extracted specimen based on the statistics of the index values at the obtained set of extraction points.

  With the above configuration, the estimation of bone age by the inspection system 1 according to the present embodiment has the following characteristics.

(1) The inspection system 1 that is not easily affected by measurement errors in X-ray imaging is based on the distribution characteristics of bright pixels extracted from one piece of bone image data 162 based on the ratio of luminance to maximum luminance. Estimate bone age. Therefore, the inspection system 1 can accurately estimate the bone age even if the luminance of the X-ray image data varies due to measurement errors.

(2) The measurement site is not limited The inspection system 1 estimates the bone age based on the distribution characteristics of high-luminance pixels using the change characteristics of bone density due to aging. Therefore, the inspection system 1 can estimate the bone age based on the bone image taken by X-ray, regardless of the part of the bone image. The inspection system 1 can estimate the bone age based on data of a bone marrow region in which an aging change in bone density appears in the bone image.

(3) No complicated procedure is required The inspection system 1 executes image processing such as extraction of high-luminance pixels in accordance with a program. Moreover, the test | inspection system 1 estimates a bone age based on a very simple calculation formula. Therefore, the user of the inspection system 1 can quickly perform the bone age estimation work and can estimate the bone age in a very short time.

  That is, according to the inspection system 1 according to the present embodiment, a bone age inspector can estimate the bone age of bones photographed in various bone images with high accuracy and in a short time.

[Second Embodiment]
The inspection system 1 according to the first embodiment estimates the bone age based on the scan result of the X-ray film in which the bone is imaged. In contrast, the inspection system 2 according to the second embodiment estimates the bone age based on the X-ray imaging result (digital data) of the bone by the X-ray detector instead of the film scanning result.

  FIG. 21 shows a configuration of the inspection system 2 according to the second embodiment. The inspection system 1 includes a computer 10, an X-ray source 50, an X-ray detector 60, and a cable 70.

  The X-ray source 50 irradiates the bone 80 with X-rays 52. In the figure, the bone 80 is drawn so as to be exposed. This assumes the case where age estimation of a white skeleton is performed. However, the bone 80 may be a bone in a living body.

  The X-ray detector 60 is installed in the irradiation range of the X-rays 52 and detects the intensity of the X-rays 52. The X-ray detector 60 has a detection surface composed of a plurality of X-ray detection elements arranged in a plane. When the inspection system 2 is used, a bone 80 is placed between the X-ray source 50 and the X-ray detector 60. Therefore, the X-ray detector 60 captures an X-ray image of the bone 80. Further, the X-ray detector 60 outputs image digital data (X-ray image data) corresponding to the detection result of the X-rays 52.

  The cable 70 connects the computer 10 and the X-ray detector 60. However, for these connection methods, modifications similar to those in the first embodiment can be used.

  The configuration of computer 10 is substantially the same as that of the first embodiment, and detailed description thereof will not be repeated. The computer 10 according to the second embodiment differs from the computer 10 according to the first embodiment in that X-ray image data is acquired from the X-ray detector 60 instead of from the scanner 20. However, the processing performed by the computer 10 on the X-ray image data is the same as that in the first embodiment.

  The procedure of bone age estimation by the inspection system 2 will be described with reference to FIG. FIG. 22 is a flowchart showing the flow of processing performed when the inspection system 2 estimates the bone age.

  In step S <b> 401, the X-ray source 50 emits X-rays 52. In addition, before the X-ray source 50 irradiates the X-ray 52, the user of the inspection system 2 places the bone 80 between the X-ray source 50 and the X-ray detector 60.

  In step S403, the X-ray detector 60 captures an X-ray image. That is, the X-ray detector 60 detects the intensity of X-rays that have entered the X-ray detector 60. Then, the X-ray detector 60 outputs digital data (X-ray image data) representing the X-ray detection result of each X-ray detection element in the detection surface.

  In step S <b> 405, the computer 10 receives X-ray image data from the X-ray detector 60. The X-ray detector 60 transmits the acquired X-ray image data to the computer 10 every time X-ray image data is acquired. However, for example, the computer 10 may acquire X-ray image data stored in the X-ray detector 60 based on an instruction from the user.

  The processing from step S407 to step S413 is the same as the processing from step S103 to step S109 shown in FIG. 4, and detailed description thereof will not be repeated.

  The bone age inspection method according to the second embodiment estimates the bone age based on the X-ray image data from the X-ray detector 60. Compared to the first embodiment, the user does not have to scan the X-ray film, and thus the bone age can be estimated more easily.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

  The present invention can be used in the field of social medicine, preferably in the field of forensic medicine. That is, the present invention can be used for identification and personal identification of an undetermined corpse (especially a skeletal corpse), which is a practice in these fields.

  1 inspection system, 2 inspection system, 10 computer, 20 scanner, 30 cable, 40 X-ray film, 50 X-ray source, 52 X-ray, 60 X-ray detector, 70 cable, 80 bone, 110 keyboard, 120 mouse, 130 Display, 160 hard disk, 161 program, 162 bone image data, 163 cut image data, 164 reconstruction data, 165 analysis result, 170 external interface, 180 FD drive, 190 optical disk drive, 192 optical disk, 200 USB connector, 202 flash memory, 210 SD drive, 212 SD card, 220 bus, 240 storage unit, 310 input unit, 320 output unit, 330 interface unit, 340 storage unit, 350 control unit, 351 strokes Acquisition unit, 352 image processing unit, 353 image cutout, 354 reconstruction unit 355 brightest pixel extracting unit, 356 area setting unit, 357 bright pixel extraction unit 358 age estimator.

Claims (10)

Image acquisition means for acquiring image data corresponding to X-rays transmitted through the bone;
First area designating means for designating a first area of the image data;
First extraction means for extracting the brightest pixel having the highest luminance from the pixels of the first region;
Second area designating means for designating a second area of a predetermined size including the brightest pixel in the image data;
Second extraction means for extracting a plurality of bright pixels having a luminance equal to or higher than a threshold value corresponding to the highest luminance from the pixels in the second region;
A bone age estimation apparatus comprising: an estimation unit configured to estimate a bone age of the bone based on a distribution characteristic of the plurality of bright pixels that changes according to the bone density of the bone.   The said estimation means calculates | requires the maximum distance and minimum distance from the said brightest pixel to each said bright pixel, and estimates the said bone age based on the ratio with respect to the said maximum distance of the said minimum distance. Bone age estimation device.   The bone age estimation apparatus according to claim 2, wherein the estimation unit estimates the bone age higher as the ratio is lower. The first area includes a plurality of designated areas,
The first extraction unit extracts the brightest pixel for each of the designated areas,
The second area includes a plurality of processing areas each including the brightest pixel of each designated area,
The second extraction unit extracts the bright pixel for each processing region,
The said estimation means calculates | requires the measured value distribution of the said bright pixel in each said process area | region, and estimates the said bone age based on the statistics of the said measured value distribution, The any one of Claim 1 to 3 Bone age estimation device.   5. The bone age estimation apparatus according to claim 1, wherein the first region designating unit sets the first region within a region corresponding to the bone marrow of the bone.   The bone age estimation apparatus according to any one of claims 1 to 5, wherein the second region designating unit designates a region centered on the brightest pixel as the second region.   The bone age estimation apparatus according to any one of claims 1 to 6, wherein the image acquisition means includes a scanner for scanning a film on which an X-ray image of the X-ray transmitted through the bone is recorded. The image acquisition means includes
An X-ray source for outputting the X-ray;
The bone age estimation apparatus according to any one of claims 1 to 6, further comprising: an X-ray detector that outputs from the X-ray source and detects the X-ray transmitted through the bone. A bone age estimation method executed by a computer,
The processor of the computer obtaining image data corresponding to X-rays transmitted through the bone;
The processor designating a first region of the image data;
The processor extracting the brightest pixel having the highest brightness from the pixels of the first region;
The processor designating a second area of a predetermined size including the brightest pixel in the image data;
The processor extracting, from the pixels in the second region, a plurality of bright pixels having a luminance equal to or higher than a threshold corresponding to the highest luminance;
A bone age estimation method comprising: a step of estimating a bone age of the bone based on a distribution characteristic of the plurality of bright pixels that changes in accordance with a bone density of the bone. Obtaining image data corresponding to X-rays that have passed through the bone;
Designating a first region of the image data;
Extracting the brightest pixel having the highest luminance from the pixels of the first region;
Designating a second area of a predetermined size including the brightest pixel in the image data;
Extracting a plurality of bright pixels having a luminance equal to or higher than a threshold value corresponding to the highest luminance from the pixels of the second region;
A bone age estimation program for causing a computer to execute a step of estimating a bone age of the bone based on a distribution characteristic of the plurality of bright pixels that changes in accordance with the bone density of the bone.