JP5693388B2 - Image collation device, patient positioning device, and image collation method - Google Patents

Description

  The present invention uses an image collation apparatus using CT image data and the like in a radiotherapy apparatus that performs cancer treatment by irradiating an affected area of a patient with radiation such as X-rays, gamma rays, and particle beams. The present invention relates to a patient positioning apparatus that positions a patient at a radiation irradiation position for irradiating radiation.

  In recent years, development and construction of cancer treatment devices (particularly called particle beam treatment devices) using particle beams such as protons and heavy ions have been promoted in radiation treatment devices for cancer treatment. As is well known, particle beam therapy using particle beams can irradiate the cancer affected area more intensively than conventional radiotherapy such as X-rays and gamma rays, that is, pinpointing according to the shape of the affected area. Can be irradiated with a particle beam and can be treated without affecting normal cells.

  In particle beam therapy, it is important to irradiate an affected area such as cancer with high accuracy. Therefore, the patient is fixed using a fixture or the like so that the position does not shift with respect to the treatment table in the treatment room (irradiation room) during the particle beam treatment. In order to accurately position the affected area such as cancer within the radiation irradiation range, settings such as rough installation of the patient using a laser pointer are performed, and then the patient's affected area is accurately positioned using an X-ray image or the like. Is going.

  In Patent Document 1, two-step pattern matching is performed without designating the same position of the same monument in any of the reference image of the X-ray fluoroscopic image and the current image captured by the X-ray receiver. A bed positioning device that generates positioning information for driving a treatment table and a positioning method therefor have been proposed. In the primary pattern matching, a second setting area having the same size as the first setting area including the isocenter (beam irradiation center) set for the two-dimensional reference image is set for the two-dimensional current image. The second setting area is sequentially moved within the area of the two-dimensional current image, and the two-dimensional reference image in the first setting area and the two-dimensional current image in the second setting area are moved at the respective positions of the second setting area. And the second setting area having the two-dimensional current image most similar to the two-dimensional reference image in the first setting area is extracted. In the secondary pattern matching, the two-dimensional current image in the second setting area extracted by the primary pattern matching is compared with the two-dimensional reference image in the first setting area, and the pattern matching is performed so that the two images most closely match. Had gone.

Japanese Patent No. 3748433 (0007-0009 stage, 0049 stage, FIG. 8, FIG. 9)

Since the shape of the affected part is a three-dimensional solid shape, using a three-dimensional image to position the affected part at the position of the affected part at the time of treatment planning enables positioning with higher accuracy than using a two-dimensional image. Generally, when creating treatment plan data, an affected part shape is specified three-dimensionally using an X-ray CT (Computed Tomography) image. In recent years, a treatment room has been equipped with an X-ray CT apparatus, and it is desired to perform positioning using an X-ray CT current image taken by the X-ray CT apparatus at the time of treatment and an X-ray CT image at the time of treatment planning. There is. In X-ray fluoroscopic images, affected areas that are soft tissues do not appear well, so positioning using bone is fundamental, but positioning using X-ray CT images is based on alignment between affected areas reflected in X-ray CT images. Because you can.

  Therefore, consider a case where the reference image and the current image are expanded to a three-dimensional image in the conventional two-stage pattern matching. The three-dimensional reference image and the three-dimensional current image include a plurality of tomographic images (slice images) captured by the X-ray CT apparatus. Since the three-dimensional current image is assumed to have a small number of images from the viewpoint of X-ray exposure or the like, the three-dimensional current image having a three-dimensional reference image having dense image information and coarser image information than the three-dimensional reference image. It is necessary to compare the image. In the conventional two-stage pattern matching, a two-dimensional reference image having the same density image information and a two-dimensional current image can be compared, but a comparison between a three-dimensional reference image and a three-dimensional current image having different image information densities. In this case, there is a problem that the two-step pattern matching cannot be realized by simply increasing the image dimension of the prior art from two dimensions to three dimensions. That is, similarly to the conventional case, the primary pattern matching from the 3D reference image in the set first setting area to the 3D current image in the second setting area is simply performed, and the extracted second setting area The three-dimensional current image is simply compared with the third three-dimensional reference image in the first setting area, and there is a problem that pattern matching cannot be realized so that the three-dimensional images most closely match.

  The present invention realizes two-step pattern matching (two-step matching) with high accuracy even when the number of tomographic images of a three-dimensional current image is smaller than that of a three-dimensional reference image when positioning a patient for radiation therapy. To aim.

An image collation apparatus according to the present invention includes a three-dimensional image input unit that reads a three-dimensional reference image captured at the time of radiation therapy treatment planning and a three-dimensional current image captured at the time of treatment, and a three-dimensional reference image. And a three-dimensional current image, and a matching processing unit that calculates a body posture correction amount so that the position and orientation of the affected part in the three-dimensional current image matches the position and orientation of the affected part in the three-dimensional reference image. The matching processing unit performs primary pattern matching on the three-dimensional current image from the three-dimensional reference image, and based on the result of the primary pattern matching from one of the three-dimensional reference image or the three-dimensional current image. From the generated predetermined template area to the predetermined search target area generated based on the result of the primary pattern matching from the other of the three-dimensional reference image or the three-dimensional current image different from the generation source of the predetermined template area A secondary matching unit that performs secondary pattern matching, a reference template region generation unit that generates a reference image template region of a three-dimensional region from a three-dimensional reference image based on diseased part information prepared in the three-dimensional reference image, , possess a position and orientation converter for converting the position and orientation of the three-dimensional image, the position and orientation transformation unit, own the position and orientation of the reference image template region A position / orientation conversion template region converted into a fixed position / orientation is generated, and the primary verification unit performs pattern matching on the three-dimensional current image from the position / orientation conversion template region during the primary pattern matching.

  The image matching apparatus according to the present invention performs primary pattern matching from a three-dimensional reference image to a three-dimensional current image, and then determines a predetermined template area and a predetermined search target area based on the result of the primary pattern matching. Generate and execute secondary pattern matching between the search target area and the template area, so even if the number of tomographic images in the 3D current image is smaller than that in the 3D reference image, highly accurate two-step pattern matching Can be realized.

It is a figure which shows the structure of the image collation apparatus and patient positioning device by Embodiment 1 of this invention. It is a figure which shows the whole apparatus structure regarding the image collation apparatus of this invention, and a patient positioning device. It is a figure which shows the three-dimensional reference | standard image and reference | standard image template area | region by Embodiment 1 of this invention. It is a figure which shows the three-dimensional present image by Embodiment 1 of this invention. It is a figure explaining the primary pattern matching method by Embodiment 1 of this invention. It is a figure explaining the relationship between the reference | standard image template area | region and slice image in the primary pattern matching method of FIG. It is a figure which shows the primary extraction area | region of the slice image extracted by the primary pattern matching method by Embodiment 1 of this invention. It is a figure explaining the secondary pattern matching method by Embodiment 1 of this invention. It is a figure explaining the relationship between the reference | standard image template area | region and slice image in the secondary pattern matching method of FIG. It is a figure explaining the primary pattern matching method by Embodiment 2 of this invention. It is a figure explaining the relationship between the reference | standard image template area | region and slice image in the primary pattern matching method of FIG. It is a figure which shows the three-dimensional reference | standard image after the attitude | position conversion by Embodiment 2 of this invention. It is a figure explaining the secondary pattern matching method by Embodiment 2 of this invention. It is a figure which shows the structure of the image collation apparatus and patient positioning device by Embodiment 3 of this invention.

Embodiment 1 FIG.
FIG. 1 is a diagram showing the configuration of an image collating device and a patient positioning device according to Embodiment 1 of the present invention, and FIG. 2 is a diagram showing the overall equipment configuration related to the image collating device and patient positioning device of the present invention. In FIG. 2, reference numeral 1 denotes a CT simulator room for performing a treatment plan performed prior to radiotherapy, which includes a CT gantry 2 and a top board 3 for a CT image capturing bed. CT image data for treatment planning is taken so that the patient 4 is laid and the affected part 5 is included. On the other hand, 6 is a treatment room for performing radiation therapy. Here, there is a CT gantry 7, a rotation treatment table 8, and a top plate 9 at the top of the rotation treatment table 8, and a patient 10 on the top plate 9. The CT image data for positioning is imaged so as to include the affected part 11 at the time of treatment.

  Here, the positioning means that the positions of the patient 10 and the affected part 11 at the time of treatment are calculated from the CT image data for the treatment plan, and the body position correction amount is calculated so as to match the treatment plan. Positioning is performed so that the beam irradiation center 12 is located. The alignment is realized by moving the position of the top plate 9 by driving and controlling the rotary treatment table 8 while the patient 10 is placed on the top plate 9. The rotational treatment table 8 is capable of drive correction with six degrees of freedom of translation and rotation, and by rotating the top plate 9 of the rotational treatment table 8 by 180 degrees, from the CT imaging position (shown by a solid line in FIG. 2). It is also possible to move to a certain treatment position (indicated by a dotted line in FIG. 2) of the irradiation head 13 that emits radiation. In FIG. 2, the CT imaging position and the treatment position are shown to be in an opposing positional relationship of 180 degrees. However, the present invention is not limited to this arrangement form, and the positional relation between them forms another angle such as 90 degrees. It doesn't matter.

  The CT image data for treatment planning and the CT image data for positioning are transferred to the positioning computer 14. The CT image data for treatment planning is a three-dimensional reference image, and the CT image data for positioning is a three-dimensional current image. The image collating device 29 and the patient positioning device 30 according to the present invention both relate to computer software existing in the positioning computer 14, and the image collating device 29 calculates the posture correction amount (translation amount, rotation amount). At the same time, the patient positioning device 30 includes the image collating device 29, and further calculates a parameter for controlling each drive shaft of the rotary treatment table 8 (referred to simply as the treatment table 8 as appropriate) based on the posture correction amount. It is what has. The patient positioning device 30 controls the treatment table 8 based on the matching result (collation result) by the image collating device 29 to guide the target affected part of the particle beam treatment to be positioned at the beam irradiation center 12 of the treatment device.

In positioning in conventional radiotherapy, the DRR (Digitally Reconstructed Radiography) image generated from CT image data for treatment planning and the X-ray fluoroscopic image taken at the same time are compared with the X-ray fluoroscopic image taken in the treatment room at the time of treatment. By doing so, the amount of positional deviation was calculated. In an X-ray fluoroscopic image, the affected part, which is a soft tissue, does not appear well, so positioning using bone is fundamental. In the positioning using the CT image data described in the present embodiment, the CT gantry 7 is installed in the treatment room 6, and the CT image data immediately before the treatment and the CT image data for treatment planning are aligned. It has the feature that it can be drawn directly and can be positioned at the affected area.

  Next, the calculation procedure of the posture correction amount in the image collating device 29 and the patient positioning device 30 in the present embodiment will be described. FIG. 1 shows the relationship between the data processing units constituting the image verification device and the patient positioning device. Here, the image verification device 29 includes a three-dimensional image input unit 21 for reading CT image data, a verification processing unit 22, A verification result display unit 23 and a verification result output unit 24 are provided. A patient positioning device patient positioning device 30 is obtained by adding the treatment table control parameter calculating unit 26 to the image collating device 29.

  As described above, the three-dimensional reference image is data taken for treatment planning at the time of treatment planning, and information on the affected part (affected part shape or the like) indicating the affected part to be subjected to particle beam therapy is input manually. Features. The three-dimensional current image is data taken for patient positioning at the time of treatment, and is characterized by a small number of tomographic images (also called slice images) from the viewpoint of suppressing X-ray exposure.

  In the present invention, primary pattern matching is performed from the three-dimensional reference image to the three-dimensional current image, and then a predetermined template area and a predetermined search target area are generated based on the result of the primary pattern matching. The template region is used to form a two-step pattern matching that performs secondary pattern matching in the same direction or in the opposite direction. In the two-step pattern matching, the matching parameter at the time of primary pattern matching is different from the matching parameter at the time of secondary pattern matching, so that the processing speed and accuracy can be increased. For example, there is a method in which primary pattern matching is performed on a wide range with a coarse resolution, and secondary pattern matching is performed on a narrowed down range with a fine resolution using the found template area or search target area. .

  The three-dimensional image input unit 21 will be described. The three-dimensional image input unit 21 captures an image group (slice image group) in DICOM (Digital Imaging and Communications in Medicine) format from an image group that is captured by an X-ray CT apparatus and is configured into a plurality of tomographic images. It is read as volume data. The CT image data for treatment planning is three-dimensional volume data at the time of treatment planning, that is, a three-dimensional reference image. The CT image data for positioning is three-dimensional volume data at the time of treatment, that is, a three-dimensional current image. The CT image data is not limited to the DICOM format, and may be in other formats.

  The collation processing unit 22 collates (pattern matching) the 3D reference image and the 3D current image, and corrects the body position so that the position and orientation of the affected part in the 3D current image matches the position and orientation of the affected part in the 3D reference image. Calculate the quantity. The collation result display unit 23 displays the collation result by the collation processing unit 22 (postural correction amount described later, an image obtained by superimposing a three-dimensional current image moved by the posture correction amount on a three-dimensional reference image, and the like). It is displayed on the monitor screen of the positioning computer 14. The collation result output unit 24 corrects the correction amount when the collation processing unit 22 collates the three-dimensional reference image with the three-dimensional current image, that is, the posture correction amount (translation amount, rotation amount) calculated by the collation processing unit 22. Is output. The treatment table control parameter calculation unit 26 uses the output values of the matching result output unit 24 (total six degrees of freedom of three translational axes [ΔX, ΔY, ΔZ] and three rotation axes [ΔA, ΔB, ΔC]) as the treatment table 8. Are converted into parameters for controlling the respective axes, that is, the parameters are calculated. The treatment table 8 drives the driving device for each axis of the treatment table 8 based on the treatment table control parameter calculated by the treatment table control parameter calculation unit 26. As a result, the body position correction amount can be calculated so as to match the treatment plan, and the affected part 11 at the time of treatment can be positioned so as to be at the beam irradiation center 12 of the radiation treatment.

  The collation processing unit 22 includes a position / orientation conversion unit 25, a primary collation unit 16, a secondary collation unit 17, and a reference template region generation unit 18. The position / orientation conversion unit 25 changes the position / orientation of the target data at the time of primary pattern matching or secondary pattern matching. The primary matching unit 16 performs primary pattern matching on the three-dimensional current image from the three-dimensional reference image. The secondary collation unit 17 uses a three-dimensional reference different from the generation source of the predetermined template region from a predetermined template region generated based on the result of the primary pattern matching from one of the three-dimensional reference image or the three-dimensional current image. Secondary pattern matching is performed on a predetermined search target region generated based on the result of primary pattern matching from the other of the image or the three-dimensional current image.

  The matching processing unit 22 will be described in detail with reference to FIGS. 3 to 9. FIG. 3 is a diagram showing a three-dimensional reference image and a reference image template region according to Embodiment 1 of the present invention. FIG. 4 is a diagram showing a three-dimensional current image according to Embodiment 1 of the present invention. FIG. 5 is a diagram for explaining a primary pattern matching method according to Embodiment 1 of the present invention. FIG. 6 is a diagram for explaining the relationship between the reference image template region and the slice image in the primary pattern matching method of FIG. FIG. 7 is a diagram showing a primary extraction region of a slice image extracted by the primary pattern matching method according to Embodiment 1 of the present invention. FIG. 8 is a diagram for explaining a secondary pattern matching method according to Embodiment 1 of the present invention. FIG. 9 is a diagram for explaining the relationship between the reference image template region and the slice image in the secondary pattern matching method of FIG.

  The reference template region generation unit 18 of the matching processing unit 22 generates a reference image template region 33 from the three-dimensional reference image 31 using the affected part shape (affected part information) input at the time of treatment planning. The three-dimensional reference image 31 is composed of a plurality of slice images 32. FIG. 3 shows an example of five slice images 32a, 32b, 32c, 32d, and 32e so as not to be complicated. The shape of the affected part is input as a ROI (Region of Interest) 35 as a closed contour surrounding the affected part for each slice image. The region including the closed contour may be a circumscribed rectangle 34, for example, and a rectangular parallelepiped region including each circumscribed rectangle 34 may be a template region. This template area is referred to as a reference image template area 33. The primary matching unit 16 of the matching processing unit 22 performs primary pattern matching of the reference image template region 33 with the three-dimensional current image 36. The three-dimensional current image 36 shown in FIG. 4 shows an example composed of three slice images 37a, 37b, and 37c. The current image area 38 shown in FIG. 5 is expressed as a rectangular parallelepiped including three slice images 37a, 37b, and 37c. As shown in FIG. 5, the reference image template region 33 (33a, 33b, 33c) is moved in a raster scan pattern in the current image region 38, and a correlation value with the three-dimensional current image 36 is calculated. As the correlation value, any correlation value used in image matching (image matching) such as a normalized cross-correlation value can be used.

  In the reference image template region 33a, the slice image 37a is moved in a raster scan shape along the scan path 39a. Similarly, the reference image template region 33b is moved along the scan path 39b in a raster scan manner on the slice image 37b, and the reference image template region 33c is moved along the scan route 39c in a raster scan manner. The scanning paths 39b and 39c are shown in a simplified manner so as not to make the figure complicated.

  In the primary pattern matching, as shown in FIG. 6, for each slice image 53 constituting the reference image template region 33, image matching with the slice image 37 constituting the current image region 38 is performed. The slice image 53 is an image divided by the reference image template region 33 in the slice image 32 of the three-dimensional reference image 31. The reference image template area 33 includes five slice images 53a, 53b, 53c, 53d, and 53e corresponding to the five slice images 32a, 32b, 32c, 32d, and 32e in the three-dimensional reference image. Therefore, at the time of primary pattern matching, image matching is performed on each of the five slice images 53a, 53b, 53c, 53d, and 53e in the reference image template region 33 with respect to the slice image 37a of the three-dimensional current image 36. Do. Image matching is similarly performed on the slice images 37b and 37c of the three-dimensional current image 36.

  The primary collation unit 16 uses each slice image 37 of the three-dimensional current image 36 so as to include a region where the correlation value between the current image region 38 and the reference image template region 33 is the highest by the primary pattern matching. The primary extraction area 43 is extracted. As shown in FIG. 7, a primary extraction region 43a is extracted from the slice image 37a of the three-dimensional current image 36. Similarly, primary extraction regions 43b and 43c are extracted from the slice images 37b and 37c of the three-dimensional current image 36. A primary extraction current image area 42 which is a search target area used for secondary pattern matching is generated so as to include the primary extraction areas 43a, 43b, and 43c. As described above, the primary matching unit 16 generates the primary extracted current image area 42 that is a search target area used for the secondary pattern matching.

  Here, in the state before positioning, since the postures (the three rotation axes) of the three-dimensional reference image 31 and the three-dimensional current image 36 do not match, in the simple raster scan as shown in FIG. If the number of slices is small, matching with high accuracy for detecting an angle shift cannot be performed, but there is no problem in extracting the primary extraction region 43 for performing secondary pattern matching. Therefore, in the primary pattern matching, the correlation value is calculated without detecting even the angle deviation, and in the subsequent secondary pattern matching, matching with high accuracy for detecting the angle deviation is performed.

  Secondary pattern matching will be described. In the secondary pattern matching, the position / orientation conversion template region 40 obtained by converting the position / orientation of the reference image template region 33 generated from the three-dimensional reference image 31 is generated by the position / orientation conversion unit 25 of the matching processing unit 22. In the secondary pattern matching, as shown in FIGS. 8 and 9, the posture change amount (rotation three axes) of the reference image template region 33 is added as a parameter at the time of matching. The secondary verification unit 17 shifts the angle between the position / orientation conversion template region 40 whose position / orientation is converted by the position / orientation conversion unit 25 and the primary extraction current image region 42 of the three-dimensional current image 36 with a small number of slice images. High-precision matching is included. By doing in this way, highly accurate two-step pattern matching including angle deviation is realizable. The primary extraction region found by performing a primary pattern matching on a wide range with a coarse resolution by targeting a narrow range including the region obtained by the primary pattern matching as a search range of the secondary pattern matching. Secondary pattern matching can be performed with high resolution using the primary extraction current image area 42 including 43, and the time required for pattern matching can be shortened.

The primary extraction current image area 42 shown in FIG. 8 is expressed as a rectangular parallelepiped including three primary extraction areas 43a, 43b, and 43c. The position / orientation conversion template area 40a, which is the reference image template area whose position / orientation has been converted, is moved in a raster scan manner along the scan path 39a in the primary extraction area 43a of the slice image 37a. Similarly, the position / orientation conversion template region 40b in which the position / orientation has been converted is moved in a raster scan manner along the scan path 39b in the primary extraction region 43b of the slice image 37b. In 40c, the primary extraction region 43c of the slice image 37c is moved in a raster scan manner along the scan path 39c. The scanning paths 39b and 39c are shown in a simplified manner so as not to make the figure complicated.

  At the time of the secondary pattern matching, the secondary verification unit 17 performs primary extraction of the slice image 37 constituting the cross section 41 of the position / orientation conversion template region 40 and the primary extraction current image region 42 as shown in FIG. Image collation with the area 43 is performed. In addition, image verification may be performed between the slice image 55 that is an image divided by the primary extraction current image region 42 in the slice image 37 of the three-dimensional current image 36 and the cross section 41. The cross section 41 of the position / orientation conversion template region 40 is generated from a plurality of slice images 32 of the three-dimensional reference image 31. For example, the data of the cross section 41 is cut out from a plurality of slice images 32 constituting the three-dimensional reference image 31. Normally, the data density of the cross section 41 of the position / orientation conversion template area 40 and the data density of the primary extraction area 43 of the three-dimensional current image 36 are different, but a correlation value for each pixel of the cross section 41 may be calculated. Further, the cross section 41 of the position / orientation conversion template region 40 may include data supplemented so that the data density thereof is the same as the data density of the primary extraction region 43 of the three-dimensional current image 36.

  Here, the two-stage pattern matching method of the first embodiment will be summarized. First, the reference template region generation unit 18 of the matching processing unit 22 generates a reference image template region 33 from the three-dimensional reference image 31 (reference image template region generation procedure). The primary matching unit 16 performs primary pattern matching on the three-dimensional current image 36 from the reference image template region 33 (primary pattern matching procedure). In the primary pattern matching, for each slice image 53 constituting the reference image template region 33, image matching with the slice image 37 constituting the current image region 38 is performed. The primary collation unit 16 calculates a correlation value between the current image region 38 and the reference image template region 33 every time the reference image template region 33 is scanned (correlation value calculation procedure). The primary extraction region 43 is extracted so as to include the region having the highest correlation value between the region 38 and the reference image template region 33 (primary extraction region extraction procedure). The primary collation unit 16 generates a primary extraction current image area 42 that is a search target area used for secondary pattern matching so as to include a primary extraction area 43 for each slice image 37 constituting the current image area 38. (Search target generation procedure). The two-stage pattern matching method of the first embodiment includes a reference image template region generation procedure, a primary pattern matching procedure, and a secondary pattern matching procedure described later. The primary pattern matching procedure includes a correlation value calculation procedure, a primary extraction region extraction procedure, and a search target generation procedure.

  Next, the secondary verification unit 17 of the verification processing unit 22 performs the primary extraction current of the three-dimensional current image 36 from the position / orientation conversion template region 40 obtained by converting the position / orientation of the reference image template region 33 by the position / orientation conversion unit 25. Secondary pattern matching is executed on the image area 42 (secondary pattern matching procedure). In the secondary pattern matching, a plurality of cross-sections 41 of the position / orientation conversion template region 40 converted into a predetermined position / orientation are generated (section generation procedure), and the slice image 37 constituting the primary extraction current image region 42 for each cross-section 41. The image is collated between the primary extraction region 43 and the slice image 55 and the cross section 41. Each time the secondary collation unit 17 scans the position / orientation conversion template area 40, the secondary collation unit 17 calculates a correlation value between the primary extracted current image area 42 and a plurality of cross sections 41 of the position / orientation conversion template area 40 (correlation value calculation procedure). ). In addition, the position / orientation conversion unit 25 converts the position / orientation into a position / orientation different from the previous position / orientation (position / orientation conversion procedure), and the secondary verification unit 17 generates a plurality of cross sections 41 of the position / orientation conversion template region 40 in the position / orientation. Each time the position / orientation conversion template area 40 is scanned, the correlation value between the primary extracted current image area 42 and the plurality of sections 41 of the position / orientation conversion template area 40 is calculated (correlation value calculation procedure). ). The secondary collation unit 17 of the collation processing unit 22 selects the position / orientation relationship (position / orientation information) between the three-dimensional reference image and the three-dimensional current image that have the highest correlation value among the calculated correlation values as the optimum solution. (Optimal solution selection procedure). In this way, pattern matching is realized so that the three-dimensional images of the three-dimensional reference image and the three-dimensional current image most closely match. The secondary pattern matching procedure includes a section generation procedure, a correlation value calculation procedure, a position / orientation conversion procedure, and an optimum solution selection procedure.

  After the pattern matching is completed, the matching processing unit 22 calculates the 3D reference image 31 and the 3D current image 36 from the position / orientation of the position / orientation conversion template region 40 having the highest correlation value among the calculated correlation values. The posture correction amount (translation amount, rotation amount) at the time of collation is calculated (position correction amount calculation procedure). The collation result display unit 23 displays on the monitor screen of the computer 14 the body position correction amount, an image obtained by superimposing the 3D current image moved by the body position correction amount on the 3D reference image, and the like. The collation result output unit 24 outputs a posture correction amount (translation amount, rotation amount) when the collation processing unit 22 collates the three-dimensional reference image 31 and the three-dimensional current image 36 (position correction amount output procedure). . The treatment table control parameter calculation unit 26 uses the output values of the matching result output unit 24 (total six degrees of freedom of three translational axes [ΔX, ΔY, ΔZ] and three rotation axes [ΔA, ΔB, ΔC]) as the treatment table 8. Are converted into parameters for controlling the respective axes, that is, parameters are calculated (treatment table control parameter calculation procedure). The treatment table 8 drives the driving device for each axis of the treatment table 8 based on the treatment table control parameter calculated by the treatment table control parameter calculation unit 26 (treatment table driving procedure).

  The image matching device 29 according to the first embodiment performs primary pattern matching from the three-dimensional reference image 31 to the three-dimensional current image 36, and then determines a predetermined value from the three-dimensional reference image 31 based on the result of the primary pattern matching. A position / orientation conversion template region 40 which is a template region for secondary pattern matching is generated, and is a predetermined search target region used for secondary pattern matching so as to include a primary extraction region 43 from the three-dimensional current image 36. Since the primary extraction current image region 42 is generated, even when the number of tomographic images (slice images) of the three-dimensional current image 36 is smaller than that of the three-dimensional reference image 31, high-precision two-stage pattern matching is realized. can do.

  The image matching device 29 according to the first embodiment realizes two-step pattern matching with high accuracy even when the number of tomographic images (slice images) of the three-dimensional current image 36 is smaller than that of the three-dimensional reference image 31. Therefore, the number of tomographic images of the three-dimensional current image 36 by the X-ray CT apparatus at the time of alignment can be reduced, and the exposure dose of the patient by the X-ray CT apparatus at the time of alignment can be reduced. it can.

  The image collating device 29 according to the first embodiment generates a primary extracted current image area 42 based on the result of executing the primary pattern matching from the 3D reference image 31 to the 3D current image 36, and the current image area 38. The primary extraction current image including the primary extraction area 43 found by performing the primary pattern matching on a wide area with a coarse resolution by making the primary extraction current image area 42 which is a narrower area as a search target. Using the region 42, the secondary pattern matching can be performed with a high resolution, and the time required for the pattern matching can be shortened.

  The patient positioning device 30 according to the first embodiment can be adapted to the position and orientation in the treatment plan based on the body posture correction amount calculated by the image collating device 29. Since it can be adapted to the position and orientation at the time of treatment planning, it can be aligned so that the affected part 11 at the time of treatment comes to the beam irradiation center 12 of radiotherapy.

The patient positioning device 30 according to the first embodiment has a smaller number of tomographic images (slice images) than the three-dimensional reference image 31 from the reference image template region 33 obtained from the three-dimensional reference image 31 by the position / orientation conversion unit 25. A position / orientation conversion template region 40 suitable for matching with the three-dimensional current image 36 can be generated, and two-stage pattern matching with high accuracy including an angle deviation can be realized.

  According to the image collating device 29 according to the first embodiment, a three-dimensional image input unit that reads each of the three-dimensional reference image 31 photographed at the time of radiation therapy treatment planning and the three-dimensional current image 36 photographed at the time of treatment. 21, the three-dimensional reference image 31 and the three-dimensional current image 36 are collated, and the body position correction amount is calculated so that the position and orientation of the affected part in the three-dimensional current image 36 match the position and posture of the affected part in the three-dimensional reference image 31. A matching processing unit 22, and the matching processing unit 22 performs primary pattern matching on the three-dimensional current image 36 from the three-dimensional reference image 31 and the three-dimensional reference image 31 or three-dimensional. From a predetermined template region (position and orientation conversion template region 40) generated based on the result of the primary pattern matching from one of the current images 36, a predetermined template region (position For a predetermined search target region 42 generated based on the result of the primary pattern matching from the other of the three-dimensional reference image 31 or the three-dimensional current image 36 different from the generation source of the posture conversion template region 40) A second matching unit 17 that performs pattern matching, so that even if the number of tomographic images of the three-dimensional current image 36 is smaller than that of the three-dimensional reference image 31, high-precision two-stage pattern matching is realized. Can do.

  According to the patient positioning device 30 according to the first embodiment, the treatment table control that calculates the parameters for controlling each axis of the treatment table 8 based on the image matching device 29 and the body posture correction amount calculated by the image matching device 29. A parameter calculation unit 26, and the image collating device 29 reads a 3D reference image 31 photographed at the time of radiation therapy treatment planning and a 3D current image 36 photographed at the time of treatment, respectively. The input unit 21, the 3D reference image 31 and the 3D current image 36 are collated, and the position correction amount is adjusted so that the position and orientation of the affected part in the 3D current image 36 matches the position and orientation of the affected part in the 3D reference image 31. And a collation processing unit 22 to calculate. The matching processing unit 22 performs primary pattern matching on the three-dimensional current image 36 from the three-dimensional reference image 31 and the primary pattern from one of the three-dimensional reference image 31 or the three-dimensional current image 36. From a predetermined template region (position / orientation conversion template region 40) generated based on the matching result, a three-dimensional reference image 31 or a three-dimensional current image different from the generation source of the predetermined template region (position / orientation conversion template region 40) A secondary collating unit 17 that performs secondary pattern matching on a predetermined search target region 42 generated based on the result of primary pattern matching from the other side of the image 36. Even if the number of tomographic images is smaller than that of the three-dimensional reference image 31, highly accurate positioning can be performed.

  The image collating method according to the first embodiment is an image collating method for collating the three-dimensional reference image 31 photographed at the time of radiation therapy treatment planning with the three-dimensional current image 36 photographed at the time of treatment. The primary pattern matching procedure for executing the primary pattern matching from the 3D reference image 31 to the 3D current image 36 and the result of the primary pattern matching from either the 3D reference image 31 or the 3D current image 36 The three-dimensional reference image 31 or the three-dimensional current image 36 that is different from the generation source of the predetermined template region (position / posture conversion template region 40) from the predetermined template region (position / posture conversion template region 40) generated based on The secondary pattern matching is performed on the predetermined search target area 42 generated based on the result of the primary pattern matching from the other side. The secondary pattern matching procedure is executed, so that even when the number of tomographic images of the three-dimensional current image 36 is smaller than that of the three-dimensional reference image 31, highly accurate two-step pattern matching can be realized. it can.

Embodiment 2. FIG.
In the two-step pattern matching according to the second embodiment, primary pattern matching is performed from the three-dimensional reference image 31 to the three-dimensional current image 36, and then a predetermined value is obtained from the three-dimensional current image 36 based on the result of the primary pattern matching. A current image template region 44, which is a template region for secondary pattern matching, is generated, and the posture conversion reference image region 47 obtained by converting the position and posture of the three-dimensional reference image 31 is used as a search target to change the posture from the current image template region 44. Secondary pattern matching is performed on the reference image region 47. Secondary pattern matching is pattern matching in the opposite direction to primary pattern matching.

  FIG. 10 is a diagram for explaining a primary pattern matching method according to Embodiment 2 of the present invention, and FIG. 11 is a diagram for explaining a relationship between a reference image template region and a slice image in the primary pattern matching method of FIG. . In the second embodiment, in the primary pattern matching, the primary verification unit 16 performs a search including up to three rotation axes to obtain the posture change amount.

  The current image area 38 shown in FIG. 10 is expressed as a rectangular parallelepiped including three slice images 37a, 37b, and 37c. The position / orientation conversion template regions 40a, 40b, and 40c, which are reference image template regions of the second embodiment, are obtained by converting the position / orientation by the position / orientation conversion unit 25. However, the initial position and orientation are in the default state, for example, the parameters for the three rotation axes are zero. The position / orientation conversion template area 40a, which is the reference image template area whose position / orientation has been converted, is moved along the scan path 39a in a raster scan manner along the slice image 37a. Similarly, the position / orientation conversion template region 40b in which the position / orientation has been converted is moved in a raster scan manner along the scan path 39b in the slice / image 37b, and the position / orientation conversion template region 40c in which the position / orientation has been converted is converted into the slice image 37c. It is moved in the form of a raster scan along the scan path 39c. The scanning paths 39b and 39c are shown in a simplified manner so as not to make the figure complicated.

  The correlation calculation between the slice images 37a, 37b, and 37c of the three-dimensional current image 36 and the position / orientation conversion template region 40 is performed while changing the position and orientation. For example, the correlation calculation is performed by changing at a predetermined change amount or change rate for each of the three rotation axes, and the correlation calculation is performed by moving to the next scan position. As shown in FIG. 11, the primary collation unit 16 performs image collation between the cross section 41 of the position / orientation conversion template region 40 and the slice image 37 constituting the current image region 38. The cross section 41 of the position / orientation conversion template region 40 is a surface obtained by cutting the position / orientation conversion template region 40 along a plane parallel to the slice image 32 of the three-dimensional reference image 31 that is the initial position and orientation. It generates from a plurality of slice images 32 (section generation procedure). For example, the method described in Embodiment 1 can be used. That is, the data of the cross section 41 can be cut out from a plurality of slice images 32 constituting the three-dimensional reference image 31. The cross section 41 of the position / orientation conversion template region 40 may include data supplemented so that the data density thereof is the same as the data density of the three-dimensional current image 36.

  Next, the primary collation unit 16 generates a current image template region 44 used for secondary pattern matching. The primary collation unit 16 determines, for example, the cross-section 41 of the position / orientation conversion template region 40 having the highest correlation value from the search result including up to three rotation axes for each slice image 37a, 37b, and 37c, and the position / orientation at that time. The posture change amount of the conversion template region 40 and the extraction region of the slice image 37 corresponding to the cross section 41 are obtained. The primary collation unit 16 generates a current image template region 44 so as to include the extracted region of the three-dimensional current image having the highest correlation value from the obtained extracted regions for each slice image. The current image template area 44 is a two-dimensional image.

Next, as shown in FIG. 12, the position / orientation conversion unit 25 of the matching processing unit 22 changes the attitude of the entire three-dimensional reference image 31 with the attitude change amount obtained when the current image template region 44 is generated. Then, a three-dimensional posture conversion reference image 45 after posture conversion, that is, a posture conversion reference image region 47 is generated. FIG. 12 is a diagram showing a three-dimensional reference image after posture conversion according to Embodiment 2 of the present invention. The slice images 46a, 46b, 46c, 46d, and 46e are slice images in which the postures of the slice images 32a, 32b, 32c, 32d, and 32e are changed by the posture change amount.

  Next, as shown in FIG. 13, the secondary collation unit 17 moves the current image template region 44 along the scan path 49 with respect to the posture conversion reference image region 47 which is the three-dimensional posture conversion reference image 45 after posture conversion. By matching in a raster scan shape, only translational deviation can be detected at high speed. FIG. 13 is a diagram for explaining a secondary pattern matching method according to the second embodiment of the present invention. The posture conversion reference image region 47 subjected to posture conversion is expressed as a rectangular parallelepiped including five slice images 46a, 46b, 46c, 46d, and 46e. The collation execution surface 48 is an image surface corresponding to the posture corresponding to the slice image 37 of the three-dimensional current image 36 and the posture having the highest correlation value by the primary pattern matching, that is, the three-dimensional current image in the posture conversion reference image region 47. This is a surface having a posture equivalent to the posture corresponding to the slice image 37 of the image 36. The secondary collation unit 17 generates a predetermined collation execution surface 48 from the posture conversion reference image region 47 from a plurality of slice images 46 of the three-dimensional posture conversion reference image 45 (collation execution surface generation procedure). For example, the method described in Embodiment 1 can be used. That is, the data of the collation execution surface 48 can be cut out from a plurality of slice images constituting the three-dimensional posture conversion reference image 45. The collation execution surface 48 may include data supplemented so that the data density is the same as the data density of the current image template region 44.

  The two-stage pattern matching method of the second embodiment will be summarized. First, the collation processing unit 22 generates a position / orientation conversion template region 40 obtained by converting the position / orientation from the three-dimensional reference image 31 by the position / orientation conversion unit 25 (position / orientation conversion template region generation procedure). The primary matching unit 16 of the matching processing unit 22 performs primary pattern matching on the position / orientation conversion template region 40 with respect to the three-dimensional current image 36 (primary pattern matching procedure). The primary pattern matching is performed every time the position and orientation of the position and orientation conversion template region 40 is changed for each slice image 37 constituting the current image region 38 (every time the position and orientation conversion procedure is executed). A cross section 41 of the area 40 is generated (cross section generation procedure), and image verification is performed between the cross section 41 of the position / orientation conversion template area 40 and the slice image 37 constituting the current image area 38.

  The primary collation unit 16 calculates a correlation value between the current image region 38 and the position / orientation conversion template region 40 every time the position / orientation of the position / orientation conversion template region 40 is changed (correlation value calculation procedure). Further, each time the position / orientation conversion template area 40 is scanned, the primary collation unit 16 calculates a correlation value between the current image area 38 and the position / orientation conversion template area 40 and performs primary pattern matching to obtain the current image area 38. The current image template region 44 is generated so as to include the extracted region of the position / orientation conversion template region 40 having the highest correlation value between the position / orientation conversion template region 40 (current image template region generation procedure).

  Next, the collation processing unit 22 causes the position / orientation conversion unit 25 to change the attitude of the entire three-dimensional reference image 31 by the attitude change amount obtained when the current image template region 44 is generated. 3D posture conversion reference image 45, that is, posture conversion reference image region 47 is generated (posture conversion reference image region generation procedure). The secondary collation unit 17 performs secondary pattern matching on the current image template region 44 against the posture conversion reference image region 47 (secondary pattern matching procedure). In the secondary pattern matching, the collation execution plane 48 is generated by the collation execution plane generation procedure, and the collation execution plane 48 generated by the collation execution plane generation procedure and the current image template region 44 are collated. At the time of this image matching, the correlation value between the matching execution surface 48 and the current image template region 44 is calculated while the current image template region 44 is translated without being rotated (correlation value calculation procedure).

  In the secondary pattern matching, the secondary matching unit 17 of the matching processing unit 22 determines the position / posture relationship between the three-dimensional posture conversion reference image 45 that has the highest correlation value among the calculated correlation values and the current image template region 44 ( Position and orientation information) is selected as the optimal solution (optimal solution selection procedure). In this way, pattern matching is realized by two-stage matching so that the three-dimensional images of the three-dimensional reference image 31 and the three-dimensional current image 36 are the best match. The two-stage pattern matching method of the second embodiment includes a position / orientation conversion template region generation procedure, a primary pattern matching procedure, an orientation conversion reference image region generation procedure, and a secondary pattern matching procedure. The primary pattern matching procedure includes a section generation procedure, a correlation value calculation procedure, a position / orientation conversion procedure, and a current image template region generation procedure. The secondary pattern matching procedure includes a collation execution surface generation procedure, a correlation value calculation procedure, and an optimal solution selection procedure.

  After the pattern matching is completed, the matching processing unit 22 determines the three-dimensional reference images 31 and 3 from the position and orientation of the high correlation value region in the three-dimensional orientation conversion reference image 45 that has the highest correlation value among the calculated correlation values. The posture correction amount (translation amount, rotation amount) when collating with the dimension current image 36 is calculated (position correction amount calculation procedure). The collation result display unit 23 displays on the monitor screen of the computer 14 the body position correction amount, an image obtained by superimposing the 3D current image moved by the body position correction amount on the 3D reference image, and the like. The collation result output unit 24 outputs a posture correction amount (translation amount, rotation amount) when the collation processing unit 22 collates the three-dimensional reference image 31 and the three-dimensional current image 36 (position correction amount output procedure). . The treatment table control parameter calculation unit 26 uses the output values of the matching result output unit 24 (total six degrees of freedom of three translational axes [ΔX, ΔY, ΔZ] and three rotation axes [ΔA, ΔB, ΔC]) as the treatment table 8. Are converted into parameters for controlling the respective axes, that is, parameters are calculated (treatment table control parameter calculation procedure). The treatment table 8 drives the driving device for each axis of the treatment table 8 based on the treatment table control parameter calculated by the treatment table control parameter calculation unit 26 (treatment table driving procedure).

  The image matching device 29 according to the second embodiment performs primary pattern matching, which is image matching including up to three rotation axes, from the position / orientation conversion template region 40 of the three-dimensional reference image 31 to the three-dimensional current image 36, Next, since the current image template region 44 that is a template region for secondary pattern matching is generated from the three-dimensional current image 36 based on the result of the primary pattern matching, the number of tomographic images of the three-dimensional current image 36 (slices) Even when the number of images) is smaller than that of the three-dimensional reference image 31, it is possible to realize two-step pattern matching with high accuracy.

  The image collating device 29 according to the second embodiment generates a three-dimensional posture conversion reference image 45 that is a three-dimensional reference image after posture conversion from the three-dimensional reference image 31, that is, a posture conversion reference image region 47. Using the current image template area 44, direct pattern matching can be realized by translation without rotational movement with respect to the orientation conversion reference image area 47. In the secondary pattern matching, only the correlation value for each translational movement is calculated, so that the speed of the secondary pattern matching can be increased as compared with the case of calculating the correlation value for each rotational movement and translational movement.

Embodiment 3 FIG.
In the third embodiment, the reference image template region 33 for primary pattern matching in the first embodiment and the reference image template region 33 that is the origin of the position / orientation conversion template region 40 in the second embodiment are stored in a human body database (Atlas). It differs from the first and second embodiments in that it is generated using a model. FIG. 14 is a diagram showing a configuration of an image collating device and a patient positioning device according to Embodiment 3 of the present invention. The image collation device 29 according to the third embodiment is different from the image collation device 29 according to the first and second embodiments in that it includes a human body database input unit 50 and an average template region generation unit 51. The patient positioning device 30 according to the third embodiment includes an image matching device 29 and a treatment table control parameter calculation unit 26.

  The human body database input unit 50 acquires a human body database (atlas model) from a storage device such as a database device. The average template region generation unit 51 cuts out the average template region 54 from the organ part of the human body database corresponding to the affected parts 5 and 11 of the patients 4 and 10. The reference template region generation unit 18 of the matching processing unit 22 automatically generates the reference image template region 33 by pattern matching the average template region 54 with the three-dimensional reference image 31 (reference image template region generation procedure).

  The two-step pattern matching of the first embodiment and the two-step pattern matching of the second embodiment are executed using the reference image template region 33 described above. By doing in this way, two-step pattern matching can be realized without preparing information (affected part shape or the like) indicating the affected part in advance on the three-dimensional reference image.

  Note that the average template region generation unit 51 may cut out a two-dimensional average template region from the organ portion of the human body database corresponding to the affected portions 5 and 11 of the patients 4 and 10. In the case of the two-dimensional average template region 54, a plurality of two-dimensional average template regions may be cut out, and a plurality of two-dimensional average template regions may be bundled and output to the matching processing unit 22. The reference template region generation unit 18 of the matching processing unit 22 automatically generates the reference image template region 33 by pattern matching the plurality of two-dimensional average template regions to the three-dimensional reference image 31.

  DESCRIPTION OF SYMBOLS 16 ... Primary collation part, 17 ... Secondary collation part, 18 ... Reference | standard template area | region production | generation part, 21 ... Three-dimensional image input part, 22 ... Collation processing part, 25 ... Position and orientation conversion part, 26 ... Treatment table control parameter calculation , 29 ... Image collation device, 30 ... Patient positioning device, 31 ... Three-dimensional reference image, 33 ... Reference image template region, 36 ... Three-dimensional current image, 40, 40a, 40b, 40c ... Position and orientation conversion template region, 41 ... Section, 42... Primary extraction current image region, 44... Current image template region, 45... 3D posture conversion reference image, 48.

Claims (11)

A three-dimensional image input unit for reading a three-dimensional reference image captured during a radiotherapy treatment plan and a three-dimensional current image captured during treatment;
A collation processing unit that collates the three-dimensional reference image with the three-dimensional current image and calculates a body position correction amount so that the position and orientation of the affected part in the three-dimensional current image matches the position and orientation of the affected part in the three-dimensional reference image And comprising
The verification processing unit includes a primary verification unit that performs primary pattern matching on the three-dimensional current image from the three-dimensional reference image;
From the predetermined template region generated based on the result of the primary pattern matching from one of the three-dimensional reference image or the three-dimensional current image, the three-dimensional reference image different from the generation source of the predetermined template region or A secondary matching unit that performs secondary pattern matching on a predetermined search target region generated based on the result of the primary pattern matching from the other of the three-dimensional current image;
A reference template region generation unit that generates a reference image template region of a three-dimensional region from the three-dimensional reference image based on diseased part information prepared in the three-dimensional reference image;
The position and orientation converter for converting the position and orientation of the three-dimensional image, the possess,
The position / orientation conversion unit generates a position / orientation conversion template region obtained by converting the position / orientation of the reference image template region into a predetermined position / orientation;
The primary collating unit performs pattern matching on the three-dimensional current image from the position / orientation conversion template region during the primary pattern matching . A three-dimensional image input unit for reading a three-dimensional reference image captured during a radiotherapy treatment plan and a three-dimensional current image captured during treatment;
A collation processing unit that collates the three-dimensional reference image with the three-dimensional current image, and calculates a body position correction amount so that the position and orientation of the affected part in the three-dimensional current image matches the position and orientation of the affected part in the three-dimensional reference image When,
A human body database input unit for acquiring a human body database from the database device;
An average template region generating unit that generates an average template region from an organ portion corresponding to an affected area of a patient in the human body database,
The verification processing unit includes a primary verification unit that performs primary pattern matching on the three-dimensional current image from the three-dimensional reference image;
From the predetermined template region generated based on the result of the primary pattern matching from one of the three-dimensional reference image or the three-dimensional current image, the three-dimensional reference image different from the generation source of the predetermined template region or A secondary matching unit that performs secondary pattern matching on a predetermined search target region generated based on the result of the primary pattern matching from the other of the three-dimensional current image;
A reference template region generating unit that performs pattern matching on the three-dimensional reference image from the average template region, and generates a reference image template region of the three-dimensional region from the three-dimensional reference image based on the result of the pattern matching ;
The position and orientation converter for converting the position and orientation of the three-dimensional image, the possess,
The position / orientation conversion unit generates a position / orientation conversion template region obtained by converting the position / orientation of the reference image template region into a predetermined position / orientation;
The primary verification unit, when said primary pattern matching, the position and orientation transformation from said template region 3 dimensional current images matching device you and performs pattern matching for the image. The primary verification unit generates a cross section parallel to the slice image of the three-dimensional reference image in the position / orientation conversion template region , performs pattern matching between the three-dimensional current image and the cross section, and Determination of a highly correlated section that is a section having the highest correlation value from among a plurality of sections, calculation of a posture change amount in the position / orientation conversion template region, and extraction of an extraction region corresponding to the highly correlated section in the three-dimensional current image The image collating apparatus according to claim 1, wherein the image collating apparatus is executed. The primary collation unit generates a current image template region that is the predetermined template region so as to include the extraction region extracted at the time of the primary pattern matching,
The position / orientation conversion unit generates an attitude conversion reference image region obtained by converting the position / orientation of the three-dimensional reference image by the amount of change in posture of the extraction region corresponding to the current image template region;
The secondary verification unit, said when the secondary pattern matching, the current claim 3, wherein the performing pattern matching with respect to the posture changing reference image area that is the search target area from the image template region Image matching device. The secondary collation unit generates a collation execution surface that is a cross section parallel to the slice image of the three-dimensional current image in the posture conversion reference image region , and between the current image template region and the collation execution surface. The image matching apparatus according to claim 4, wherein pattern matching is performed. An image collation device according to any one of claims 1 to 5 ,
A patient positioning apparatus comprising: a treatment table control parameter calculation unit that calculates parameters for controlling each axis of the treatment table based on the posture correction amount calculated by the image collating device. An image collation method for collating a three-dimensional reference image photographed during radiation therapy treatment planning with a three-dimensional current image photographed during treatment,
A reference image template region generation procedure for generating a reference image template region of a three-dimensional region from the three-dimensional reference image;
A position and orientation conversion template region generation procedure for generating a position and orientation conversion template region obtained by converting the position and orientation of the reference image template region into a predetermined position and orientation ;
A primary pattern matching procedure for performing primary pattern matching on the three-dimensional current image from the position and orientation conversion template region ;
Before Symbol primary pattern wherein the position and orientation transformation template region is a predetermined template region generated based on the result of the matching, which is generated based on the prior Symbol 3-dimensional current picture image or al the primary pattern matching result And a secondary pattern matching procedure for performing secondary pattern matching on a predetermined search target region. A three-dimensional image input unit for reading a three-dimensional reference image captured during a radiotherapy treatment plan and a three-dimensional current image captured during treatment;
A collation processing unit that collates the three-dimensional reference image with the three-dimensional current image and calculates a body position correction amount so that the position and orientation of the affected part in the three-dimensional current image matches the position and orientation of the affected part in the three-dimensional reference image And comprising
The verification processing unit includes a primary verification unit that performs primary pattern matching on the three-dimensional current image from the three-dimensional reference image;
From the predetermined template region generated based on the result of the primary pattern matching from one of the three-dimensional reference image or the three-dimensional current image, the three-dimensional reference image different from the generation source of the predetermined template region or A secondary matching unit that performs secondary pattern matching on a predetermined search target region generated based on the result of the primary pattern matching from the other of the three-dimensional current image;
A reference template region generation unit that generates a reference image template region of a three-dimensional region from the three-dimensional reference image based on diseased part information prepared in the three-dimensional reference image;
The position and orientation converter for converting the position and orientation of the three-dimensional image, the possess,
The position / orientation conversion unit generates a position / orientation conversion template region obtained by converting the position / orientation of the reference image template region into a predetermined position / orientation;
The primary collation unit generates a primary extraction current image region that is the search target region so as to include a region having a highest correlation value with the reference image template region from the three-dimensional current image,
The secondary verification unit performs pattern matching on the primary extracted current image area from the position / orientation conversion template area, which is the predetermined template area, in the secondary pattern matching. Verification device. A three-dimensional image input unit for reading a three-dimensional reference image captured during a radiotherapy treatment plan and a three-dimensional current image captured during treatment;
A collation processing unit that collates the three-dimensional reference image with the three-dimensional current image and calculates a body position correction amount so that the position and orientation of the affected part in the three-dimensional current image matches the position and orientation of the affected part in the three-dimensional reference image When,
A human body database input unit for acquiring a human body database from the database device;
An average template region generating unit that generates an average template region from an organ portion corresponding to an affected area of a patient in the human body database,
The verification processing unit includes a primary verification unit that performs primary pattern matching on the three-dimensional current image from the three-dimensional reference image;
From the predetermined template region generated based on the result of the primary pattern matching from one of the three-dimensional reference image or the three-dimensional current image, the three-dimensional reference image different from the generation source of the predetermined template region or A secondary matching unit that performs secondary pattern matching on a predetermined search target region generated based on the result of the primary pattern matching from the other of the three-dimensional current image;
A reference template region generating unit that performs pattern matching on the three-dimensional reference image from the average template region, and generates a reference image template region of the three-dimensional region from the three-dimensional reference image based on the result of the pattern matching;
The position and orientation converter for converting the position and orientation of the three-dimensional image, the possess,
The position / orientation conversion unit generates a position / orientation conversion template region obtained by converting the position / orientation of the reference image template region into a predetermined position / orientation;
The primary collation unit generates a primary extraction current image region that is the search target region so as to include a region having a highest correlation value with the reference image template region from the three-dimensional current image,
The secondary matching unit, when the secondary pattern matching, you and performing pattern matching with respect to the predetermined said primary extraction current image area from the position and orientation transformation template region is a template region images matching device. The secondary verification unit generates a plurality of cross sections parallel to a slice image constituting the primary extraction current image area in the position / orientation conversion template area , and the primary extraction current image area and the plurality of cross sections The image matching apparatus according to claim 8 , wherein pattern matching is performed between them. The image collation device according to any one of claims 8 to 10 ,
A patient positioning apparatus comprising: a treatment table control parameter calculation unit that calculates parameters for controlling each axis of the treatment table based on the posture correction amount calculated by the image collating device.

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