JP2010221015A - Three-dimensional human body model generator, three-dimensional human body model generating method, and three-dimensional human body model generating program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To easily generate a three-dimensional human body model for each subject. <P>SOLUTION: A body internal space 37 of a three-dimensional identified model 38 is extracted based on three-dimensional image data D1 imaged by a CT (computed tomography) apparatus or an MRI (magnetic resonance imaging) apparatus, and a body internal region 47 of a three-dimensional standard human body model 40 formed by three-dimensionally modeling each of standard organs is deformed in conformity to the body internal space 37 to generate a three-dimensional subject model 80. The three-dimensional subject model 80 for each subject can thereby be easily generated. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a three-dimensional human body model generation device, a three-dimensional human body model generation method, and a three-dimensional human body model generation program. For example, a three-dimensional human body model used in a virtual reality surgery simulator (hereinafter also referred to as a VR simulator) is generated. It is suitable to be applied to.

  In recent years, endoscopic surgical operations that are less invasive to patients have been actively performed in the medical field. Endoscopic surgery has great benefits for patients, including small wounds, reduction of postoperative pain, shortened hospital stay, and early rehabilitation.

  However, in endoscopic surgery, doctors have to operate forceps with a low degree of freedom and a lack of sensation while viewing images with a narrow field of view and a three-dimensional effect, and special techniques different from open surgery are required. . Therefore, it is necessary to allow a doctor to perform sufficient training to provide a safe and high-quality endoscopic surgery, and many surgical training devices have been devised recently.

  One of the surgical training devices is a VR simulator. The VR simulator represents a three-dimensional human body model and a surgical instrument in a virtual three-dimensional space, and displays the three-dimensional space on a display, thereby allowing a doctor to perform surgery training while showing the display. (For example, refer to Patent Document 1).

  In some surgical training, a human body modeling model is made using a material such as a resin, and training is performed by a doctor using the human body modeling model and an actual surgical instrument. Incidentally, the human body modeling model is produced by, for example, an optical modeling apparatus using a three-dimensional human body model.

  In order to perform such a surgical training to a doctor more realistically, a three-dimensional human body model is finely divided into organs such as a skeleton, a joint, and an organ, and the three-dimensional human body model is converted into a VR simulator or a three-dimensional modeling. It is necessary to have realization information for use in applications such as.

  Here, the realization information for using the 3D human body model in an application such as a VR simulator or 3D modeling is a texture-texture attachment method or the like when the 3D human body model is applied to virtual reality. Furthermore, when applied to a VR simulator, physiological information such as heart rate and blood pressure, organ and skeleton connection information, anatomical information, organ and skeleton Young's modulus, Poisson's ratio, and spring mass model are used. This is physical property information such as a spring constant and a damping coefficient in the dynamic simulation. In the case of application to three-dimensional modeling, resin for optical modeling, support shape, color, and the like.

JP-A-11-231770

  By the way, in a conventional 3D human body model generation apparatus that generates a 3D human body model, 3D image data obtained by imaging a chest mainly of a subject by a CT (Computed Tomography) apparatus or an MRI (Magnetic Resonance Imaging) apparatus is used as a basis. When generating a 3D human body model, it is not possible to easily extract organs, joints, and connection information from the 3D image data. Therefore, the user manually extracts the organs, joints, connection information, etc. More scenes to make.

  Specifically, the three-dimensional human body model generation apparatus extracts a target organ based on the shading of three-dimensional image data, and then manually corrects an extraction defect or erroneous extraction. The three-dimensional human body model generation apparatus causes the user to manually classify the skeleton from the skeleton extracted from the three-dimensional image data according to the morphological positional relationship, and extracts a joint based on the classified skeleton. Furthermore, the 3D human body model generation apparatus manually extracts connection information by comparing the organs, skeletons, and joints extracted from the 3D image data with morphological positional relationships, and then extracts the organs, skeletons, and joints. Attach physical property information to the joint.

  Thus, in the conventional three-dimensional human body model generation device, when generating a three-dimensional human body model, the user is forced to take a lot of time and troublesome work, and easily generate a three-dimensional human body model for each subject. There was a problem that could not be done.

  In addition, as described above, since a three-dimensional human model for each subject cannot be easily generated, the VR simulator can only allow a doctor to perform training using a specific three-dimensional human model and is limited. Will only be trained in a particular situation.

  Therefore, the VR simulator is beginning to see a limit in its training effect, and a 3D human body model generation device that can easily generate a 3D human body model for each subject from 3D image data captured by a CT apparatus or an MRI apparatus. Development of was desired.

  The present invention has been made in consideration of the above points, and a three-dimensional human body model generation device, a three-dimensional human body model generation method, and a three-dimensional human body model generation program capable of easily generating a three-dimensional human body model for each subject. Is to try to propose.

  In order to solve this problem, in the present invention, body space is extracted from three-dimensional image data showing a tomographic image of a human body, and body region data including body space data and organ data associated with the body space data is obtained. The in-vivo region data of the three-dimensional standard human body model provided is transformed to match the in-vivo space extracted by the in-vivo space extraction step. Incidentally, the three-dimensional standard human body model is composed of organs whose positions and sizes are standard for each sex, age, and lesion.

  In the present invention, a skeleton is extracted from three-dimensional image data representing a tomogram of a human body, a plurality of ribs are identified from the skeleton extracted in the skeleton extraction step, and a body space surrounded by the plurality of ribs is extracted. The body region data of the 3D standard human body model including body region data including body space data and each organ data associated with the body space data is transformed to match the body space extracted by the rib identification unit. I tried to make it.

  Thus, by deforming the three-dimensional standard human body model so that the body region corresponding to the body space in the three-dimensional standard human body model matches the body space based on the three-dimensional image data, A three-dimensional human body model can be generated.

  According to the present invention, the subject is deformed so that the body area corresponding to the body space in the 3D standard human body model matches the body space based on the 3D image data. 3D human body model that can generate a 3D human body model including organs such as organs, skeletons, and joints, and can easily generate a 3D human body model for each subject. A generation method and a three-dimensional human body model generation program can be realized.

It is a basic diagram which shows the structure of a three-dimensional human body model production | generation apparatus. It is a basic diagram which shows the functional structure of CPU in 1st Embodiment. It is an approximate line figure showing a horizontal section picture based on three-dimensional image data, a sagittal section picture, and a forehead section image. It is a basic diagram which shows a binarized image. It is a basic diagram which shows a three-dimensional skeleton model. It is a basic diagram which shows the mode of the vertebral body identification of a three-dimensional skeleton model. It is a basic diagram which shows the mode of the rib identification of a three-dimensional skeleton model. It is a basic diagram which shows a three-dimensional identification model and a three-dimensional standard human body model. It is a basic diagram which shows the mode (1) of a deformation | transformation to an up-down direction. It is a basic diagram which shows the mode (2) of a deformation | transformation to an up-down direction. It is a basic diagram which shows the mode (1) of a deformation | transformation to the front-back direction. It is a basic diagram which shows the mode (2) of a deformation | transformation to the front-back direction. It is a basic diagram which shows the mode (1) of a deformation | transformation to the left-right direction. It is a basic diagram which shows the mode (2) of a deformation | transformation to the left-right direction. It is a basic diagram which shows the mode of a deformation | transformation of a rib. It is a flowchart with which it uses for description of a three-dimensional human body model production | generation process procedure. It is a flowchart with which it uses for description of a skeleton extraction process procedure. It is a flowchart with which it uses for description of a vertebral body identification processing procedure. It is a flowchart with which it uses for description of a rib identification processing procedure. It is a flowchart with which it uses for description of a human body model deformation | transformation process procedure. It is a basic diagram which shows the functional structure of CPU in 2nd Embodiment. It is a horizontal sectional view based on three-dimensional image data. It is a basic diagram which shows a three-dimensional skeleton and body surface model. It is a basic diagram which shows a three-dimensional identification model and a three-dimensional standard human body model. It is a flowchart with which it uses for description of a three-dimensional human body model production | generation process procedure. It is a flowchart with which it uses for description of a skeleton and body surface extraction process procedure. It is a flowchart with which it uses for description of a vertebral body identification processing procedure. It is a flowchart with which it uses for description of a body space extraction process procedure. It is a flowchart with which it uses for description of a human body model deformation | transformation process procedure. It is a basic diagram which shows the functional structure of CPU in 3rd Embodiment. It is a basic diagram which shows a three-dimensional skeleton and muscle model. It is a basic diagram which shows the horizontal cross section of a three-dimensional skeleton and a muscle model. It is a basic diagram which shows a three-dimensional identification model and a three-dimensional standard human body model. It is a flowchart with which it uses for description of a three-dimensional human body model production | generation process procedure. It is a flowchart with which it uses for description of a skeletal / muscle extraction processing procedure. It is a flowchart with which it uses for description of a vertebral body identification processing procedure. It is a flowchart with which it uses for description of a body space extraction process procedure. It is a flowchart with which it uses for description of a human body model deformation | transformation process procedure. It is a basic diagram which shows the functional structure of CPU in 4th Embodiment. It is a basic diagram which shows a three-dimensional skeleton and muscle model. It is a basic diagram which shows the feature point of a 17th vertebral body, a sacrum, and a coccyx. It is a basic diagram which shows the horizontal cross section in a three-dimensional skeleton and muscle model. It is a basic diagram which shows a three-dimensional identification model and a three-dimensional standard human body model. It is a flowchart with which it uses for description of a three-dimensional human body model production | generation process procedure. It is a flowchart with which it uses for description of a skeletal / muscle extraction processing procedure. It is a flowchart with which it uses for description of a vertebral body identification processing procedure. It is a flowchart with which it uses for description of a body space extraction process procedure. It is a flowchart with which it uses for description of a human body model deformation | transformation process procedure.

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

<1. First Embodiment>
(1) Configuration of 3D Human Body Model Generation Device As shown in FIG. 1, reference numeral 1 denotes a 3D human body model generation device as a whole, which includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, interface unit 14, storage unit 15 and display unit 16 are connected via a bus 17.

  In the three-dimensional human body model generation device 1, the CPU 11 reads out a basic program stored in the ROM 12, expands it in the RAM 13, and performs overall control according to the basic program, and various application programs stored in the ROM 12 or the storage unit 15. Are expanded in the RAM 13 and various processes are executed in accordance with the various application programs.

  The three-dimensional human body model generation apparatus 1 is connected to an external device via the interface unit 14, and acquires, for example, three-dimensional image data captured by a CT apparatus or an MRI apparatus, or a three-dimensional image described later. The three-dimensional subject model generated by the human body model generation process can be output to the VR simulator.

  The three-dimensional human body model generation device 1 stores the three-dimensional image data acquired through the interface unit 14 and the three-dimensional subject model generated by the three-dimensional human body model generation process in the storage unit 15. The three-dimensional image data, the three-dimensional subject model, and the like can be displayed on the display unit 16.

(2) Three-dimensional human body model generation processing When the CPU 11 expands the three-dimensional human body model generation processing program stored in the ROM 12 in the RAM 13, the interface unit 14, the storage unit 15 and the The display unit 16 is appropriately controlled to execute a three-dimensional human body model generation process.

  When executing the three-dimensional human body model generation process, the CPU 11 functions as a skeleton extraction unit 21, a vertebral body identification unit 22, a rib identification unit 23, and a human body model deformation unit 24 as shown in FIG. ing.

(2-1) Skeletal Extraction Processing When the CPU 11 executes the three-dimensional human body model generation processing, the skeleton extraction processing is executed by the skeleton extraction unit 21. This skeleton extraction process will be described in detail.

  The three-dimensional human body model generation apparatus 1 stores three-dimensional image data D1 formed by laminating a number of cross-sectional images obtained by, for example, imaging a subject's chest with a predetermined slice width by a CT apparatus or an MRI apparatus. Stored in the unit 15.

  The three-dimensional image data D1 is in a data format conforming to, for example, DICOM (Digital Imaging and Communications in Medicine) standard, and includes patient information, examination information, imaging conditions, and the like as incidental information.

  When executing the skeleton extraction process, the skeleton extraction unit 21 reads the three-dimensional image data D1 from the storage unit 15, creates volume data based on the three-dimensional image data D1, and slices the volume data in three directions. Thus, as shown in FIG. 3, a horizontal cross-sectional image CG1, a sagittal cross-sectional image CG2, and a forehead cross-sectional image CG3 based on the three-dimensional image data D1 are created and displayed on the display unit 16.

  Here, the three-dimensional image data D1 is obtained by using the horizontal cross-sectional image CG1, the sagittal cross-sectional image CG2, and the forehead cross-sectional image CG3 to indicate the luminance (accordingly, the image) (Shading level).

  When the 3D image data D1 is captured by, for example, a CT apparatus, in the 3D image data D1, a skeleton with a high X-ray absorption rate appears white, and air, which is a portion with a low X-ray absorption rate, appears black. The organs and muscles, which have an intermediate absorption rate, are reflected in an intermediate color (gray) between white and black.

  Even when the three-dimensional image data D1 is captured by the MRI apparatus, the light and shade levels of the skeleton and other portions are greatly different.

  Therefore, the skeleton extraction unit 21 uses a predetermined upper threshold value and lower threshold value such that the gray level of the skeleton displayed in the three-dimensional image data D1 is “1” and the gray level of other tissues is “0”. Binarization processing is performed.

  Incidentally, the upper and lower thresholds are set so that the gray level of the skeleton displayed in the three-dimensional image data D1 is between the upper threshold and the lower threshold, and the gray levels of other tissues are higher than the lower threshold or lower than the lower threshold. Is set.

  As a result of performing the binarization processing, the skeleton extraction unit 21 has a white skeleton (lightness level “1”) and all except the skeleton is black (lightness level “0”) as illustrated in FIG. 4. The binarized image BWG is generated, and the binarized image BWG is displayed on the display unit 16.

  Then, as shown in FIG. 5, the skeleton extraction unit 21 extracts a pixel whose gray level of the binarized image BWG obtained by the binarization process is “1” (white), and the voxel corresponding to the pixel Are generated and arranged three-dimensionally to generate a three-dimensional skeleton model 30 in which the skeleton 31 is modeled in three dimensions, and the data of the three-dimensional skeleton model 30 (hereinafter referred to as three-dimensional skeleton model data). (Also referred to as D11) (FIG. 2) is stored in the storage unit 15, and the skeleton extraction process is terminated.

  Incidentally, each voxel can be added with a unique value representing the characteristic of the voxel (hereinafter also referred to as a voxel value), and each voxel corresponding to the skeleton 31 has, for example, each of the voxels. A voxel value indicating that the voxel is the skeleton 31 is added.

  The skeleton extraction unit 21 has a coordinate system having front and rear, top and bottom, left and right orientations based on the imaging conditions included in the three-dimensional image data D1, and actual dimensions based on the slice width of the cross-sectional image and the pixel size of the cross-sectional image. The coordinate system of the three-dimensional skeleton model 30 is converted.

  In this way, the skeleton extraction unit 21 performs binarization processing on the three-dimensional image data D1 obtained from the CT apparatus or the MRI apparatus, and the skeleton 31 of the subject from the binarized image BWG obtained as a result. Is extracted to generate a three-dimensional skeleton model 30.

(2-2) Vertebral body identification process CPU11 will perform a vertebral body identification process by the vertebral body identification part 22 (FIG. 2), if complete | finishing a skeleton extraction process. This vertebral body identification process will be described in detail.

  The vertebral body identification unit 22 reads the 3D skeleton model data D11 stored in the storage unit 15, and identifies a vertebral body from the 3D skeleton model 30 based on the 3D skeleton model data D11.

  Here, the human spinal column is connected by an intervertebral disc in which a plurality of vertebral bodies are soft tissues. Therefore, when the skeleton extraction unit 21 performs binarization processing on the three-dimensional image data D1, the intervertebral disc that is a soft tissue has a gray level of “0” and is not extracted as a skeleton. Therefore, in the three-dimensional skeleton model 30, a plurality of vertebral bodies are extracted independently without being connected.

  Further, since the shape of the human vertebral body is similar, the vertebral body identification unit 22 reads out the vertebral body template data D2 stored in the storage unit 15 in advance, and a standard vertebral body based on the vertebral body template data D2 is read out. Pattern matching is performed between the vertebral body template having a body shape and the three-dimensional skeleton model 30, and as a result, a plurality of vertebral bodies having a substantially cylindrical shape are detected.

  The vertebral body identifying unit 22 detects the morphological midpoints of the detected plurality of vertebral bodies as feature points, and identifies the detected plurality of vertebral bodies based on the morphological characteristics. Here, the morphological midpoint of the vertebral body is the center of gravity of a rectangular parallelepiped inscribed in the vertebral body and is detected based on the morphological characteristics.

  Specifically, when all of the vertebral bodies of the cervical vertebra, the thoracic vertebra, and the lumbar vertebra are detected in the detected plurality of vertebral bodies, the vertebral body identifying unit 22 identifies the plurality of vertebral bodies in order from the top. .

  As shown in FIG. 6, the vertebral body identifying unit 22 extends left and right into the vertebral body when all of the vertebral bodies of the cervical vertebra, the thoracic vertebra and the lumbar vertebra are not detected in the detected plurality of vertebral bodies. If there is a skeleton and such skeletons are also present on the upper and lower sides, the vertebral body of the upper thoracic vertebra is identified as one of the vertebral bodies 32A of the first thoracic vertebra to the vertebral body 32H of the eighth thoracic vertebra. To do.

  The vertebral body identification unit 22 is a vertebral body having a skeleton extending to the left and right, and when a skeleton extending only to the left and right is present, the vertebral body of the tenth thoracic vertebra 32J to the vertebrae of the twelfth thoracic vertebra It is identified as any of the body 32L.

  Incidentally, the right tenth rib 34J and the left tenth rib 35J (FIG. 7) extend over the vertebral body 32I of the ninth thoracic vertebra 32I and the vertebral body 32I of the ninth thoracic vertebra. In some cases, it is not identified whether the attribute is included in the upper, middle, or lower attributes as described above.

  The vertebral body identification unit 22 uses the vertebral bodies of the first thoracic vertebra 32A to the 12th thoracic vertebra based on the shape and inclination of the vertebral body, the position information of the skeleton other than the vertebral body, and the three-dimensional image data D1. 32L may be identified. In the following description, the first thoracic vertebral body 32A to the twelfth thoracic vertebral body 32L are also referred to as the first vertebral body 32A to the twelfth vertebral body 32L, respectively.

  In this way, the vertebral body identification unit 22 identifies, for example, the first vertebral body 32A to the twelfth vertebral body 32L from among the plurality of detected vertebral bodies. The vertebral body identification unit 22 detects the feature points of the identified first vertebral body 32A to twelfth vertebral body 32L as the first feature point 33A to the twelfth feature point 33L.

  Then, the vertebral body identification unit 22 obtains the positional information and anatomical names of the identified first vertebral body 32A to twelfth vertebral body 32L and the positional information of the first feature point 33A to twelfth feature point 33L as vertebral body information D12. Is stored in the storage unit 15 and the vertebral body identification process is terminated.

(2-3) Rib Identification Process When the CPU 11 finishes the vertebral body identification process, the rib identification unit 23 (FIG. 2) executes the rib identification process. This rib identification process will be described in detail.

  The rib identification unit 23 reads the three-dimensional skeleton model data D11 and the vertebral body information D12 stored in the storage unit 15 and identifies the ribs from the skeleton 31 of the three-dimensional skeleton model 30 based on the vertebral body information D12.

  Here, the human rib is an arcuate skeleton that extends from the thoracic vertebra, which is a part of the vertebral body, to the left and right. Therefore, the rib identifying unit 23 starts and ends with respect to the skeleton 31 of the three-dimensional skeleton model 30 based on the three-dimensional skeleton model data D11, starting from each of the first vertebral body 32A to the twelfth vertebral body 32L based on the vertebral body information D12. By detecting a part of the skeleton 31 extending in the direction and tracing the skeleton 31 from the detected part as a starting point, as shown in FIG. 7, the right first rib 34A to the right twelfth rib 34L and the left first rib The first rib 35A to the left twelfth rib 35L are identified.

  Incidentally, the human rib is connected to the sternum 36 via the costal cartilage, and when the costal cartilage is binarized by the skeleton extraction unit 21 with respect to the three-dimensional image data D1, the density level is “0”. Therefore, the skeleton 31 is not extracted. Accordingly, the three-dimensional skeleton model 30 can extract only the right first rib 34A to the right twelfth rib 34L and the left first rib 35A to the left twelfth rib 35L.

  The rib identification unit 23 detects a forehead cross section at predetermined intervals for each of the identified right first rib 34A to right twelfth rib 34L and left first rib 35A to left twelfth rib 35L, and the forehead cross section. A center line (not shown) is detected by interpolating the center point of the curve.

  Next, the rib identifying unit 23 extracts a body space inscribed in the identified right first rib 34A to right twelfth rib 34L and left first rib 35A to left twelfth rib 35L.

  Specifically, the rib identification unit 23 extracts a substantially elliptic curved surface (not shown) inscribed in the right first rib 34A and the left first rib 35A. Here, since the right first rib 34A and the left first rib 35A are not connected, the rib identifying unit 23 first connects one ends of the right first rib 34A and the left first rib 35A on the first vertebral body 32A side. By interpolating with a curve so as to pass through one feature point 33A and also interpolating with a curve so as to pass through the sternum 36 also on the front end side, it is substantially inscribed in the right first rib 34A and the left first rib 35A. Extract an elliptical curved surface.

  Here, the sternum 36 used for the interpolation by the curve on the front end side is all the sternum pattern, the sternum body, and the xiphoid process without distinguishing the sternum pattern, the sternum body, and the xiphoid process from the skeleton 31 of the three-dimensional skeleton model 30 at the height position of the thoracic vertebra Identified as sternum.

  Similarly, the rib identifying unit 23 extracts a substantially elliptical curved surface inscribed in each of the right second rib 34B and the left second rib 35B to the right twelfth rib 34L and the left twelfth rib 35L. Here, when the sternum 36 is not present at the tip of the front end of the rib, particularly when the right sixth rib 34F and the left sixth rib 35F to the right twelfth rib 34L and the left twelfth rib 35L, extrapolation from the front end is performed. To extract a substantially elliptical curved surface inscribed. In this way, the rib identification unit 23 extracts 12 curved surfaces stacked in the vertical direction inscribed from the right first rib 34A and the left first rib 35A to the right twelfth rib 34L and the left twelfth rib 35L.

  Then, the rib identifying unit 23 sets the space from the first feature point 33A to the twelfth feature point 33L in the up-down direction in the three-dimensional space formed by stacking the extracted 12 curved surfaces in the up-down direction (see FIG. 8). Extracted as (A) and (B)).

  The rib identification unit 23 includes position information and centerline information of the sternum 36 identified from the skeleton 31 of the three-dimensional skeleton model 30, the right first rib 34A to the right twelfth rib 34L, and the left first rib 35A to the left twelfth rib 35L. Is stored in the storage unit 15 as rib information D13.

  The rib identification unit 23 stores the positional information of the body space 37 inscribed in the right first rib 34A to the right twelfth rib 34L and the left first rib 35A to the left twelfth rib 35L in the storage unit 15 as the body space information D14. Then, the rib identification process is terminated.

(2-4) Human body model deformation | transformation process CPU11 will perform a human body model deformation | transformation process by the human body model deformation | transformation part 24 (FIG. 2), after complete | finishing a rib identification process. This human body model deformation process will be described in detail.

  The human body model deforming unit 24 includes the three-dimensional skeleton model data D11 generated by the skeleton extracting unit 21, the vertebral body information D12 generated by the vertebral body identifying unit 22, the rib information D13 generated by the rib identifying unit 23, The spatial information D14 is read from the storage unit 15.

  Here, the three-dimensional skeleton model data D11 generated by the skeleton extracting unit 21, the vertebral body information D12 generated by the vertebral body identifying unit 22, the rib information D13 generated by the rib identifying unit 23, and the body space information D14 are combined. Also referred to as three-dimensional identification model data D15.

  As shown in FIGS. 8A and 8B, the human body model deforming unit 24 performs the first vertebral body 32A to the twelfth vertebral body 32L on the right side of the skeleton 31 based on the three-dimensional identification model data D15. A first rib 34A to a right twelfth rib 34L, a left first rib 35A to a left twelfth rib 35L, and a sternum 36 are identified, and a first feature point 33A to a twelfth feature point 33L and a body space 37 are added. An identification model 38 is generated.

  Then, the human body model deforming unit 24 cuts the internal space 37 of the three-dimensional identification model 38 in a horizontal plane that includes the first feature point 33A to the twelfth feature point 33L, thereby making the first divided space 37A to the eleventh divided portion. The space 37K is divided (FIG. 8B).

  8A is a right side view of the three-dimensional identification model 38. FIG. 8B is a sagittal cross-sectional view passing through the third feature point 33C of the three-dimensional identification model 38.

  On the other hand, the human body model deforming unit 24 reads data (hereinafter also referred to as 3D standard human body model data) D3 of the 3D standard human body model 40 (FIG. 8C) from the storage unit 15.

  As shown in FIGS. 8C and 8D, the three-dimensional standard human body model 40 is obtained by modeling a standard human body in three dimensions with a large number of voxels. A value indicating a living tissue constituting a human body such as a skeleton, a joint, and an organ is added as a voxel value (each organ data). Further, the three-dimensional standard human body model 40 is provided with a coordinate system having a distance dimension, and this coordinate system is a global coordinate system that does not depend on the human body model generation process.

  The three-dimensional standard human body model data D3 includes information on the feature points of the vertebral bodies in the three-dimensional standard human body model 40 and position information of a region (hereinafter also referred to as a body region) 47 surrounded by the ribs. Has been made.

  Accordingly, the human body model deforming unit 24 reads out the three-dimensional standard human body model data D3, thereby causing the first feature point 43A to the twelfth feature point 43L, the right first rib 44A to the right twelfth rib 44L, and the left first rib to A body region 47 surrounded by the left twelfth rib (not shown) can be recognized.

  Here, the body region 47 is located at a position corresponding to the body space 37 in the three-dimensional identification model 38, and contains a living tissue (organ data) such as an organ.

  When the human body model deforming unit 24 reads the three-dimensional standard human body model data D3, the human body region 47 of the three-dimensional standard human body model 40 is cut in a horizontal plane including the first feature point 43A to the twelfth feature point 43L. Thus, the first divided area 47A to the eleventh divided area 47K are divided.

  Here, FIG. 8C is a right side view of the three-dimensional standard human body model 40. FIG. 8D is a sagittal sectional view passing through the third feature point 43 </ b> C of the three-dimensional standard human body model 40.

  Incidentally, here, the case where the in-vivo region 47 of the three-dimensional standard human body model 40 is smaller than the body space 37 of the three-dimensional identification model 38, that is, the case where the subject's physique is larger than the standard physique will be described. The same can be done when the body region 47 is larger than the body space 37.

  In addition, here, mainly, a space sandwiched between horizontal planes passing through the fifth feature point 33E and the sixth feature point 33F of the three-dimensional identification model 38, and the fifth feature point 43E and the sixth feature of the three-dimensional standard human body model 40, respectively. A specific description will be given of a region sandwiched between horizontal planes that respectively pass through the points 43F, but the same applies to other spaces and regions.

  As shown in FIGS. 9A and 9B, the human body model deforming unit 24 extracts a sagittal section 37Ea of the fifth divided space 37E passing through the third feature point 33C in the three-dimensional identification model 38.

  Further, the human body model deforming unit 24 extracts a sagittal section 47Ea of the fifth divided region 47E passing through the third feature point 43C (FIG. 8D) in the three-dimensional standard human body model 40.

  When extracting the sagittal section 37Ea and the sagittal section 47Ea, the human body model deforming unit 24 extracts the sagittal section 37Ea and the sagittal section 47Ea by approximating a trapezoid.

  Here, FIG. 9A is a diagram in which the sagittal section 47Ea is superimposed on the sagittal section of the three-dimensional identification model 38 passing through the third feature point 33C. FIG. 9B is a diagram in which the left part of the fifth divided space 37E and the left part of the fifth divided region 47E are overlapped.

  The human body model deforming unit 24 calculates the ratio (Ta / Tb) between the vertical height Ta of the extracted sagittal section 37Ea and the vertical height Tb of the sagittal section 47Ea.

  Then, as shown in FIG. 9C, the human body model deforming unit 24 divides the fifth divided region 47E in a plurality of horizontal planes at predetermined intervals in the vertical direction, and sets the horizontal plane intervals to a ratio (Ta / Tb). Accordingly, the fifth divided region 57E having a sagittal section 57Ea having a height of Ta is generated by expanding and contracting in the vertical direction.

  At this time, the human body model deforming unit 24 is a portion sandwiched between horizontal planes passing through the fifth feature point 43E and the sixth feature point 43F of the skeleton 41 in the three-dimensional standard human model 40 (FIGS. 8C and 8D), respectively. In the same manner as in the fifth divided region 47E, it is expanded and contracted in the vertical direction according to the ratio (Ta / Tb).

  Accordingly, the interval between the fifth feature point 43E and the sixth feature point 43F is the same as the interval between the fifth feature point 33E and the sixth feature point 33F in the three-dimensional identification model 38.

  Similarly, the human body model deforming unit 24 expands and contracts the first divided region 47A to the fourth divided region 47D and the sixth divided region 47F to the eleventh divided region 47K in the vertical direction as well as the corresponding skeleton 41 portion. Also expand and contract in the vertical direction.

  Therefore, the human body model deforming unit 24 deforms the three-dimensional standard human body model 40 shown in FIG. 10A so as to expand and contract in the vertical direction, and has a skeleton 51 and a body region 57 as shown in FIG. A three-dimensional deformation model 50 is generated.

  Next, as shown in FIGS. 11A and 11B, the human body model deforming unit 24 has three hypotenuses of the sagittal section 57Ea of the fifth divided region 57E in the three-dimensional deformed model 50 (FIG. 10B). The fifth divided region 57E is deformed so as to expand and contract in the front-rear direction so as to coincide with the corresponding oblique side of the sagittal section 37Ea of the fifth divided space 37E in the dimension identification model 38.

  Specifically, the human body model deforming unit 24 equally divides the upper surface of the third divided space 37C in the three-dimensional identification model 38 (horizontal cross section of the body space 37 passing through the third feature point 33C) into two equally in the front-rear direction. The forehead cross section is set as the reference plane SS1. In addition, the human body model deforming unit 24 equally divides the upper surface of the three-dimensional deformed model 50 (for example, a horizontal section of the in-vivo region 57 passing through the third feature point 43C) into two in the front-rear direction. The forehead cross section is set as the reference plane SS2.

  Here, FIG. 11A is a diagram in which the sagittal section 57Ea is superimposed on the sagittal section of the three-dimensional identification model 38 passing through the third feature point 33C. FIG. 11B is a diagram in which the left portion of the fifth divided space 37E and the left portion of the fifth divided region 57E are overlapped.

  As shown in FIG. 11C, the human body model deforming unit 24 has the lengths L1a and L2a of the upper bases in the front-rear direction and the lower bases of the sagittal section 37Ea of the fifth divided space 37E with reference to the reference plane SS1. The lengths L3a and L4a are calculated.

  The human body model deforming unit 24 also calculates the lengths L1b and L2b of the upper base in the front-rear direction and the lengths L3b and L4b of the lower base with respect to the reference plane SS2 for the sagittal section 57Ea of the fifth divided region 57E. To do.

  The human body model deforming unit 24 linearly interpolates the ratio (L1a / L1b) and the ratio (L3a / L3b) from the upper base to the lower base on the front side of the reference plane SS2 of the fifth divided region 57E. A ratio for expanding / contracting the fifth divided region 57E in a predetermined interval from the bottom to the bottom is calculated. Then, the human body model deforming unit 24 expands and contracts the front portion of the fifth divided region 57E from the reference plane SS2 in the forward direction using the calculated ratio.

  Similarly, the human body model deforming unit 24 linearly interpolates the ratio (L2a / L2b) and the ratio (L4a / L4b) from the upper base to the lower base on the rear side of the reference plane SS2 of the fifth divided region 57E. A ratio for expanding / contracting the fifth divided region 57E in a predetermined interval from the upper base to the lower base is calculated. Then, the human body model deforming unit 24 expands / contracts the rear portion of the fifth divided region 57E from the reference plane SS2 in the backward direction using the calculated ratio.

  Thus, as shown in FIG. 11D, the human body model deforming unit 24 expands and contracts the fifth divided region 57E in the front-rear direction, thereby having a fifth divided portion having a sagittal section 67Ea that matches the sagittal section 37Ea. A region 67E is generated.

  At this time, similarly to the fifth divided region 57E, the human body model deforming unit 24 also applies the reference to the skeleton 51 part sandwiched between the horizontal planes passing through the fifth feature point 43E and the sixth feature point 43F in the three-dimensional deformed model 50, respectively. The surface SS2 is expanded and contracted in the front-rear direction.

  Similarly, the human body model deforming unit 24 expands and contracts in the front-rear direction with respect to the other divided areas (not shown) of the three-dimensional deformed model 50 with reference to the reference plane SS2, and also the front and back of the corresponding skeleton 51 portion. Stretch in the direction.

  Therefore, the human body model deforming unit 24 expands and contracts the three-dimensional deformed model 50 shown in FIG. 12A in the front-rear direction with reference to the reference plane SS2, thereby, as shown in FIG. A three-dimensional deformation model 60 having 67 is generated.

  Subsequently, as shown in FIGS. 13A and 13B, the human body model deforming unit 24 forms a forehead cross section in a three-dimensional identification model 38 that approximates a trapezoidal shape where the fifth divided space 37E and the reference plane SS1 intersect. Extract as 37Eb.

  Further, the human body model deforming unit 24 extracts a trapezoidal approximate cross section where the fifth divided region 67E and the reference plane SS2 intersect in the three-dimensional deformable model 60 as the forehead cross section 67Eb.

  Here, FIG. 13A is a diagram in which the forehead cross section 67Eb is superimposed on the forehead cross section of the reference plane SS1 of the three-dimensional identification model 38. FIG. 13B is a diagram in which the rear portion of the fifth divided space 37E and the rear portion of the fifth divided region 67E are overlapped.

  The human body model deforming unit 24 is configured so that the hypotenuse of the forehead cross section 67Eb of the fifth divided region 67E in the three-dimensional deformable model 60 matches the corresponding hypotenuse of the forehead cross section 37Eb of the fifth subdivision space 37E in the three-dimensional identification model 38. Then, the fifth divided region 67E is deformed to expand and contract in the left-right direction.

  Specifically, the human body model deforming unit 24 uses, for example, the sagittal section passing through the third feature point 33C in the three-dimensional identification model 38 as the reference plane SS3, and passes through the third feature point 43C of the three-dimensional deformation model 60, for example. A sagittal section is set as the reference plane SS4.

  Then, as shown in FIG. 13C, the human body model deforming unit 24 has the length of the upper base in the left-right direction with respect to the reference plane SS3 with respect to the forehead cross section 37Eb of the fifth divided space 37E in the three-dimensional identification model 38. W1a and W2a and lower bottom lengths W3a and W4a are calculated.

  Further, the human body model deforming unit 24 has the upper base lengths W1b and W2b and the lower base length W3b in the left-right direction with respect to the reference plane SS4 with respect to the forehead cross section 67Eb of the fifth divided region 67E in the three-dimensional deformation model 60. And W4b.

  The human body model deforming unit 24 linearly interpolates the ratio (W1a / W1b) and the ratio (W3a / W3b) from the upper base to the lower base on the left side of the reference plane SS4 of the fifth divided region 67E. A ratio for expanding and contracting the fifth divided region 67E in the left direction from the bottom to the bottom is calculated. Then, the human body model deforming unit 24 expands / contracts the left portion of the fifth divided region 67E from the reference plane SS4 using the calculated ratio in the left direction.

  Similarly, the human body model deforming unit 24 linearly interpolates the ratio (W2a / W2b) and the ratio (W4a / W4b) from the upper base to the lower base on the right side of the reference plane SS4 of the fifth divided region 67E. A ratio for expanding / contracting the fifth divided region 67E in the right direction from the bottom to the bottom is calculated. Then, the human body model deforming unit 24 expands and contracts the right side portion of the fifth divided region 67E from the reference plane SS4 using the calculated ratio in the right direction.

  Thereby, as shown in FIG. 13D, the human body model deforming unit 24 expands and contracts the fifth divided region 67E in the left-right direction, thereby having a fifth divided region having a forehead cross section 77Eb coinciding with the forehead cross section 37Eb. 77E is generated.

  At this time, similarly to the fifth divided region 67E, the human body model deforming unit 24 also includes a portion sandwiched between horizontal planes passing through the fifth feature point 43E and the sixth feature point 43F of the skeleton 61 in the three-dimensional deformed model 60. The reference plane SS4 is expanded and contracted in the left-right direction.

  Similarly, the human body model deforming unit 24 expands and contracts the other divided regions (not shown) of the three-dimensional deformed model 60 in the left-right direction with reference to the reference plane SS4, and also the left and right sides of the corresponding skeleton 61 portion. Stretch in the direction.

  Accordingly, the human body model deforming unit 24 deforms the three-dimensional deformation model 60 shown in FIG. 14A so as to expand and contract in the left-right direction with reference to the reference plane SS4, and three-dimensional deformation as shown in FIG. 14B. A model 70 is generated.

  In this way, the human body model deforming unit 24 expands / contracts the fifth divided region 47E of the three-dimensional standard human model 40 in the vertical direction, the front / rear direction, and the left / right direction in accordance with the shape of the fifth divided space 37E of the three-dimensional identification model 38. Let

  The human body model deforming unit 24 also applies to the first divided area 47A to the fourth divided area 47D of the three-dimensional standard human body model 40 in the same manner as the fifth divided area 47E. It is expanded and contracted in the vertical direction, the front-rear direction, and the left-right direction according to the shape of the quadrant 37D.

  Furthermore, similarly to the sixth divided region 47F to the eleventh divided region 47K of the three-dimensional standard human body model 40, the human body model deforming unit 24 similarly shapes the sixth divided space 37F to the eleventh divided space 37K of the three-dimensional identification model 38. It is deformed by expanding and contracting in the vertical direction, the front-rear direction, and the left-right direction according to the above.

  Subsequently, as shown in FIG. 15A, the human body model deforming unit 24, in the three-dimensional identification model 38, the reference plane SS1, the center line (not shown) of the right first rib 34A to the right eleventh rib 34K, and The intersection points 39A to 39K are respectively detected. Further, in the three-dimensional identification model 38, the human body model deforming unit 24 extrapolates the center line of the right twelfth rib 34L to the reference plane SS1, and calculates the point as an intersection 39L. The human body model deforming unit 24 detects points corresponding to the detected intersections 39A to 39K as the passing points 79A to 79K in the three-dimensional deformed model 70, and calculates the passing point 79L in the same manner as the intersection 39L.

  Furthermore, the human body model deforming unit 24 moves the height positions of the passage points 79A to 79L to the corresponding intersection points 39A to 39L, and generates the passage points 89A to 89L.

  Then, as shown in FIG. 15B, the human body model deforming unit 24 starts from the first right rib 74A to the right twelfth rib 74L and the first feature point 43A to the twelfth feature point 43L of the three-dimensional deformation model 70. And passing through the passing points 89A to 89L and deforming so as to circumscribe the body region 77, respectively.

  Here, FIG. 15B shows the right first rib 74A to the right twelfth rib 74L before deformation by broken lines, and the right first rib 84A to the right twelfth rib 84L after deformation by solid lines.

  The human body model deforming unit 24 deforms the left first rib to the left twelfth rib (not shown) of the three-dimensional deformation model 70 in the same manner. By performing such deformation, the human body model deforming unit 24 generates a three-dimensional subject model 80.

  The human body model deforming unit 24 stores the generated data (hereinafter, also referred to as 3D subject model data) D16 of the 3D subject model 80 in the storage unit 15 (FIG. 2).

  As a result, the 3D human body model generation device 1 sends the 3D subject model data D16 to a VR simulator or the like connected via the interface unit 14, and the 3D subject model data D16 based on the 3D subject model data D16. A doctor can perform a surgical simulation using the examiner model 80.

  By the way, when the 3D human body model generation apparatus 1 generates the 3D subject model 80 by deforming the in-vivo region 47 of the 3D standard human body model 40 to fit the internal space 37 of the 3D identification model 38, the 3D subject model 80 is generated. The realization information of the dimensional standard human body model 40 is inherited without being lost.

  In addition, after the three-dimensional human body model generation device 1 generates the three-dimensional subject model 80, the user can check the model data generated in each step, and the process returns to the step designated by the user. The 3D human body model generation process can be redone.

(3) 3D Human Body Model Generation Processing Procedure Next, the above-described 3D human body model generation processing procedure will be described in detail using a flowchart.

  That is, as shown in FIG. 16, the CPU 11 proceeds from the start step of the routine RT1 to the subroutine SRT1, and performs a skeleton extraction process by the skeleton extraction unit 21.

  Specifically, as shown in FIG. 17, the CPU 11 enters from the start step of the subroutine SRT1, moves to the next step SP1, reads out the 3D image data D1 from the storage unit 15, and copies it to the 3D image data D1. Predetermined upper and lower thresholds are set so that the gray level of the skeleton is “1”, and the process proceeds to the next step SP2.

  In step SP2, the CPU 11 performs binarization processing on the three-dimensional image data D1 using the upper limit threshold and the lower limit threshold, and proceeds to the next step SP3.

  In step SP3, the CPU 11 generates the three-dimensional skeleton model 30 by extracting the subject's skeleton 31 from the binarized image BWG (FIG. 4) obtained by performing the binarization process, and the skeleton extraction process. And the process proceeds to the next subroutine SRT2 (FIG. 16).

  In the subroutine SRT2, the CPU 11 performs vertebral body identification processing by the vertebral body identification unit 22. Specifically, as shown in FIG. 18, the CPU 11 enters from the start step of the subroutine SRT2, moves to the next step SP11, and performs pattern matching between the three-dimensional skeleton model 30 and the vertebral body template based on the vertebral body template data D2. Thus, a plurality of vertebral bodies having a substantially cylindrical shape are detected, and the process proceeds to the next step SP12.

  In step SP12, the CPU 11 detects the midpoints of the plurality of vertebral bodies detected in step SP11 as feature points, and proceeds to the next step SP13.

  In step SP13, the CPU 11 identifies the first vertebral body 32A to the twelfth vertebral body 32L (FIG. 6) based on the morphological features of the plurality of vertebral bodies detected in step SP12, and the first vertebral body 32A to The feature points of the twelfth vertebral body 32L are set as the first feature point 33A to the twelfth feature point 33L, respectively, and the vertebral body identification process is terminated, and the process proceeds to the next subroutine SRT3 (FIG. 16).

  In the subroutine SRT3, the CPU 11 performs a rib identification process by the rib identification unit 23. Specifically, as shown in FIG. 19, the CPU 11 enters from the start step of the subroutine SRT3, moves to the next step SP21, and moves left and right from the first vertebral body 32A to the twelfth vertebral body 32L in the three-dimensional skeleton model 30. The extending skeleton 31 portion is detected, and the process proceeds to the next step SP22.

  In step SP22, the CPU 11 traces the skeleton 31 with the skeleton 31 portion detected in step SP21 as a starting point, whereby the right first rib 34A to the right twelfth rib 34L and the left first rib 35A to the left twelfth. The rib 35L is identified, and the process proceeds to the next step SP23.

  In step SP23, the CPU 11 detects the center lines of the right first rib 34A to the right twelfth rib 34L and the left first rib 35A to the left twelfth rib 35L, and proceeds to the next step SP24.

  In step SP24, the CPU 11 causes the right first rib 34A to the right twelfth rib 34L, the left first rib 35A to the left twelfth rib 35L, the sternum 36, the horizontal plane passing through the first feature point 33A and the horizontal plane passing through the twelfth feature point 33L. The body space 37 surrounded by is extracted, the rib identification process is terminated, and the process proceeds to the next subroutine SRT4 (FIG. 16).

  In the subroutine SRT4, the CPU 11 performs a human body model deformation process by the human body model deformation unit 24. Specifically, as shown in FIG. 20, the CPU 11 enters from the start step of the subroutine SRT4, moves to the next step SP31, and moves the internal space 37 of the three-dimensional identification model 38 to the first feature point 33A to the twelfth feature. Dividing into a first divided space 37 </ b> A to an eleventh divided space 37 </ b> K by rounding off at horizontal planes including the respective points 33 </ b> L (FIG. 8B).

  Further, the CPU 11 cuts the in-vivo region 47 of the three-dimensional standard human body model 40 into a first divided region 47A to an eleventh divided region 47K by cutting the body region 47 into horizontal planes including the first feature point 43A to the twelfth feature point 43L. Divide and move to next step SP32.

  In step SP32, the CPU 11 causes the fifth divided region so that, for example, the height Tb of the fifth divided region 47E in the three-dimensional standard human body model 40 matches the height Ta of the fifth divided space 37E of the three-dimensional identification model 38. 47E is expanded and contracted in the vertical direction, and the corresponding skeleton 41 portion is also expanded and contracted in the vertical direction.

  Similarly, the CPU 11 expands and contracts the first divided region 47A to the fourth divided region 47D and the sixth divided region 47F to the eleventh divided region 47K in the vertical direction and also expands and contracts the corresponding skeleton 41 portion in the vertical direction. Then, the three-dimensional deformation model 50 is generated, and the process proceeds to the next step SP33.

  In step SP33, the CPU 11 extracts, for example, the sagittal section 37Ea of the fifth divided space 37E in the three-dimensional identification model 38 and the sagittal section 57Ea of the fifth divided region 57E in the three-dimensional deformation model 50, and proceeds to the next step SP34. Move.

  In step SP34, the CPU 11 expands and contracts the fifth divided region 57E in the front-rear direction using the reference plane SS2 as a reference so that the hypotenuse of the sagittal section 57Ea coincides with the hypotenuse of the sagittal section 37Ea.

  Similarly, the CPU 11 generates a three-dimensional deformation model 60 by expanding and contracting the other divided regions (not shown) in the three-dimensional deformation model 50 in the front-rear direction and expanding and contracting the skeleton 51 in the front-rear direction. The process proceeds to step SP35.

  In step SP35, the CPU 11 extracts, for example, the forehead section 37Eb of the fifth divided space 37E in the three-dimensional identification model 38 and the forehead section 67Eb of the fifth divided area 67E in the three-dimensional deformation model 60, and proceeds to the next step SP36. Move.

  In step SP36, the CPU 11 expands and contracts the fifth divided region 67E in the left-right direction with reference to the reference plane SS4 so that the hypotenuse of the forehead cross section 67Eb coincides with the hypotenuse of the forehead cross section 37Eb.

  Similarly, the CPU 11 generates a three-dimensional deformation model 70 by expanding and contracting the other divided regions (not shown) in the three-dimensional deformation model 60 in the left-right direction and expanding and contracting the skeleton 61 in the left-right direction. The process proceeds to step SP37.

  In step SP37, the CPU 11 detects intersections 39A to 39K between the reference plane SS1 and the center lines of the right first rib 34A to the right eleventh rib 34K in the three-dimensional identification model 38, respectively. Further, in the three-dimensional identification model 38, the CPU 11 extrapolates the center line of the right twelfth rib 34L to the reference plane SS1, and calculates an intersection 39L.

  In the three-dimensional deformation model 70, the CPU 11 detects points corresponding to the detected intersections 39A to 39K as passing points 79A to 79K, and calculates the passing point 79L in the same manner as the intersection point 39L. Further, the CPU 11 generates the passing points 89A to 89L by moving the height positions of the passing points 79A to 79L to the corresponding intersections 39A to 39L, respectively.

  Then, the CPU 11 starts from the first right rib 74A to the right twelfth rib 74L of the three-dimensional deformation model 70, passes through the passing points 89A to 89L with the first feature point 43A to the twelfth feature point 43L as a starting point, and circumscribes the body region 77. To deform.

  Similarly, the CPU 11 deforms the left first rib to the left twelfth rib (not shown) of the three-dimensional deformation model 70. By performing such deformation, the CPU 11 generates a three-dimensional subject model 80, moves to the next step, and ends the process.

(4) Operation and Effect In the above configuration, when the three-dimensional human body model generation device 1 acquires the three-dimensional image data D1 captured by the CT device or the MRI device, a predetermined upper limit is set for the three-dimensional image data D1. By performing the binarization process using the threshold value and the lower limit threshold value, only the skeleton 31 having a lightness level of “1” is extracted to generate the three-dimensional skeleton model 30.

  The three-dimensional human body model generation device 1 performs pattern matching between the three-dimensional skeleton model 30 and a standard vertebral body-shaped vertebral body template, and a first vertebral body having a substantially cylindrical shape based on morphological features. 32A to 12th vertebral body 32L are identified. The three-dimensional human body model generation device 1 calculates morphological midpoints of the first vertebral body 32A to the twelfth vertebral body 32L, and extracts the midpoints as the first feature point 33A to the twelfth feature point 33L. To do.

  The three-dimensional human body model generation device 1 traces the skeleton 31 portion extending in the left-right direction starting from each of the first vertebral body 32A to the twelfth vertebral body 32L with respect to the three-dimensional skeleton model 30 to the right. The first rib 34A to the right twelfth rib 34L and the left first rib 35A to the left twelfth rib 35L are identified.

  The three-dimensional human body model generation device 1 includes the right first rib 34A to the right twelfth rib 34L, the left first rib 35A to the left twelfth rib 35L, the sternum 36, the horizontal plane passing through the first feature point 33A and the twelfth feature point. A body space 37 surrounded by a horizontal plane passing through 33L is extracted.

  Next, the three-dimensional human body model generation device 1 cuts the body space 37 of the three-dimensional identification model 38 in a horizontal plane including the first feature point 33A to the twelfth feature point 33L, thereby making the first divided space 37A to the first divided space 37A to the first space 37A. It is divided into 11 divided spaces 37K.

  The three-dimensional human body model generation device 1 also includes a body region corresponding to the body space 37 of the three-dimensional identification model 38 in the three-dimensional standard human body model 40 in which each organ having a standard position and size is modeled in three dimensions. 47 is divided into a first divided region 47A to an eleventh divided region 47K by rounding off on a horizontal plane including the first feature point 43A to the twelfth feature point 43L.

  The three-dimensional human body model generation device 1 matches the first divided area 47A to the eleventh divided area 47K in the three-dimensional standard human body model 40 with the first divided space 37A to the eleventh divided space 37K in the three-dimensional identification model 38, respectively. As described above, the three-dimensional standard human body model 40 is deformed, and as a result, the three-dimensional deformation model 70 is generated.

  Further, the three-dimensional human body model generation device 1 generates the three-dimensional deformation model 70 and passes through the passing points 89A to 89L with the first feature point 43A to the twelfth feature point 43L as the starting point so as to circumscribe the body region 77. The right first rib 74A to the right twelfth rib 74L are respectively deformed. Further, the three-dimensional human body model generation apparatus 1 generates the three-dimensional subject model 80 by similarly deforming the left first rib to the left twelfth rib (not shown).

  Therefore, the 3D human body model generation apparatus 1 corrects the extraction defect or the erroneous extraction after extracting the target organ based on the gray level of the 3D image data D1, or the morphological position from the skeleton. The 3D subject model 80 for each subject can be easily generated without forcing the user to perform complicated operations such as dividing the skeleton according to the relationship.

  Further, the 3D human body model generation device 1 deforms the shape of the body region 47 of the 3D standard human body model 40 in accordance with the shape of the body space 37 surrounded by the skeleton 31 extracted from the 3D image data D1. A three-dimensional subject model 80 that accurately reproduces the body shape of each subject can be generated.

  By using the three-dimensional subject model 80 that reproduces the body shape of each subject in this way, it is possible to cause a doctor to perform surgical training, for example, before surgery, using the subject model created by a VR simulator or stereolithography apparatus. Therefore, it is possible to contribute to improving the safety and quality of endoscopic surgery.

  Further, when the shape of the in-vivo region 47 of the three-dimensional standard human body model 40 is deformed, the three-dimensional human body model generation device 1 performs first cutting by cutting the horizontal plane including the first feature point 43A to the twelfth feature point 43L. The image is divided into the divided areas 47A to 47K, and the first divided area 47A to the eleventh divided area 47K are deformed.

  As a result, the three-dimensional human body model generation device 1 can deform the shape of the living tissue included in each of the first divided region 47A to the eleventh divided region 47K more precisely according to the body shape of the subject.

  Further, the three-dimensional human body model generation device 1 can read out model data generated in each step. Furthermore, it is possible to return to the step designated by the user and repeat the 3D human body model generation process as many times as necessary. For this reason, the three-dimensional human body model generation apparatus 1 can reduce erroneous identification and deformation.

  According to the above configuration, the three-dimensional human body model generation device 1 extracts the internal space 37 of the three-dimensional identification model 38 based on the three-dimensional image data D1 imaged by the CT device or the MRI device, and the standard body shape The internal region 47 of the three-dimensional standard human body model 40 in which the human body is modeled in three dimensions is deformed in accordance with the internal space 37, whereby each organ data contained in the internal region 47 (for example, organs such as the heart and lungs) Data) is also generated to generate a three-dimensional subject model 80. Thereby, the three-dimensional human body model generation device 1 can easily generate the three-dimensional subject model 80 for each subject without forcing the user to perform complicated work.

<2. Second Embodiment>
In the first embodiment, a space surrounded by the ribs extracted from the three-dimensional image data D1 is extracted as the body space 37, and the body region 47 of the three-dimensional standard human body model 40 is deformed according to the body space 37. Let

  On the other hand, in the second embodiment, a body surface is extracted from the three-dimensional image data D1, and a space surrounded by the body surface is extracted as a body space. Further, the body region of the three-dimensional standard human body model 40 is deformed according to the body space surrounded by the body surface. Note that the configuration of the three-dimensional human body model generation apparatus 1 is the same as that of the first embodiment, and thus the description thereof is omitted.

(1) Three-dimensional human body model generation process When the CPU 11 executes the three-dimensional human body model generation process, the skeleton / body surface extraction unit 121, as shown in FIG. It functions as a vertebral body identification unit 122, a body space extraction unit 123, and a human body model deformation unit 124.

(1-1) Skeletal / Body Surface Extraction Processing When the CPU 11 executes the three-dimensional human body model generation processing, the skeleton / body surface extraction unit 121 executes the skeleton / body surface extraction processing. This skeleton / body surface extraction process will be described in detail.

  When the skeleton / body surface extraction unit 121 executes the skeleton / body surface extraction process, the skeleton / body surface extraction unit 121 reads the three-dimensional image data D1 from the storage unit 15 and creates volume data based on the three-dimensional image data D1.

  Here, as shown in FIG. 22, in the horizontal cross-sectional image CG4 based on the three-dimensional image data D1, when the image is captured by the CT apparatus, the skeleton appears white, and the body surface and organs are intermediate colors between white and black (gray ), And external and internal cavities appear black. Similarly, when the image is taken by the MRI apparatus, the shading level varies depending on the skeleton and the organ.

  Therefore, the skeleton / body surface extraction unit 121 displays the skeleton imaged in the three-dimensional image data D1 as white (lightness level is “1”), and the outside and body cavities become black (lightness level is “0”). Then, ternarization processing is performed on the basis of a predetermined upper limit threshold and lower limit threshold so that the tissue portion excluding the extracorporeal body and the body cavity is gray (the light and shade level is “0.5”).

  From the ternary image obtained as a result of the ternarization process, the skeleton / body surface extraction unit 121 has a pixel whose gray level is “1” (white) and a gray level of “0.5” (gray). Are extracted, and voxels corresponding to these pixels are generated and arranged three-dimensionally, so that a three-dimensional skeleton / body surface model 130 including a skeleton 31 and a body surface 131 is obtained as shown in FIG. Is generated.

  The skeleton / body surface extraction unit 121 stores the data of the generated three-dimensional skeleton / body surface model 130 (hereinafter also referred to as three-dimensional skeleton / body surface model data) D111 (FIG. 21) in the storage unit 15. Then, the skeleton / body surface extraction process is terminated.

(1-2) Vertebral body identification process CPU11 will perform a vertebral body identification process by the vertebral body identification part 122 (FIG. 21), after complete | finishing a skeleton and body surface extraction process.

  As in the first embodiment, the vertebral body identification unit 122 receives the three-dimensional skeleton / body surface model data D111 stored in the storage unit 15 and the vertebral body template data D2 stored in the storage unit 15 in advance. read out.

  The vertebral body identification unit 122 pattern-matches the vertebral body template having a standard vertebral body shape based on the vertebral body template data D2 and the skeleton 31 of the three-dimensional skeleton / body surface model 130, and as a result, substantially circular A plurality of columnar vertebral bodies 32 are detected.

  The vertebral body identification unit 122 selects the first thoracic vertebral body (first vertebral body) 32A to the twelfth thoracic vertebral body (12th vertebral body) 32L based on the morphological characteristics from the detected plurality of vertebral bodies. Identify. The vertebral body identification unit 122 detects the feature points of the identified first vertebral body 32A to the twelfth vertebral body 32L as the first feature point 33A to the twelfth feature point 33L.

  The vertebral body identification unit 122 uses the positional information and anatomical names of the identified first vertebral body 32A to twelfth vertebral body 32L and the positional information of the first feature point 33A to twelfth feature point 33L as vertebral body information D112. It memorize | stores in the memory | storage part 15, and complete | finishes a vertebral body identification process.

(1-3) Internal Space Extraction Processing When the CPU 11 finishes the vertebral body identification processing, the internal space extraction unit 123 (FIG. 21) executes internal space extraction processing.

  The internal space extraction unit 123 reads the 3D skeleton / body surface model data D111 stored in the storage unit 15 and extracts the gray level in the 3D skeleton / body surface model 130 as “0.5” (gray). A space surrounded by the body surface 131 which is the outermost outline of the tissue portion is extracted as a body space 132 (FIG. 24).

  When extracting as the internal space 132, the internal space extraction unit 123 separates the portion corresponding to the arm in the body surface 131 based on the morphological shape, and the portion that does not have the body surface 131 due to the separation is used as the chest. The corresponding portion of the body surface 131 is extrapolated by curve interpolation. Then, the body space extraction unit 123 extracts the space surrounded by the body surface 131 corresponding to the chest as the body space 132.

  The internal space extraction unit 123 stores the positional information of the internal space 132 in the storage unit 15 as internal space information D113, and ends the internal space extraction process.

(1-4) Human Body Model Deformation Process When the CPU 11 finishes the body space extraction process, the human body model deformation unit 124 (FIG. 21) executes the human body model deformation process. This human body model deformation process will be described in detail.

  The human body model deforming unit 124 is generated by the three-dimensional skeleton / body surface model data D111 generated by the skeleton / body surface extracting unit 121, the vertebral body information D112 generated by the vertebral body identifying unit 122, and the body space extracting unit 123. The obtained body space information D113 is read from the storage unit 15.

  Here, the 3D skeleton / body surface model data D111 generated by the skeleton / body surface extraction unit 121, the vertebral body information D112 generated by the vertebral body identification unit 122, and the in-vivo space information generated by the in-vivo space extraction unit 123. D113 is also collectively referred to as three-dimensional identification model data D114.

  As shown in FIG. 24A, the human body model deforming unit 124 identifies the first vertebral body 32A to the twelfth vertebral body 32L with respect to the skeleton 31 based on the three-dimensional identification model data D114. A three-dimensional identification model 133 to which the body space 132 surrounded by the feature points 33A to 13L and the body surface 131 is added is generated.

  Then, the human body model deforming unit 124 cuts the internal space 132 of the three-dimensional identification model 133 along the horizontal planes including the first feature point 33A to the twelfth feature point 33L, respectively, so that the first divided space 132A to the eleventh division are obtained. The space is divided into 132K.

  On the other hand, the human body model deforming unit 124 reads data (three-dimensional standard human body model data) D103 of the three-dimensional standard human body model 140 from the storage unit 15.

  This three-dimensional standard human body model 140 also includes information on vertebral body feature points in the three-dimensional standard human body model 140 and position information of the body region 142 surrounded by the body surface 141, as shown in FIG. It is made like that.

  Therefore, the human body model deforming unit 124 can recognize the first feature point 43A to the twelfth feature point 43L and the in-vivo region 142 surrounded by the body surface 141 by reading the three-dimensional standard human body model data D103. Has been made.

  Here, the body region 142 is located at a position corresponding to the body space 132 in the three-dimensional identification model 133, and includes a living tissue (each organ data) such as an organ.

  The human body model deforming unit 124 cuts the in-vivo region 142 of the three-dimensional standard human body model 140 in a horizontal plane including the first feature point 43A to the twelfth feature point 43L, respectively, so that the first segment region 142A to the eleventh segment are divided. The area is divided into 142K.

  Similar to the first embodiment, the human body model deforming unit 124 moves the first divided area 142A to the eleventh divided area 142K to the first divided space 132A to the eleventh divided space 132K, respectively, in the up and down direction and the front and rear direction. And a three-dimensional subject model is generated by expanding and contracting in the left-right direction. Along with this, the body surface is also deformed in the same manner as the ribs.

  The human body model deforming unit 124 stores the generated three-dimensional subject model data (three-dimensional subject model data) D115 in the storage unit 15.

(2) Human Body Model Deformation Processing Procedure Next, the above-described three-dimensional human body model generation processing procedure will be described in detail using a flowchart.

  That is, as shown in FIG. 25, the CPU 11 proceeds from the start step of the routine RT2 to the subroutine SRT11. As shown in FIG. 26, the CPU 11 enters from the start step of the subroutine SRT11, moves to the next step SP41, reads out the three-dimensional image data D1 from the storage unit 15, and the density level of the skeleton of the three-dimensional image data D1 is “ Predetermined upper and lower thresholds are set such that the density levels of the extracorporeal and internal cavities are "0", and the density levels of the other tissue portions are "0.5", and the process proceeds to the next step SP42. Move.

  In step SP42, the CPU 11 performs ternary processing on the three-dimensional image data D1 using the upper limit threshold and the lower limit threshold, and proceeds to the next step SP43.

  In step SP43, the CPU 11 generates a three-dimensional skeleton / body surface model 130 from the ternary image obtained by performing the ternarization processing, ends the skeleton / body surface extraction processing, and executes the next subroutine SRT12 (FIG. Go to 25).

  In the subroutine SRT12, the CPU 11 performs vertebral body identification processing. Specifically, as shown in FIG. 27, the CPU 11 enters from the start step of the subroutine SRT12 and proceeds to the next step SP51, and the vertebral body template based on the three-dimensional skeleton / body surface model 130 and the vertebral body template data D2 Are subjected to pattern matching to detect a plurality of vertebral bodies having a substantially cylindrical shape, and the process proceeds to the next step SP52.

  In step SP52, the CPU 11 detects the midpoints of the plurality of vertebral bodies detected in step SP51 as feature points, and proceeds to the next step SP53.

  In step SP53, the CPU 11 identifies the first vertebral body 32A to the twelfth vertebral body 32L based on the morphological characteristics from the plurality of vertebral bodies detected in step SP52, and the first vertebral body 32A to the twelfth vertebral body. The 32L feature points are set as the first feature point 33A to the twelfth feature point 33L, respectively, and the vertebral body identification process is terminated, and the process proceeds to the next subroutine SRT13 (FIG. 25).

  In the subroutine SRT13, the CPU 11 performs a body space extraction process. Specifically, as shown in FIG. 28, the CPU 11 enters from the start step of the subroutine SRT13, moves to the next step SP61, and the gray level in the three-dimensional skeleton / body surface model 130 is “0.5” (gray). The space surrounded by the body surface 131 which is the outermost contour of the extracted tissue part is extracted as the body space 132, the body space extraction process is terminated, and the process proceeds to the next subroutine SRT14 (FIG. 25).

  In the subroutine SRT14, the CPU 11 performs a human body model deformation process. Specifically, as shown in FIG. 29, the CPU 11 enters from the start step of the subroutine SRT4, moves to the next step SP71, and moves the internal space 132 of the three-dimensional identification model 133 to the first feature point 33A to the twelfth feature. It divides | segments into the 1st division space 132A-the 11th division space 132K by carrying out a round slice in the horizontal surface each including the point 33L.

  Further, the CPU 11 cuts the in-vivo region 142 of the three-dimensional standard human body model 140 into a first divided region 142A to an eleventh divided region 142K by cutting the body region 142 into horizontal planes including the first feature point 43A to the twelfth feature point 43L. Divide and move to next step SP72.

  In steps SP72 to SP77, the CPU 11 matches the first divided area 142A to the eleventh divided area 142K with the first divided space 132A to the eleventh divided space 132K, respectively, similarly to steps SP32 to SP37 in the first embodiment. As described above, the three-dimensional subject model is generated by expanding and contracting in the vertical direction, the front-rear direction, and the left-right direction, and the process proceeds to the next step and ends.

(3) Operation and effect In the above configuration, when the three-dimensional human body model generation device 1 acquires the three-dimensional image data D1 including the chest imaged by the CT device or the MRI device, the three-dimensional image data D1 is obtained. A three-dimensional process is performed to generate a three-dimensional skeleton / body surface model 130.

  The three-dimensional human body model generation device 1 identifies the first vertebral body 32A to the twelfth vertebral body 32L from the three-dimensional skeleton / body surface model 130, and extracts the first feature point 33A to the twelfth feature point 33L. The three-dimensional human body model generation apparatus 1 extracts a space surrounded by the body surface 131 from the three-dimensional skeleton / body surface model 130 as the body space 132.

  Then, the three-dimensional human body model generation device 1 deforms the body region 142 of the three-dimensional standard human body model 140 so as to match the body space 132, whereby each organ data (for example, heart, lung, etc.) included in the body region 142 is transformed. A three-dimensional subject model in which the organ data, joint data, and skeleton data) are also deformed is generated.

  Therefore, the three-dimensional human body model generation apparatus 1 can easily generate a three-dimensional subject model in which the chest for each subject is accurately reproduced based on the three-dimensional image data D1.

<3. Third Embodiment>
In the first and second embodiments, the chest internal spaces 37 and 132 are extracted from the three-dimensional image data D1, and the chest internal regions 47 and 142 in the three-dimensional standard human models 40 and 140 are extracted from the internal space 32. And 132.

  In contrast, in the third embodiment, the abdominal body space is extracted from the three-dimensional image data D1, and the abdominal body region in the three-dimensional standard human body model is deformed in accordance with the body space. Note that the configuration of the three-dimensional human body model generation apparatus 1 is the same as that of the first embodiment, and thus the description thereof is omitted.

(1) Three-dimensional human body model generation process When the CPU 11 executes the three-dimensional human body model generation process, the skeleton / muscle extraction unit 221, vertebrae as shown in FIG. It functions as a body identification unit 222, a body space extraction unit 223, and a human body model deformation unit 224.

(1-1) Skeletal / Muscle Extraction Processing When the CPU 11 executes the three-dimensional human body model generation process, the skeleton / muscle extraction unit 221 executes the skeletal / muscle extraction processing. This skeletal / muscle extraction process will be described in detail.

  When imaged by the CT apparatus, the skeletal / muscle extracting unit 221 reads the three-dimensional image data D1 including the abdomen from the storage unit 15, and creates volume data based on the three-dimensional image data D1.

  Here, as shown in FIG. 22, in the horizontal cross-sectional image CG4 of the three-dimensional image data D1, the skeleton appears white, and the muscles, internal organs, etc. appear in an intermediate color (gray) between white and black. Appears black. The muscles and internal organs have different brightness levels. Similarly, when the image is taken by the MRI apparatus, the shading level varies depending on the skeleton and the organ.

  Therefore, the skeletal / muscle extracting unit 221 turns the skeleton of the three-dimensional image data D1 white (shading level is “1”), and the muscle (muscle) is gray (shading level is “0.5”). A ternarization process is performed on the basis of a predetermined first upper limit threshold, first lower limit threshold, second upper limit threshold, and second lower limit threshold so that the tissue portion excluding the color becomes black (the light and shade level is “0”).

  Incidentally, the density level of the skeleton in the three-dimensional image data D1 is between the first upper limit threshold value and the first lower limit threshold value, and the density level of the muscle is between the second upper limit threshold value and the second lower limit threshold value. The first upper limit threshold, the first lower limit threshold, the second upper limit threshold, and the first upper limit threshold are set such that the tissue portion to be excluded is between the first upper limit threshold, the first lower limit threshold and the second upper limit threshold, and less than the second lower limit threshold. A 2 lower limit threshold is set.

  The skeletal / muscle extracting unit 221 uses a ternary image obtained as a result of the ternarization processing, a pixel having a lightness level of “1” (white), and a lightness level of “0.5” (gray). Each pixel is extracted, and voxels corresponding to the pixels are generated and arranged three-dimensionally, thereby generating a three-dimensional skeleton / muscle model 230 including a skeleton 231 and a muscle 232 as shown in FIG. .

  The skeletal / muscle extracting unit 221 stores the generated three-dimensional skeletal / muscle model 230 data (hereinafter also referred to as three-dimensional skeletal / muscular model data) D211 (FIG. 30) in the storage unit 15, The muscle extraction process ends.

(1-2) Vertebral body identification process CPU11 will perform a vertebral body identification process by the vertebral body identification part 222 (FIG. 21), after complete | finishing a skeleton and a muscle extraction process.

  The vertebral body identification unit 222 reads out the 3D skeletal / muscle model data D211 stored in the storage unit 15 and the vertebral body template data D2 stored in the storage unit 15 in the same manner as in the first embodiment. .

  The vertebral body identifying unit 22 pattern-matches the vertebral body template having a standard vertebral body shape based on the vertebral body template data D2 and the skeleton 231 of the three-dimensional skeleton / muscle model 230, and as a result, has a substantially cylindrical shape. A plurality of vertebral bodies 32 are detected.

  Subsequently, the vertebral body identifying unit 222 identifies, for example, the vertebral body 32L of the twelfth thoracic vertebra 32L to the vertebral body 32Q of the fifth lumbar vertebra based on the morphological features from the plurality of detected vertebral bodies (FIG. 33). The first lumbar vertebra 32M to the fifth lumbar vertebra 32Q are also referred to as the thirteenth vertebra 32M to the seventeenth vertebra 32Q.

  The vertebral body identification unit 222 detects the midpoints of the identified twelfth vertebral body 32L to seventeenth vertebral body 32Q as the twelfth feature point 33L to the seventeenth feature point 33Q.

  The vertebral body identification unit 222 uses the identified position information and anatomical names of the twelfth vertebral body 32L to the seventeenth vertebral body 32Q and the positional information of the twelfth feature point 33L to the seventeenth feature point 33Q as vertebral body information D212. It memorize | stores in the memory | storage part 15, and complete | finishes a vertebral body identification process.

(1-3) Body Space Extraction Processing When the CPU 11 finishes the vertebral body identification processing, the body space extraction unit 223 (FIG. 30) executes body space extraction processing.

  The internal space extraction unit 223 reads the three-dimensional skeletal / muscle model data D211 stored in the storage unit 15, and the gray level in the three-dimensional skeletal / muscular model 230 is “0.5” (gray) as shown in FIG. ) Of the muscles 232 extracted as the outermost side are detected.

  Then, the body space extraction unit 223 detects an outer peripheral line 233 that surrounds the outside of the detected muscle 232 in the horizontal section of the three-dimensional skeletal / muscle model 230. The internal space extraction unit 223 detects the outer peripheral line 233 in a horizontal section at predetermined intervals in the three-dimensional skeleton / muscle model 230, and extracts a space surrounded by the plurality of outer peripheral lines 233 as the internal space 234 (FIG. 33). .

  The internal space extraction unit 223 stores the positional information of the internal space 234 surrounded by the outer peripheral line 233 in the storage unit 15 as internal space information D213, and ends the internal space extraction process.

(1-4) Human Body Model Deformation Process When the CPU 11 finishes the body space extraction process, the human body model deformation unit 224 (FIG. 30) executes the human body model deformation process. This human body model deformation process will be described in detail.

  The human body model deforming unit 224 is generated by the 3D skeletal / muscle model data D211 generated by the skeletal / muscle extracting unit 221, the vertebral body information D212 generated by the vertebral body identifying unit 222, and the body space extracting unit 223. The body space information D213 is read from the storage unit 15.

  Here, the three-dimensional skeletal / muscle model data D211 generated by the skeletal / muscle extracting unit 221, the vertebral body information D212 generated by the vertebral body identifying unit 222, and the in-vivo space information D213 generated by the in-vivo space extracting unit 223 are used. These are also referred to as three-dimensional identification model data D214.

  As shown in FIG. 33A, the human body model deforming unit 224 identifies the twelfth vertebral body 32L to the seventeenth vertebral body 32Q with respect to the skeleton 231 based on the three-dimensional identification model data D214. A three-dimensional identification model 235 to which the feature point 33L to the seventeenth feature point 33Q and the body space 234 are added is generated.

  Then, the human body model deforming unit 224 cuts the internal space 234 of the three-dimensional identification model 235 into a horizontal plane that includes the twelfth feature point 33L to the seventeenth feature point 33Q, thereby twelfth divided space 234L to sixteenth division. The space 234P is divided.

  On the other hand, the human body model deforming unit 224 reads data (three-dimensional standard human body model data) D203 of the three-dimensional standard human body model 240 from the storage unit 15.

  As shown in FIG. 33 (B), this three-dimensional standard human body model 240 also includes information on vertebral body feature points in the three-dimensional standard human body model 240 and positional information on the body region 244 surrounded by the outer circumference of the muscle. It is made to include.

  Therefore, the human body model deforming unit 224 can recognize the twelfth feature point 43L to the seventeenth feature point 43Q and the body region 244 surrounded by the outer peripheral line by reading the three-dimensional standard human body model data D203. ing.

  Here, the body region 244 is located at a position corresponding to the body space 234 in the three-dimensional identification model 235, and contains a living tissue (organ data) such as an organ.

  The human body model deforming unit 224 cuts the in-vivo region 244 of the three-dimensional standard human body model 240 into a horizontal plane including the twelfth feature point 43L to the seventeenth feature point 43Q, thereby twelfth divided region 244L to sixteenth division. The area is divided into 244P.

  Similar to the first embodiment, the human body model deforming unit 224 moves the twelfth divided region 244L to the sixteenth divided region 244P to the twelfth divided space 234L to the sixteenth divided space 234P in the vertical direction and the front-rear direction. And a three-dimensional subject model is generated by expanding and contracting in the left-right direction. Along with this, the muscles (muscles) are also deformed in the same manner as the ribs.

  The human body model deforming unit 224 stores the generated three-dimensional subject model data (three-dimensional subject model data) D215 in the storage unit 15.

(2) Human Body Model Deformation Processing Procedure Next, the above-described three-dimensional human body model generation processing procedure will be described in detail using a flowchart.

  That is, as shown in FIG. 34, the CPU 11 proceeds from the start step of the routine RT3 to the subroutine SRT21. As shown in FIG. 35, the CPU 11 enters from the start step of the subroutine SRT21, moves to the next step SP81, reads out the 3D image data D1 from the storage unit 15, and the skeleton density level in the 3D image data D1 is “ The first upper limit threshold, the first lower limit threshold, the second upper limit threshold, and the second lower limit threshold are set to “1”, the tone level of the muscle is “0.5”, and the tone levels of the other tissue portions are set to “0”. Is set and the process proceeds to the next step SP82.

  In step SP82, the CPU 11 performs ternary processing on the three-dimensional image data D1 using the first upper limit threshold, the first lower limit threshold, the second upper limit threshold, and the second lower limit threshold, and proceeds to the next step SP83.

  In step SP83, the CPU 11 generates a three-dimensional skeletal / muscle model 230 from the ternary image obtained by performing the ternary processing, ends the skeletal / muscle extraction processing, and executes the next subroutine SRT22 (FIG. 34). Move on.

  In the subroutine SRT22, the CPU 11 performs vertebral body identification processing. Specifically, as shown in FIG. 36, the CPU 11 enters from the start step of the subroutine SRT22, moves to the next step SP91, and the vertebral body based on the skeleton 231 of the three-dimensional skeleton / muscle model 230 and the vertebral body template data D2. By pattern matching with the template, a plurality of vertebral bodies having a substantially cylindrical shape are detected, and the process proceeds to the next step SP92.

  In step SP92, the CPU 11 detects the midpoints of the plurality of vertebral bodies detected in step SP91 as feature points, and proceeds to the next step SP93.

  In step SP93, the CPU 11 identifies the twelfth vertebral body 32L to the seventeenth vertebral body 32Q based on the morphological features from the plurality of vertebral bodies detected in step SP91, and the twelfth vertebral body 32L to the seventeenth vertebral body. The 32Q feature points are set as the twelfth feature point 33L to the seventeenth feature point 33Q, respectively, and the vertebral body identification process is terminated, and the process proceeds to the next subroutine SRT23 (FIG. 34).

  In the subroutine SRT23, the CPU 11 performs a body space extraction process. Specifically, as shown in FIG. 37, the CPU 11 enters from the start step of the subroutine SRT23 and moves to the next step SP101, where the outer periphery of the muscle 232 is shown in a horizontal section at predetermined intervals in the three-dimensional skeletal / muscle model 230. , And moves to the next step SP102.

  In step SP102, the CPU 11 extracts the space surrounded by the outer peripheries 233 detected at predetermined intervals as the body space 234, ends the body space extraction process, and proceeds to the next subroutine SRT24 (FIG. 34).

  In the subroutine SRT24, the CPU 11 performs a human body model deformation process. Specifically, as shown in FIG. 38, the CPU 11 enters from the start step of the subroutine SRT24, moves to the next step SP111, and changes the internal space 234 of the three-dimensional identification model 235 from the twelfth feature point 33L to the seventeenth feature. Dividing into a twelfth divided space 234L to a sixteenth divided space 234P by rounding off at horizontal planes including the respective points 33Q.

  Further, the CPU 11 cuts the body region 244 of the three-dimensional standard human body model 240 into a twelfth divided region 244L to a sixteenth divided region 244P by cutting the body region 244 into horizontal planes including the twelfth feature point 43L to the seventeenth feature point 43Q. Divide and move to next step SP112.

  In steps SP112 to SP117, the CPU 11 matches the twelfth divided area 244L to the sixteenth divided area 244P with the twelfth divided space 234L to the sixteenth divided space 234P, respectively, similarly to steps SP32 to SP37 in the first embodiment. As described above, the three-dimensional subject model is generated by expanding and contracting in the vertical direction, the front-rear direction, and the left-right direction, and the process proceeds to the next step and ends.

(3) Operation and Effect In the above configuration, when the three-dimensional human body model generation device 1 acquires the three-dimensional image data D1 of the abdomen captured by the CT device or the MRI device, the three-dimensional image data D1 is 3 A three-dimensional skeletal / muscle model 230 is generated by performing the value processing.

  The three-dimensional human body model generation device 1 identifies the twelfth vertebral body 32L to the seventeenth vertebral body 32Q from the three-dimensional skeletal / muscular model 230 and extracts the twelfth feature point 33L to the seventeenth feature point 33Q.

  Further, the three-dimensional human body model generation device 1 extracts a space surrounded by an outer peripheral line 233 that surrounds the outer periphery of the muscle 232 from the three-dimensional skeleton / muscle model 230 as the body space 234. Then, the three-dimensional human body model generation device 1 deforms the body region 244 of the three-dimensional standard human body model 240 so as to match the body space 234, whereby each organ data (for example, stomach, liver, etc.) included in the body region 244 is changed. A three-dimensional subject model in which the organ data, joint data, and skeleton data) are also deformed is generated.

  Therefore, the three-dimensional human body model generation device 1 can easily generate a three-dimensional subject model in which the abdomen for each subject is accurately reproduced based on the three-dimensional image data D1.

<4. Fourth Embodiment>
In the first and second embodiments, the chest internal spaces 37 and 132 are extracted from the three-dimensional image data D1, and the chest internal regions 47 and 142 in the three-dimensional standard human models 40 and 140 are extracted from the internal space 32. And 132.

  In the third embodiment, the abdominal body space 234 is extracted from the three-dimensional image data D1, and the abdominal body region 244 in the three-dimensional standard human body model 240 is deformed so as to match the body space 234.

  On the other hand, in the fourth embodiment, the body space of the lower abdomen around the pelvis is extracted from the three-dimensional image data D1, and the body region of the lower abdomen in the three-dimensional standard human body model is matched with the body space. Deform. Note that the configuration of the three-dimensional human body model generation apparatus 1 is the same as that of the first embodiment, and thus the description thereof is omitted.

(1) Three-dimensional human body model generation process When the CPU 11 executes the three-dimensional human body model generation process, the skeleton / muscle extraction unit 321, It functions as a body identifying unit 322, a body space extracting unit 323, and a human body model deforming unit 324.

(1-1) Skeletal / Muscle Extraction Processing When the CPU 11 executes the three-dimensional human body model generation process, the skeleton / muscle extraction unit 321 executes the skeletal / muscle extraction processing. This skeletal / muscle extraction process will be described in detail.

  When the skeletal / muscle extracting unit 321 executes the skeletal / muscle extracting process, the skeletal / muscle extracting unit 321 reads out the three-dimensional image data D1 including the lower abdomen from the storage unit 15, and creates volume data based on the three-dimensional image data D1.

  As in the third embodiment, the skeleton / muscle extraction unit 321 has a white skeleton in the three-dimensional image data D1 (lightness level is “1”) and a gray color (lightness level is “0.5”). Ternary with reference to a predetermined first upper limit threshold, first lower limit threshold, second upper limit threshold and second lower limit threshold so that the tissue portion excluding the skeleton and muscles is black (shading level is “0”) The process is applied.

  From the ternary image obtained as a result of the ternary processing, the skeletal / muscle extraction unit 321 has a pixel with a gray level of “1” (white) and a gray level of “0.5” (gray). Each pixel is extracted, and voxels corresponding to the pixels are generated and arranged three-dimensionally to generate a three-dimensional skeletal / muscle model 330 including a skeleton 331 and a muscle 332 as shown in FIG. .

  The skeletal / muscle extracting unit 321 then stores the generated data (three-dimensional skeletal / muscular model data) D311 of the three-dimensional skeletal / muscular model 330 in the storage unit 15, and ends the skeletal / muscle extracting process.

(1-2) Vertebral body identification process CPU11 will perform a vertebral body identification process by the vertebral body identification part 322 (FIG. 39), after complete | finishing a skeleton and a muscle extraction process.

  The vertebral body identification unit 322 reads out the 3D skeletal / muscle model data D311 stored in the storage unit 15 and the vertebral body template data D2 stored in advance in the storage unit 15 in substantially the same manner as in the first embodiment. .

  The vertebral body identification unit 322 pattern-matches a vertebral body template having a standard vertebral body shape based on the vertebral body template data D2 and the skeleton 331 of the three-dimensional skeleton / muscle model 330, and as a result, has a substantially cylindrical shape. A plurality of vertebral bodies are detected.

  Subsequently, the vertebral body identifying unit 322 identifies, for example, the vertebral body (17th vertebral body) 32Q of the fifth lumbar vertebra based on the morphological characteristics from the plurality of detected vertebral bodies. The vertebral body identification unit 322 detects the midpoint of the identified 17th vertebral body 32Q as the 17th feature point 33Q.

  The vertebral body identification unit 322 identifies the sacrum 333 by tracing the skeleton 331 portion existing below the seventeenth vertebral body 32Q. As shown in FIG. 41, the vertebral body identifying unit 332 detects the first sacral hole 333A to the fourth sacral hole 333D forming a pair of the identified sacrum 333, and the first sacral hole 333A to the fourth sacrum forming a pair, respectively. The sacrum 333 is divided into five by a horizontal section passing through the center of the hole 333D.

  The vertebral body identification unit 322 detects, for example, the midpoint of each of the divided sacrum 333 as the 18th feature point 33R to the 22nd feature point 33V.

  The vertebral body identifying unit 322 identifies the coccyx 334 by tracing the portion of the skeleton 331 existing below the sacrum 333. The vertebral body identifying unit 322 detects, for example, the midpoint of the identified tailbone 334 as the 23rd feature point 33W.

  The vertebral body identification unit 322 uses the identified 17th vertebral body 32Q, positional information and anatomical names of the sacrum 333 and coccyx 334, and positional information of the 17th feature point 33Q to the 23rd feature point 33W as vertebral body information D312. It memorize | stores in the memory | storage part 15, and complete | finishes a vertebral body identification process.

(1-3) Internal Space Extraction Processing When the CPU 11 finishes the vertebral body identification processing, the internal space extraction unit 323 (FIG. 39) executes internal space extraction processing.

  The internal space extraction unit 323 reads the three-dimensional skeletal / muscle model data D311 stored in the storage unit 15 and extracts the muscle 332 extracted as the gray level of “0.5” (gray) in the three-dimensional skeletal / muscular model 330. Among them, the most forward and left and right muscles are detected.

  The internal space extraction unit 323 detects a skeleton 331 portion extending from the sacrum 333 to the left and right in the skeleton 331 of the three-dimensional skeleton / muscle model 330 based on the vertebral body information D312. The body space extraction unit 323 identifies the iliac bone and the pubic bone as the pelvis 335 by tracing adjacent skeletons starting from the detected skeleton 331 near the sacrum 333.

  As shown in FIGS. 42A to 42C, the internal space extraction unit 323 is a horizontal section at predetermined intervals in the three-dimensional skeletal / muscle model 330 and passes through the inner boundary of the detected muscle 332 and pelvis 335. The circumference line 336 is detected, and the space surrounded by the inner circumference line 336 is extracted as the body space 337 (FIG. 43). Note that the horizontal sectional views of FIGS. 42A to 42C use CT images for convenience of explanation.

  The body space extraction unit 323 stores the identified position information and anatomical name of the pelvis 335 in the storage unit 15 as pelvic information D313, and also stores the position information of the body space 337 surrounded by the inner peripheral line 336. It memorize | stores in the memory | storage part 15 as D314, and complete | finishes a body space extraction process.

(1-4) Human Body Model Deformation Process When the CPU 11 finishes the body space extraction process, the human body model deformation unit 324 (FIG. 39) executes the human body model deformation process. This human body model deformation process will be described in detail.

  The human body model deforming unit 324 is generated by the three-dimensional skeletal / muscle model data D311 generated by the skeletal / muscle extracting unit 321, the vertebral body information D312 generated by the vertebral body identifying unit 322, and the body space extracting unit 323. Pelvic information D313 and internal space information D314 are read from the storage unit 15.

  Here, the three-dimensional skeletal / muscle model data D311 generated by the skeletal / muscle extracting unit 321, the vertebral body information D312 generated by the vertebral body identifying unit 322, the pelvis information D313 generated by the body space extracting unit 323, and the internal body The spatial information D314 is also collectively referred to as three-dimensional identification model data D315.

  As shown in FIG. 43A, the human body model deforming unit 324 identifies the seventeenth vertebral body 32Q, the sacrum 333, the tailbone 334, and the pelvis 335 with respect to the skeleton 331 based on the three-dimensional identification model data D315. A three-dimensional identification model 338 to which the seventeenth feature point 33Q to the twenty-third feature point 33W and the body space 337 are added is generated.

  Then, the human body model deforming unit 324 cuts the internal space 337 of the three-dimensional identification model 338 into horizontal planes including the 17th feature point 33A to the 23rd feature point 33Q, respectively, so that the 17th divided space 337Q to the 22nd division are obtained. The space is divided into 337V.

  On the other hand, the human body model deforming unit 324 reads data of the 3D standard human body model 340 (also referred to as 3D standard human body model data) D303 from the storage unit 15.

  As shown in FIG. 43 (B), the three-dimensional standard human model 340 includes information on the vertebral body, sacrum, and tailbone feature points 43Q to 43W in the three-dimensional standard human model 340, and the inner circumference of the muscle and pelvis. The position information of the enclosed body region 347 is also included.

  Therefore, the human body model deforming unit 324 recognizes the seventeenth feature point 43Q to the twenty-third feature point 43W and the body region 347 surrounded by the inner circumference of the muscle and pelvis by reading the three-dimensional standard human model data D303. It is made to be able to do.

  Here, the in-vivo region 347 is located at a position corresponding to the in-vivo space 337 in the three-dimensional identification model 338, and includes a living tissue (each organ data) such as an organ.

  The human body model deforming unit 324 then cuts the in-vivo region 347 of the three-dimensional standard human body model 340 into horizontal planes including the 17th feature point 43Q to the 23rd feature point 43W, respectively, so that the 17th divided regions 347Q to 22nd. The area is divided into divided areas 347V.

  Similar to the first embodiment, the human body model deforming unit 324 moves the 17th divided area 347Q to the 22nd divided area 347V to the 17th divided space 337Q to the 22nd divided space 337V, respectively, in the up and down direction and the front and rear direction. And a three-dimensional subject model is generated by expanding and contracting in the left-right direction. Along with this, muscles, iliac bones, and pubic bones are also deformed in the same manner as the ribs.

  The human body model deforming unit 324 stores the generated three-dimensional subject model data (three-dimensional subject model data) D316 in the storage unit 15.

(2) Human Body Model Deformation Processing Procedure Next, the above-described three-dimensional human body model generation processing procedure will be described in detail using a flowchart.

  That is, as shown in FIG. 44, the CPU 11 proceeds from the start step of the routine RT4 to the subroutine SRT31. As shown in FIG. 45, the CPU 11 enters from the start step of the subroutine SRT31, moves to the next step SP121, reads out the three-dimensional image data D1 from the storage unit 15, and the density level of the skeleton of the three-dimensional image data D1 is “ The first upper limit threshold, the first lower limit threshold, the second upper limit threshold, and the second lower limit threshold are set to “1”, the tone level of the muscle is “0.5”, and the tone levels of the other tissue portions are set to “0”. Is set and the process proceeds to the next step SP122.

  In step SP122, the CPU 11 performs ternary processing on the three-dimensional image data D1 using the first upper limit threshold, the first lower limit threshold, the second upper limit threshold, and the second lower limit threshold, and proceeds to the next step SP123.

  In step SP123, the CPU 11 generates a three-dimensional skeletal / muscle model 330 from the ternary image obtained by performing the ternarization process, ends the skeleton extraction process, and proceeds to the next subroutine SRT32 (FIG. 44). .

  In the subroutine SRT32, the CPU 11 performs vertebral body identification processing. Specifically, as shown in FIG. 46, the CPU 11 enters from the start step of the subroutine SRT32, moves to the next step SP131, and obtains a vertebral body template based on the three-dimensional skeletal / muscle model 330 and the vertebral body template data D2. By performing pattern matching, a plurality of vertebral bodies having a substantially cylindrical shape are detected, and the process proceeds to the next step SP132.

  In step SP132, the CPU 11 detects the midpoints of the plurality of vertebral bodies detected in step SP131 as feature points, and proceeds to the next step SP133.

  In step SP133, the CPU 11 identifies the seventeenth vertebral body 32Q based on the morphological features of the plurality of vertebral bodies detected in step SP131, and sets the feature point of the seventeenth vertebral body 32Q as the seventeenth feature point 33Q. Control goes to the next step SP134.

  In step SP134, the CPU 11 identifies the sacrum 333 and the coccyx 334 existing below the seventeenth vertebral body 32Q, and proceeds to the next step SP135.

  In step SP135, the CPU 11 detects the 18th feature point 33R to the 22nd feature point 33V of the sacrum 333. Further, the CPU 11 detects the 23rd feature point 33W of the coccyx 334, ends the vertebral body identification process, and proceeds to the next subroutine SRT33 (FIG. 44).

  In the subroutine SRT33, the CPU 11 performs a body space extraction process. Specifically, as shown in FIG. 47, the CPU 11 enters from the start step of the subroutine SRT33, moves to the next step SP141, and is the most forward and leftmost among the muscles 332 in the three-dimensional skeletal / muscle model 330. The streak is detected, and the process proceeds to the next step SP142.

  In step SP142, based on the vertebral body information D312, the CPU 11 detects a skeleton 331 portion extending from the sacrum 333 to the left and right in the skeleton 331 of the three-dimensional skeleton / muscle model 330, and proceeds to the next step SP143.

  In step SP143, the CPU 11 traces adjacent skeletons starting from the detected skeleton 331 near the sacrum 333, thereby identifying the iliac bone and pubic bone as the pelvis 335, and proceeds to the next step SP144.

  In step SP144, the CPU 11 detects an inner peripheral line 336 passing through the inner boundary of the detected muscle 332 and pelvis 335 in a horizontal section at predetermined intervals in the three-dimensional skeletal / muscular model 330, and is surrounded by the inner peripheral line 336. The internal space is extracted as the internal space 337, the internal space extraction process is terminated, and the process proceeds to the next subroutine SRT34 (FIG. 44).

  In the subroutine SRT34, the CPU 11 performs a human body model deformation process. Specifically, as shown in FIG. 48, the CPU 11 enters from the start step of the subroutine SRT34, moves to the next step SP151, and moves the internal space 337 of the three-dimensional identification model 338 into the 17th feature point 33Q to the 23rd feature. It divides | segments into the 17th division space 337Q-22nd division space 337V by carrying out a ring cut in the horizontal surface each including the point 33W.

  In addition, the CPU 11 cuts the body region 347 of the three-dimensional standard human body model 340 into a seventeenth divided region 347Q to a twenty-second divided region 347V by cutting the body region 347 into horizontal planes including the seventeenth feature point 43Q to the twenty-third feature point 43W. Divide and move to next step SP152.

  In steps SP152 to SP157, the CPU 11 matches the seventeenth divided region 347Q to the twenty-second divided region 347V with the seventeenth divided space 337Q to the twenty-second divided space 337V, respectively, similarly to steps SP32 to SP37 in the first embodiment. As described above, the three-dimensional subject model is generated by expanding and contracting in the vertical direction, the front-rear direction, and the left-right direction, and the process proceeds to the next step and ends.

(3) Operation and effect In the above configuration, when the three-dimensional human body model generation device 1 acquires the three-dimensional image data D1 of the lower abdomen imaged by the CT device or the MRI device, the three-dimensional image data D1 is obtained. A three-dimensional process is performed to generate a three-dimensional skeletal / muscle model 330.

  The three-dimensional human body model generation device 1 identifies the seventeenth vertebral body 32Q, the sacrum 333, the tailbone 334, and the pelvis 335 from the three-dimensional skeletal / muscle model 330, and extracts the seventeenth feature point 33Q to the twenty-third feature point 33W. .

  In addition, the three-dimensional human body model generation device 1 extracts a space surrounded by the muscle 332 and the pelvis 335 from the three-dimensional skeletal / muscle model 330 as the body space 337. Then, the three-dimensional human body model generation device 1 deforms the body region 347 of the three-dimensional standard human body model 340 so as to match the body space 337, whereby each organ data included in the body region 347 (for example, large intestine, bladder, etc.) A three-dimensional subject model with deformed organ data was also generated.

  Therefore, the three-dimensional human body model generation device 1 can easily generate a three-dimensional subject model in which the lower abdomen of each subject is accurately reproduced based on the three-dimensional image data D1.

<5. Other embodiments>
In the first and second embodiments, the internal space of the chest is extracted, the internal space of the abdomen is extracted in the third embodiment, and the internal space of the lower abdomen in the fourth embodiment. As described above, the case where the body region of the three-dimensional standard model corresponding to the body space is deformed to match the body space has been described. The present invention is not limited to this, and the internal space is extracted from any region of the chest, abdomen, and lower abdomen, and the internal region of the three-dimensional standard model corresponding to the internal space is matched with the internal space. You may make it deform | transform.

  As an example, when targeting the chest and abdomen, for example, the first vertebral body 32A to the 17th vertebral body 32Q are identified from the three-dimensional image data D1, and the chest as described in the first or second embodiment. As described in the third embodiment, the abdominal body space is extracted, and these body spaces are combined into one body space, and the corresponding body region is defined as the body space. Transform to match.

  As another example, for example, from the fifth vertebra 32E to the fifteenth vertebra 32O in the middle of the chest is identified, and as described in the first or second embodiment, the body space of the chest In addition, as described in the third embodiment, the abdominal body space is extracted, and these body spaces are combined into one body space, and the corresponding body region is matched with the body space. Deform.

  Furthermore, in the above-described embodiment, the space surrounded by the body surface may be extracted as the body space as in the second embodiment for the abdomen and the lower abdomen.

  In the above-described second to fourth embodiments, the case where the body space extraction process is performed after the vertebral body identification process has been described has been described, but the present invention is not limited thereto, and the body space extraction is performed. After executing the processing, the vertebral body identification processing may be executed.

  Further, in the third embodiment described above, the case where the space surrounded by the outer peripheral line 233 surrounding the outer periphery of the muscle 232 is extracted as the body space is described, but the present invention is not limited to this, for example, A rib may be detected from the skeleton 231, and a space surrounded by an outer peripheral line surrounding the outer periphery of the rib and the muscle 232 may be extracted as a body space. Alternatively, the costal cartilage may be extracted from the three-dimensional image data D1, and a space surrounded by an outer peripheral line surrounding the outer circumferences of the costal cartilage, the ribs, and the muscle 232 may be extracted as the body space.

  Hereinafter, although other embodiments with respect to the first embodiment will be mainly described, the same applies to the second to fourth embodiments.

  Furthermore, in the above-described embodiment, the case where the binarization process is performed on the three-dimensional image data D1 using the predetermined upper limit threshold and the lower limit threshold has been described, but the present invention is not limited thereto, For example, the user may be allowed to set arbitrary upper and lower thresholds with reference to the horizontal cross-sectional image CG1, the sagittal cross-sectional image CG2, and the forehead cross-sectional image CG3.

  Further, in the above-described embodiment, the case where the front, back, top, bottom, and left and right directions of the three-dimensional skeleton model 30 are set from the imaging conditions included in the three-dimensional image data D1 has been described. Instead, the model position may be finely adjusted by the user rotating the three-dimensional skeleton model 30 or the three-dimensional identification model 38 after setting the front, back, top, bottom, left and right directions around the coordinate axis.

  Furthermore, in the above-described embodiment, the three-dimensional skeleton model 30, the three-dimensional identification model 38, the three-dimensional standard human body model 40, the three-dimensional deformation models 50, 60, 70, and the three-dimensional subject model 80 include a plurality of voxels. Although the case where it is configured by arranging three-dimensionally has been described, the present invention is not limited to this, and may be configured by, for example, wire frame data or surface data.

  For example, when wire frame data is used, it can be realized by configuring vertebral bodies, ribs, joints, organs, and the like with different wire frames.

  Furthermore, in the above-described embodiment, the case where the voxel having a size corresponding to each pixel of the tomographic image is generated has been described. However, the present invention is not limited to this, and a voxel size smaller than the pixel size may be used. However, a larger voxel size may be used.

  Further, in the above-described embodiment, the first vertebral body 32A to the twelfth vertebral body 32L are used as the first feature point 33A to the twelfth vertebral body 33L as the first feature point 33A to the twelfth feature point 33L. However, the present invention is not limited to this. For example, the geometric center of gravity of the first vertebral body 32A to the twelfth vertebral body 32L is used as the first vertebral body 32A to the twelfth vertebra. The first feature point 33A to the twelfth feature point 33L of the body 32L may be used.

  Further, in the above-described embodiment, after performing, for example, the deformation of expanding and contracting the fifth divided region 57E of the three-dimensional deformation model 50 in the front-rear direction, the deformation of expanding and contracting the fifth divided region 67E obtained as a result thereof is performed. Although the case where it performed is described, this invention is not restricted to this, You may make it expand and contract in the front-back direction after expanding and contracting the 5th division area 57E in the left-right direction.

  Further, in the above-described embodiment, the three-dimensional deformation model 50 is deformed to expand and contract in the front-rear direction, and the resulting three-dimensional deformation model 60 is deformed to expand and contract in the left-right direction. Although the case where the right first rib 74A to the right twelfth rib 74L and the left first rib to the left twelfth rib are deformed has been described, the present invention is not limited to this, and the three-dimensional deformation model 50 (see FIG. After deforming the rib (10 (B)), the body region surrounded by the rib may be expanded and contracted in the left-right direction and the front-rear direction.

  In the above-described embodiment, the sagittal section passing through the third feature points 33C and 43C has been described as the reference planes SS1 and SS2. However, the present invention is not limited to this, and preferably the third feature point. A sagittal section passing through any one of the feature points 33C to 33G is defined as a reference plane SS1, and a sagittal section passing through any one of the third feature points 43C to the seventh feature point 43G is defined as a reference plane SS2. It may be.

  Furthermore, in the above-described embodiment, the case where the forehead cross section that equally divides the upper surfaces of the third divided space 37C and the third divided region 47C in the front-rear direction is set as the reference planes SS3 and SS4 has been described. The present invention is not limited to this. Preferably, the forehead cross section that equally divides any of the upper surfaces of the third divided space 37C to the seventh divided space 37G in the front-rear direction is defined as the reference plane SS3, and the third divided regions 47C to 47C Any one of the upper surfaces of the seventh divided region 47G may be used as a reference surface SS4 that is equally divided in the front-rear direction.

  Further, in the above-described embodiment, for example, the sagittal cross sections 37Ea, 47Ea, 57Ea and the forehead cross sections 37Eb, 67Eb are approximated to a trapezoidal shape. You may make it approximate.

  Further, in the above-described embodiment, pixels whose gradation level is “1” (white) in the binarized image BWG obtained by performing binarization processing on the three-dimensional image data D1 are extracted. The case where the three-dimensional skeleton model 30 is generated has been described. However, the present invention is not limited to this, and pixels having a gray level of “1” (white) in the binarized image BWG are extracted, and smoothing is performed on the skeleton 31 in which voxels corresponding to the pixels are three-dimensionally arranged. Processing may be performed to generate the three-dimensional skeleton model 30. By doing in this way, the unevenness | corrugation which generate | occur | produces on the surface of the frame | skeleton 31 extracted from the binarized image BWG is removable.

  Further, in the above-described embodiment, the ratio (L1a / L1b) and the ratio (L1a / L1b) from the upper base to the lower base, for example, the front side portion of the fifth divided region 57E (FIGS. 11B and 11C) from the reference plane SS2 are used. L3a / L3b) is linearly interpolated using the ratio obtained by linear interpolation, and the ratio (L2a / L2b) and ratio (L4a / L4b) are linear from the upper base to the lower base on the rear side of the reference plane SS2. The case where the fifth divided region 57E is deformed so as to expand and contract backward from the reference surface SS2 using the interpolated ratio has been described. However, the present invention is not limited to this, and the human body model deforming unit 24 may perform the fifth division so that the hypotenuse of the sagittal cross section 57Ea of the fifth subdivision 57E matches the hypotenuse of the sagittal cross section 37Ea of the fifth subdivision 37E. The method is not limited as long as the region 57E is deformed to expand and contract in the front-rear direction.

  Further, in the above-described embodiment, for example, the left side portion from the reference plane SS4 of the fifth divided region 67E (FIGS. 13B and 13C) is set to the ratio (W1a / W1b) and the ratio ( W3a / W3b) is stretched leftward using a ratio obtained by linear interpolation, and the ratio (W2a / W2b) and ratio (W4a / W4b) are linearly interpolated from the upper base to the lower base on the right side of the reference surface SS4. The case where the fifth divided region 67E is deformed so as to expand and contract in the right direction from the reference plane SS4 using the ratio described above has been described. However, the present invention is not limited to this, and the human body model deforming unit 24 may perform the fifth division so that the hypotenuse of the forehead cross-section 67Eb of the fifth subdivision 67E matches the hypotenuse of the forehead cross-section 37Eb of the fifth subdivision 37E. If the deformation | transformation which expands / contracts the area | region 67E to the left-right direction is performed, the method will not be ask | required.

  Further, in the above-described embodiment, a procedure in which the same value is always returned from the three-dimensional standard human body model data D3 by a constant process even if the three-dimensional image data D1 is different, for example, the arrow of the fifth divided region 57E. The case where the procedure for calculating the lengths L1b and L2b of the upper base in the front-rear direction and the lengths L3b and L4b of the lower base with respect to the reference plane SS2 from the cross section 57Ea is described each time, but the present invention describes Not limited to this, these values calculated in advance may be included in the three-dimensional standard human body model data D3 and stored in the storage unit 15.

  Further, in the above-described embodiment, when the right twelfth rib 74L of the three-dimensional deformation model 70 is deformed so as to circumscribe the in-vivo region 77 starting from the twelfth feature point 43L, the three-dimensional identification is performed. The intersection line 39L is calculated by extrapolating the center line of the right twelfth rib 34L of the model 38 to the reference plane SS1, and the center line of the right twelfth rib 74L of the three-dimensional deformation model 70 is extrapolated to the reference plane SS2 to pass through. 79L is calculated, and the passing point 79L is moved to the same height position as the intersection point 39L to generate a passing point 89L, which is the same deformation as the right first rib 74A to the right eleventh rib 74K of the three-dimensional deformation model 70. The case where it was supposed to be described. However, the present invention is not limited to this, and the eleventh feature point 43K and the eleventh feature point 43K are defined based on the right eleventh rib 74K of the three-dimensional deformation model 70 obtained by deforming the right first rib 74A to the right eleventh rib 74K in the above-described implementation. The right twelfth rib 74L may be deformed so as to maintain the vertical distance of the twelve feature points 43L, or the right twelfth rib 74L may be deformed by the same distance in the direction in which the right eleventh rib 74K is deformed. good.

  Further, in the embodiment described above, after generating the three-dimensional subject model 80, the user confirms the model data generated in each step and the user designates the step of starting the redo of the three-dimensional human body model generation process. Although the case where it performed is described, this invention is not restricted to this, You may enable it to perform confirmation of model data etc. and designation | designated of a redo step between arbitrary steps.

  Further, in the above-described embodiment, when the three-dimensional human body model generation process is executed, it functions as the skeleton extraction unit 21, the vertebral body identification unit 22, the rib identification unit 23, and the human body model generation unit 24 as a software configuration. However, the present invention is not limited to this, and a three-dimensional human body model generation process is executed by the skeleton extraction unit 21, the vertebral body identification unit 22, the rib identification unit 23, and the human body model generation unit 24 having a hardware configuration. You may make it do.

  Further, in the above-described embodiment, the case where the CPU 11 performs the above-described three-dimensional human body model generation processing according to the three-dimensional human body model generation processing program stored in the ROM 12 or the storage unit 15 has been described. The invention is not limited to this, and the above-described 3D human body model generation processing is performed according to a 3D human body model generation processing program installed from a storage medium or downloaded from the Internet, or another 3D human body model generation processing program installed by various routes. You may make it do.

  The three-dimensional human body model generation device 1 of the present invention can be applied to the medical field, for example.

  DESCRIPTION OF SYMBOLS 1 ... Three-dimensional human body model production | generation apparatus, 11 ... CPU, 12 ... ROM, 13 ... RAM, 14 ... Interface part, 15 ... Memory | storage part, 16 ... Display part, 17 ... Bus, 21 ... ... skeletal extraction unit, 22, 122, 222, 322 ... vertebral body identification unit, 23 ... rib identification unit, 24, 124, 224, 324 ... human body model deformation unit, 30 ... 3D skeletal model, 31, 41, 51, 61, 71, 81, 131, 231, 331 ... Skeleton, 32 ... Vertebral body, 33 ... Feature point, 34A-34L, 44A-44L, 74A-74L, 84A-84L ... Right 1 rib-right twelfth rib, 35A-35L ... left first rib-left twelfth rib, 36 ... sternum, 37, 132, 234, 337 ... internal space, 37A-37K ... first divided space- 11th divided space, 37Ea, 47 a, 57Ea, 67Ea ...... Sagittal cross-section, 37Eb, 67Eb, 77Eb ... Forehead cross-section, 38, 133, 235, 338 ... 3-D identification model, 40, 140, 240, 340 ... 3-D standard human body model 47, 57, 67, 77, 142, 244, 347 ... Body region, 47A-47K, 57A-57K, 67A-67K, 77A-77K ... First division region to eleventh division region, 50, 60, 70 …… 3D deformation model, 80 …… 3D subject model, 121 …… Body / body surface extraction unit, 123, 223, 323 …… Body space extraction unit, 130 …… 3D skeleton / body surface model , 131... Body surface, 221, 321... Skeleton / muscle extraction unit, 230, 330... Three-dimensional skeletal / muscle model, 232, 332. Bone .

Claims (16)

A three-dimensional standard human body model comprising body region data including body space data and organ data associated with the body space data;
An internal space extraction unit that extracts internal space from three-dimensional image data representing a tomographic image of the human body;
A three-dimensional human body model generation device, comprising: a human body model deformation unit that deforms the internal body region data so as to conform to the internal space extracted by the internal space extraction unit. The three-dimensional human body model generation device according to claim 1, wherein the body space extraction unit extracts a space surrounded by a skeleton and / or muscle as a body space. The three-dimensional human body model generation device according to claim 1, wherein the body space extraction unit extracts a space surrounded by a body surface as a body space. A feature point extracting unit that extracts a feature point in the vertical direction from the three-dimensional image data as a feature point;
The human body model deforming part is
The body space is divided into a plurality of divided spaces by a horizontal plane including the feature points extracted by the feature point extraction unit, and the body regions are divided by the horizontal plane including the feature points in the three-dimensional standard human body model. The three-dimensional human body model generation device according to any one of claims 1 to 3, wherein a region is deformed in accordance with the plurality of corresponding divided spaces. A body space extraction step for extracting the body space from the three-dimensional image data showing the tomographic image of the human body;
The internal region data of a three-dimensional standard human body model including internal region data including internal space data and organ data associated with the internal space data is modified to match the internal space extracted by the internal space extraction step. A three-dimensional human body model generation method comprising: a human body model transformation step. A body space extraction step for extracting the body space from the three-dimensional image data showing the tomographic image of the human body;
The internal region data of a three-dimensional standard human body model including internal region data including internal space data and organ data associated with the internal space data is modified to match the internal space extracted by the internal space extraction step. A three-dimensional human body model generation program comprising: a human body model transformation step. A three-dimensional standard human body model comprising body region data including body space data and organ data associated with the body space data;
A skeleton extraction unit that extracts a skeleton from three-dimensional image data representing a tomographic image of the human body;
A rib identifying unit that identifies a plurality of ribs from the skeleton extracted by the skeleton extracting unit, and extracts a body space surrounded by the plurality of ribs;
A three-dimensional human body model generation device comprising: a human body model deformation unit that deforms the body region data so as to conform to the body space extracted by the rib identification unit. A vertebral body identifying unit that identifies a plurality of vertebral bodies from the skeleton extracted by the skeleton extracting unit and extracts feature points of the plurality of vertebral bodies;
The human body model deforming part is
The body space is divided into a plurality of divided spaces by a horizontal plane including the feature points extracted by the vertebral body identification unit, and the body regions are divided by a horizontal plane including the feature points in the three-dimensional standard human body model. The three-dimensional human body model generation device according to claim 7, wherein the region is deformed according to a corresponding divided space. The human body model deforming part is
9. The divided regions are vertically expanded and contracted so that the heights of the plurality of divided regions in the three-dimensional standard human body model respectively coincide with the heights of the corresponding divided spaces. 3D human body model generator. The human body model deforming part is
Expanding and contracting the plurality of divided regions in the front-rear direction so that the sagittal sections of the plurality of divided regions with respect to a predetermined reference position coincide with the sagittal cross-sections of the plurality of corresponding divided spaces, respectively. The three-dimensional human body model generation apparatus according to claim 8, wherein the apparatus is a three-dimensional human body model generation apparatus. The human body model deforming part is
Expanding and contracting the plurality of divided regions in the left-right direction so that the forehead cross sections of the plurality of divided regions with respect to a predetermined reference position coincide with the forehead cross sections of the plurality of corresponding divided spaces, respectively. The three-dimensional human body model generation apparatus according to claim 8, wherein the apparatus is a three-dimensional human body model generation apparatus. The human body model deforming part is
The intersection of the forehead cross section that divides the internal space with respect to a predetermined reference position in the front-rear direction and a plurality of ribs identified by the rib identification unit is calculated, and a plurality of the three-dimensional standard human body models are calculated. The three-dimensional human body according to any one of claims 8 to 11, wherein the rib is deformed so as to circumscribe the in-vivo region that has been deformed so as to pass through a position corresponding to the intersection and to match the internal space. Model generator. The three-dimensional standard human body model according to any one of claims 8 to 12, wherein the three-dimensional standard human body model includes realization information, and the realization information is inherited even after being deformed by the human body model deformation means. Human body model generation device. The three-dimensional human body model generation device according to claim 8, wherein the feature point of the vertebral body is a geometric center of gravity or a morphological midpoint of the vertebral body. A skeleton extraction step of extracting a skeleton from three-dimensional image data representing a tomographic image of the human body;
Identifying a plurality of ribs from the skeleton extracted by the skeleton extracting step, and extracting a body space surrounded by the plurality of ribs;
The internal region data of the three-dimensional standard human body model including internal region data including internal space data and each organ data associated with the internal space data is transformed to match the internal space extracted by the rib identification unit. A three-dimensional human body model generation method comprising: a human body model transformation step. A skeleton extraction step of extracting a skeleton from three-dimensional image data representing a tomographic image of the human body;
Identifying a plurality of ribs from the skeleton extracted by the skeleton extracting step, and extracting a body space surrounded by the plurality of ribs;
The body region data of a three-dimensional standard human body model including body region data including body space data and each organ data associated with the body space data is transformed to match the body space extracted by the rib identification unit. A three-dimensional human body model generation program for causing a computer to execute a human body model transformation step.