CN117017487B - Spinal column registration method, device, equipment and storage medium - Google Patents
Spinal column registration method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention provides a spine registration method, a spine registration device, spine registration equipment and a storage medium. The device comprises an image segmentation and rough registration point selection module, an image calibration module, a CT-X ray registration module, a rough registration module and a spine registration module, and is used for realizing a spine registration method. Compared with the prior art, the invention establishes the relation between the array coordinate system of the part to be operated and the X-ray image coordinate system through the image calibration module, is not dependent on the parameters of the C-arm machine, can be suitable for any type of C-arm for performing robot operation navigation, and simultaneously, the registration method provided by the invention is based on a single vertebra, thereby avoiding the problem of the change of the posture of a patient during preoperative CT and intraoperative X-ray shooting.
Description
Technical Field
The invention relates to the field of medical image processing, in particular to a spine registration method, a spine registration device, spine registration equipment and a storage medium.
Background
In robot navigation spine minimally invasive surgery, spine registration is the most critical step, and can obtain the conversion relation from a coordinate system planned before surgery (usually a coordinate system of preoperative CT) to a coordinate system of an actual surgical site of a patient in surgery, so as to provide guidance for the path of nail placement navigation. However, many practical factors, such as registration time, operation complexity, operation wound, radiation dose, etc., often need to be considered in the process of the spine registration, so the spine registration is a problem to be solved in the field. With the progress of computer technology and image processing technology, a more advanced mode is to use a computer to assist in surgery, such as C-arm spine surgery auxiliary equipment, and the main principle is to use a surgery navigation system to position a patient part, accurately position the patient part, and avoid errors of doctors depending on experience surgery.
Patent CN 111429491A provides a method and system for registering a three-dimensional image of a spine before operation with a two-dimensional image in operation, which generates DRR images by using a CT before operation, performs vertebral segmentation on X-ray images taken by a C-arm in operation, and finally registers corresponding vertebral bodies before operation and in operation. The method solves the problem of inconsistent overall spinal posture before and during operation by segmenting vertebral bodies and adopting a single-vertebral registration method, but the method can only obtain the conversion relation between a CT coordinate system and an X-ray image coordinate system, but can not obtain the conversion relation between the CT coordinate system and a coordinate system of a part to be operated, and can not be used for performing robot operation navigation.
Disclosure of Invention
The invention aims to solve the defects of the prior art scheme described in the background art, and provides a spine registration method, a device, equipment and a storage medium, which can simply, quickly and accurately acquire a coordinate conversion relation. The invention uses the C-arm machine to shoot X-ray images, has the advantages of low radiation dose, simple operation and short time consumption, and establishes the relation between the array coordinate system of the part to be operated and the X-ray image coordinate system through the image calibration module without depending on the parameters of the C-arm machine, thereby being suitable for C-type arms of any manufacturer and any model.
The invention is realized by the following technical scheme: in a first aspect, the present invention provides a spinal registration method comprising the steps of:
s101, selecting image segmentation and rough registration points: dividing a preoperative CT image to obtain a three-dimensional model of the vertebra, and selecting rough registration points on the three-dimensional model;
s102, calibrating an image: calibrating an X-ray film shot by a C-arm by using an image calibration tool to obtain a projection matrix from the array coordinate of a part to be operated to the image coordinate of the X-ray film;
wherein, the image calibration tool is provided with at least 6 non-coplanar calibration points which are not penetrated by X rays and an optical tracking array, and the optical tracking array can be identified and positioned by a binocular camera;
s103, CT-X ray registration: 2D-3D registration is carried out on the preoperative CT image and the X-ray film image of the part to be operated, which is shot in the operation, and the coordinate of the pre-operative coarse registration point on the X-ray film image is obtained by utilizing the registration result and the DRR algorithm;
s104, coarse registration: three-dimensional reconstruction is carried out on the coarse registration points on the X-ray film image of the part to be operated based on a triangulation method, and coarse registration is carried out on the coarse registration points and the coarse registration points selected before operation;
s105, fine registration: downsampling is carried out on a spine model obtained by preoperative segmentation, the downsampled points are projected onto an X-ray film image, then three-dimensional reconstruction is carried out by utilizing a projection matrix, a spine point cloud under an array coordinate system of a part to be operated is obtained, and registration is carried out on the spine point cloud under the coordinate system of the part to be operated and the spine model obtained by preoperative segmentation through an ICP point cloud registration algorithm, so that a final spine registration result is obtained.
Further, at least 3 coarse registration points are selected on the three-dimensional model in S101.
Further, in S102, the image calibration is performed by using an image calibration tool to calibrate an X-ray film shot by a C-arm, and a projection matrix from an array coordinate of a part to be operated to an image coordinate of the X-ray film is obtained, and the method includes the following steps:
using a C-arm shooting image calibration tool to obtain two X-ray films under different angles;
identifying the calibration points of the image calibration tools on the two X-ray film images by an image processing method, and respectively obtaining the coordinates of the calibration points of the image calibration tools on the two X-ray film images;
installing an array at a part to be operated, and establishing an array coordinate system of the part to be operated; wherein the array coordinate system of the to-be-operated part is determined by the positions of three reflective patches on the array: determining a central point of the array of the part to be operated according to the positions of the three reflecting circle centers, taking the central point as an origin of a coordinate system of the array of the part to be operated, wherein a plane where the three reflecting circle centers are positioned is an XOY plane, an outward axis perpendicular to the plane is a Z axis, an extension line of a connecting line from the origin to any one reflecting circle center is a Y axis, and determining the direction of the X axis through cross multiplication;
The binocular camera identifies an array of the to-be-operated part and an optical tracking array on the image calibration tool, obtains the position conversion relation between the array of the to-be-operated part and the optical tracking array on the image calibration tool, and calculates the coordinates of the calibration point on the image calibration tool under the array coordinate system of the to-be-operated part;
according to the obtained coordinates of the calibration points on the image calibration tool on the two X-ray film images and the coordinates of a group of calibration points under the array coordinate system of the to-be-operated position, respectively obtaining the projection matrixes of the array coordinate of the to-be-operated position of the calibration points to the two groups of X-ray film image coordinates through a direct linear transformation method, namely, the projection matrixes between the array coordinate system of the to-be-operated position and the X-ray film image coordinate systems under two different angles, respectively marking as P 1 ，P 2 ；
The coordinate of the calibration point on the image calibration tool on the X-ray film image is a 2D coordinate, and the coordinate of the calibration point on the image calibration tool on the X-ray film image is a 3D coordinate under the array coordinate system of the part to be operated.
Further, the image processing method adopts one of threshold segmentation or connected domain analysis.
Further, in S103, the CT-X-ray registration performs 2D-3D registration on the pre-operative CT image and the X-ray image of the portion to be operated captured during the operation, and obtains the coordinates of the pre-operative coarse registration point on the X-ray image by using the registration result and the DRR algorithm, including the following steps:
Shooting X-ray films of a part to be operated by using a C-type arm;
2D-3D registration is carried out on the preoperative CT image and the X-ray image of the part to be operated in the operation to obtain Rx and R x ，R y ，R z ，t x ，t y ，t z 6 parameters, wherein R x ，R y ，R z ，t x ，t y ，t z Representing the rotational component and the translational component of the preoperative CT image in the X, Y, Z axial directions of the CT coordinate system respectively;
calculating to obtain the position coordinates of the pre-operation selected rough registration point on the current X-ray film image through a DRR algorithm and a registration result, wherein the DRR algorithm is a digital reconstructed radiographic image;
taking X-ray film of the part to be operated at another angle, keeping the two shooting angles consistent with the shooting of the image calibration tool in the image calibration, repeating the steps to obtain the coordinates of the rough registration point on the X-ray film images of the two parts to be operated respectively, namely, the coordinates of the rough registration point under the X-ray film image coordinate systems under the two different angles are respectively marked as C 1 ，C 2 。
Further, the 2D-3D registration of the preoperative CT image and the X-ray film image of the part to be operated in the operation adopts automatic registration, and the method comprises the following steps:
generating a DRR image of the preoperative CT image, wherein the DRR image is a digitally reconstructed radiological image;
iterative optimization of R using an optimization algorithm with the similarity of the generated DRR image and the X-ray film image of the part to be operated taken during operation as an objective function x ，R y ，R z ，t x ，t y ，t z The 6 parameters enable the registration to be considered successful when the similarity reaches a certain set threshold value;
the similarity function of the DRR image and the X-ray film image of the part to be operated shot in operation adopts one of mutual information or normalized cross correlation, and the optimization algorithm adopted when the 6 parameters are optimized in an iterative mode is one of a Powell algorithm or a Nelder-Mead algorithm.
Further, the rough registration in S104 performs three-dimensional reconstruction of the rough registration points on the X-ray image of the to-be-operated site based on the triangulation method, and performs rough registration with the rough registration points selected before the operation, including the following steps:
according to the projection matrix P between the array coordinate system of the part to be operated and the X-ray film image coordinate system under two different angles 1 ，P 2 And coordinates C of the coarse registration point in the X-ray image coordinate system at two different angles 1 ，C 2 Three-dimensional reconstruction is carried out on the coarse registration points on the X-ray film images of two to-be-operated positions based on a triangulation method, so as to obtain the coordinates of the coarse registration points under the array coordinate system of the to-be-operated positions, and the coordinates are marked as C Patient ；
Marking the sitting of the rough registration point under the CT coordinate system as C CT Obtaining the result of coarse registration according to the point-to-point matching calculation, namely, converting the CT coordinate system into the array coordinate system of the to-be-operated part, and marking the matrix as T CT2Patient 。
Further, the point pair matching employed in calculating the result of the coarse registration employs a least squares method.
Further, in S105, the fine registration is performed, a spine model obtained by pre-operation segmentation is downsampled, points after downsampling are projected onto an X-ray film image, a projection matrix is used for three-dimensional reconstruction, a spine point cloud under a coordinate system of an array of a part to be operated is obtained, and registration is performed with the spine model obtained by pre-operation segmentation through an ICP point cloud registration algorithm, so that a final spine registration result is obtained, and the method comprises the following steps:
downsampling the vertexes of the spine model obtained by preoperative segmentation;
projecting the downsampled point onto X-ray film images at two different angles to obtain coordinates of the downsampled point under the X-ray film image coordinate system at two different angles, and marking the coordinates as F 1 、F 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the two projection angles are consistent with the shooting of an image calibration tool in the image calibration;
three-dimensional reconstruction is carried out on the down-sampled points on the two X-ray film images based on a triangulation method, and a projection matrix P between the X-ray film image coordinate systems under two different angles is obtained according to the array coordinate system of the part to be operated 1 ，P 2 Obtaining the coordinates of the down-sampled points in the array coordinate system of the part to be operated, and marking the coordinates as F Patient ；
Transformation matrix T from CT coordinate system to-be-operated position array coordinate system by using ICP point cloud registration algorithm CT2Patient As an initial pose, the position and orientation of the human body,for F Patient Performing point cloud registration with the spine model;
constantly optimize T CT2Patient Obtaining the final registration result, namely the conversion relation T of the CT coordinate system to the array coordinate system of the part to be operated CT2Patient 。
In a second aspect, the present invention provides a spinal registration device, the device comprising: the system comprises an image segmentation and rough registration point selection module, an image calibration module, a CT-X ray registration module and a spine registration module, wherein the spine registration module comprises a rough registration module and a fine registration module.
The image segmentation and rough registration point selection module is used for segmenting the preoperative CT image to obtain a three-dimensional model of the vertebra, and selecting rough registration points on the three-dimensional model;
the image calibration module is used for calibrating the X-ray film shot by the C-arm by using an image calibration tool, and acquiring a projection matrix from the array coordinate of the part to be operated to the image coordinate of the X-ray film;
the CT-X-ray registration module is used for carrying out 2D-3D registration on a preoperative CT image and an X-ray image of a part to be operated, which is shot in an operation, and acquiring the coordinates of a pre-operation selected rough registration point on the X-ray image by utilizing a registration result and a DRR algorithm;
The coarse registration module is used for carrying out three-dimensional reconstruction on the coarse registration points on the X-ray film image of the part to be operated on the basis of a triangulation method and carrying out coarse registration on the coarse registration points and the coarse registration points selected before operation;
the fine registration module is used for downsampling the spine model obtained by the preoperative segmentation, projecting the downsampled points onto an X-ray film image, carrying out three-dimensional reconstruction by utilizing a projection matrix to obtain a spine point cloud under an array coordinate system of a part to be operated, and registering the spine point cloud with the spine model obtained by the preoperative segmentation by an ICP point cloud registration algorithm to obtain a final spine registration result.
In a third aspect, the present invention provides a spinal registration apparatus, the apparatus comprising: the system comprises a processor, a memory and computer program instructions stored in the memory and executable on the processor, wherein the processor is used for executing the computer program instructions stored in the memory to realize the spine registration method.
In a fourth aspect, the present invention provides a spinal registration computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement the spinal registration method described above.
The invention provides a spine registration method, a device, equipment and a storage medium, which have the following advantages compared with the prior art:
the relation between the array coordinate system of the part to be operated and the X-ray film image coordinate system is established through the image calibration module, and the parameter of the C-arm machine is not dependent, so that the C-arm machine can be adapted to C-arms of any manufacturer and any model;
performing three-dimensional reconstruction on the matching points on the X-rays at two angles, and performing point cloud registration to obtain a conversion relation from a CT coordinate system to an array coordinate system of a part to be operated, wherein the conversion relation can be used for performing robot operation navigation;
the C-arm machine is used for shooting X-ray images in the operation, and compared with a scheme of shooting CT in the operation, the method has the advantages of low radiation dose, simplicity in operation and short time consumption;
the registration is carried out based on a single vertebra, so that the problem that the posture of a patient changes during preoperative CT and intraoperative X-ray shooting is avoided, meanwhile, as the vertebra is of a bone structure, deformation can not occur like soft tissues, the registration can be carried out through rigid transformation, and the problem caused by deformation is avoided.
Drawings
Features, advantages, and technical effects of exemplary embodiments of the present invention will be described below with reference to the accompanying drawings.
FIG. 1 is a schematic flow chart of a spinal registration method provided by an embodiment of the present invention;
FIG. 2 is a schematic view of image segmentation and coarse registration point selection according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of establishing an array coordinate system of a part to be operated according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of acquiring coordinates of a pre-operatively selected rough registration point on an X-ray film image using a registration result and a DRR algorithm according to an embodiment of the present invention;
FIG. 5 is a schematic representation of spinal registration provided by an embodiment of the present invention;
FIG. 6 is a schematic illustration of a spinal registration device provided in an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a computing device according to an embodiment of the present invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present disclosure will be described in detail below, and in order to make the objects, technical solutions and advantages of the present disclosure more apparent, the present disclosure will be described in further detail below with reference to the accompanying drawings and the detailed embodiments. It should be understood that the specific embodiments described herein are intended to be illustrative of the present disclosure and not limiting. It will be apparent to one skilled in the art that the present disclosure may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present disclosure by showing examples of the present disclosure.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
For a better understanding of the present invention, embodiments of the present invention are described in detail below with reference to the drawings.
Fig. 1 is a schematic flow chart of a spinal registration method according to an embodiment of the present invention.
As shown in fig. 1, the present invention provides a spinal registration method comprising the steps of:
S101, selecting image segmentation and rough registration points: dividing a preoperative CT image, obtaining a three-dimensional model of the vertebra as shown in fig. 2, and selecting rough registration points on the three-dimensional model;
s102, calibrating an image: calibrating an X-ray film shot by a C-arm by using an image calibration tool to obtain a projection matrix from the array coordinate of a part to be operated to the image coordinate of the X-ray film;
wherein, the image calibration tool is provided with at least 6 non-coplanar calibration points which are not penetrated by X rays and an optical tracking array, and the optical tracking array can be identified and positioned by a binocular camera;
s103, CT-X ray registration: 2D-3D registration is carried out on the preoperative CT image and the X-ray film image of the part to be operated, which is shot in the operation, and the coordinate of the pre-operative coarse registration point on the X-ray film image is obtained by utilizing the registration result and the DRR algorithm;
s104, coarse registration: three-dimensional reconstruction is carried out on the coarse registration points on the X-ray film image of the part to be operated based on a triangulation method, and coarse registration is carried out on the coarse registration points and the coarse registration points selected before operation;
s105, fine registration: downsampling is carried out on a spine model obtained by preoperative segmentation, the downsampled points are projected onto an X-ray film image, then three-dimensional reconstruction is carried out by utilizing a projection matrix, a spine point cloud under an array coordinate system of a part to be operated is obtained, and registration is carried out on the spine point cloud under the coordinate system of the part to be operated and the spine model obtained by preoperative segmentation through an ICP point cloud registration algorithm, so that a final spine registration result is obtained.
As an alternative embodiment, at least 3 coarse registration points are selected on the three-dimensional model in S101.
As an optional implementation manner, the image calibration in S102, the calibration of the X-ray film shot by the C-arm by using an image calibration tool, and the acquisition of the projection matrix from the array coordinates of the part to be operated to the image coordinates of the X-ray film, includes the following steps:
using a C-arm shooting image calibration tool to obtain two X-ray films under different angles;
identifying the calibration points of the image calibration tools on the two X-ray film images by an image processing method, and respectively obtaining the coordinates of the calibration points of the image calibration tools on the two X-ray film images;
installing an array at a part to be operated, and establishing an array coordinate system of the part to be operated; as shown in fig. 3, the array coordinate system of the surgical site is determined by the positions of three reflective patches on the array: determining a central point of the array of the part to be operated according to the positions of the three reflecting circle centers, taking the central point as an origin of a coordinate system of the array of the part to be operated, wherein a plane where the three reflecting circle centers are positioned is an XOY plane, an outward axis perpendicular to the plane is a Z axis, an extension line of a connecting line from the origin to any one reflecting circle center is a Y axis, and determining the direction of the X axis through cross multiplication;
The binocular camera identifies an array of the to-be-operated part and an optical tracking array on the image calibration tool, obtains the position conversion relation between the array of the to-be-operated part and the optical tracking array on the image calibration tool, and calculates the coordinates of the calibration point on the image calibration tool under the array coordinate system of the to-be-operated part;
according to the obtained coordinates of the calibration points on the image calibration tool on the two X-ray film images and the coordinates of a group of calibration points under the array coordinate system of the to-be-operated position, respectively obtaining the projection matrixes of the array coordinate of the to-be-operated position of the calibration points to the two groups of X-ray film image coordinates through a direct linear transformation method, namely, the projection matrixes between the array coordinate system of the to-be-operated position and the X-ray film image coordinate systems under two different angles, respectively marking as P 1 ，P 2 ；
The coordinate of the calibration point on the image calibration tool on the X-ray film image is a 2D coordinate, and the coordinate of the calibration point on the image calibration tool on the X-ray film image is a 3D coordinate under the array coordinate system of the part to be operated.
As an alternative embodiment, the image processing method employs one of threshold segmentation or connected domain analysis.
As an alternative embodiment, the image processing method may also use other methods that can produce the same or similar effects, such as edge detection, etc.
As an optional implementation manner, the CT-X-ray registration in S103 performs 2D-3D registration on a pre-operative CT image and an X-ray image of a portion to be operated captured during an operation, and obtains coordinates of a pre-operative coarse registration point on the X-ray image by using a registration result and a DRR algorithm, where the method includes the following steps:
shooting X-ray films of a part to be operated by using a C-type arm;
2D-3D registration is carried out on the preoperative CT image and the X-ray image of the part to be operated in the operation to obtain R x ，R y ，R z ，t x ，t y ，t z 6 parameters, wherein R x ，R y ，R z ，t x ，t y ，t z Representing the rotational component and the translational component of the preoperative CT image in the X, Y, Z axial directions of the CT coordinate system respectively;
through a DRR algorithm and a registration result, as shown in fig. 4, calculating to obtain the position coordinates of the pre-operation selected rough registration point on the current X-ray film image, wherein the DRR algorithm is a digital reconstructed radiological image;
taking X-ray film of the part to be operated at another angle, keeping the two shooting angles consistent with the shooting of the image calibration tool in the image calibration, repeating the steps to obtain the coordinates of the rough registration point on the X-ray film images of the two parts to be operated respectively, namely, the coordinates of the rough registration point under the X-ray film image coordinate systems under the two different angles are respectively marked as C 1 ，C 2 。
As an alternative embodiment, the 2D-3D registration of the preoperative CT image and the X-ray image of the surgical site in the operation adopts automatic registration, and includes the following steps:
generating a DRR image of the preoperative CT image, wherein the DRR image is a digitally reconstructed radiological image;
iterative optimization of R using an optimization algorithm with the similarity of the generated DRR image and the X-ray film image of the part to be operated taken during operation as an objective function x ，R y ，R z ，t x ，t y ，t z These 6 parametersCounting, namely considering that the registration is successful when the similarity reaches a certain set threshold value;
the similarity function of the DRR image and the X-ray film image of the part to be operated shot in operation adopts one of mutual information or normalized cross correlation, and the optimization algorithm adopted when the 6 parameters are optimized in an iterative mode is one of a Powell algorithm or a Nelder-Mead algorithm.
As an alternative embodiment, the similarity function between the DRR image and the intraoperative X-ray image of the site to be operated on may also use other objective functions, such as corr2 function, etc.
As an alternative embodiment, other optimization algorithms, such as gradient descent, may be used to iteratively optimize the 6 parameters.
As an alternative embodiment, the 2D-3D registration of the preoperative CT image and the X-ray image of the site to be operated in the operation adopts manual registration, and includes the following steps:
By manual change of R by user x ，R y ，R z ，t x ，t y ，t z The values of the 6 parameters are used for generating a DRR image based on the 6 parameters by using a DRR generation algorithm by utilizing a preoperative CT image, then the DRR image is compared with an X-ray film image shot in the operation in similarity, and when a certain set threshold value is reached, the registration is considered to be successful.
As an optional implementation manner, the coarse registration in S104 performs three-dimensional reconstruction based on a triangulation method on the coarse registration points on the X-ray image of the to-be-operated site, and performs coarse registration with the coarse registration points selected before operation, including the following steps:
according to the projection matrix P between the array coordinate system of the part to be operated and the X-ray film image coordinate system under two different angles 1 ，P 2 And coordinates C of the coarse registration point in the X-ray image coordinate system at two different angles 1 ，C 2 Three-dimensional reconstruction is carried out on the coarse registration points on the X-ray film images of two to-be-operated positions based on a triangulation method, so as to obtain the coordinates of the coarse registration points under the array coordinate system of the to-be-operated positions, and the coordinates are marked as C Patient ；
Marking the sitting of the rough registration point under the CT coordinate system as C CT Obtaining the result of coarse registration according to the point-to-point matching calculation, namely, converting the CT coordinate system into the array coordinate system of the to-be-operated part, and marking the matrix as T CT2Patient 。
As an alternative embodiment, the point pair matching employed in computing the result of the coarse registration employs a least squares method.
As an optional implementation manner, the fine registration in S105 performs downsampling on a spine model obtained by pre-operation segmentation, projects the downsampled points onto an X-ray film image, performs three-dimensional reconstruction by using a projection matrix to obtain a spine point cloud under a coordinate system of an array of a part to be operated, and performs registration with the spine model obtained by pre-operation segmentation by using an ICP point cloud registration algorithm to obtain a final spine registration result, including the following steps:
as shown in fig. 5, the vertexes of the spine model obtained by the preoperative segmentation are downsampled;
projecting the downsampled point onto X-ray film images at two different angles to obtain coordinates of the downsampled point under the X-ray film image coordinate system at two different angles, and marking the coordinates as F 1 、F 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the two projection angles are consistent with the shooting of an image calibration tool in the image calibration;
three-dimensional reconstruction is carried out on the down-sampled points on the two X-ray film images based on a triangulation method, and a projection matrix P between the X-ray film image coordinate systems under two different angles is obtained according to the array coordinate system of the part to be operated 1 ，P 2 Obtaining the coordinates of the down-sampled points in the array coordinate system of the part to be operated, and marking the coordinates as F Patient ；
Transformation matrix T from CT coordinate system to-be-operated position array coordinate system by using ICP point cloud registration algorithm CT2Patient As an initial pose, for F Patient Performing point cloud registration with the spine model;
constantly optimize T CT2Patient Obtaining the final registration result, namely the conversion relation T of the CT coordinate system to the array coordinate system of the part to be operated CT2Patient 。
As shown in fig. 6, the present invention also provides a spinal registration device, the device comprising: the image segmentation and rough registration point selection module 601, the image calibration module 602, the CT-X ray registration module 603 and the spine registration module, wherein the spine registration module comprises a rough registration module 604 and a fine registration module 605.
The image segmentation and rough registration point selection module 601 is used for segmenting the preoperative CT image to obtain a three-dimensional model of the vertebra, and selecting rough registration points on the three-dimensional model;
the image calibration module 602 is used for calibrating an X-ray film shot by the C-arm by using an image calibration tool, and acquiring a projection matrix from the array coordinate of the part to be operated to the image coordinate of the X-ray film;
the CT-X-ray registration module 603 is configured to perform 2D-3D registration on a pre-operative CT image and an X-ray image of a portion to be operated captured during an operation, and acquire coordinates of a pre-operative coarse registration point on the X-ray image by using a registration result and a DRR algorithm;
The coarse registration module 604 performs three-dimensional reconstruction on the coarse registration points on the X-ray film image of the part to be operated based on a triangulation method, and performs coarse registration with the coarse registration points selected before operation;
the fine registration module 605 is configured to downsample the spine model obtained by the pre-operation segmentation, project the downsampled points onto the X-ray film image, and perform three-dimensional reconstruction by using the projection matrix to obtain a spine point cloud under the array coordinate system of the part to be operated, and register the spine point cloud with the spine model obtained by the pre-operation segmentation by using the ICP point cloud registration algorithm to obtain a final spine registration result.
The modules/units in the apparatus shown in fig. 6 have functions of implementing the steps in fig. 1, and achieve corresponding technical effects, which are not described herein for brevity.
As shown in fig. 7, the present invention also provides a spinal registration apparatus, the apparatus comprising: a processor 701, a memory 702 and computer program instructions stored in the memory 702 and executable on the processor, wherein the processor 701 is configured to execute the computer program instructions stored in the memory 702 to implement the above-described spine registration method.
In particular, the processor 701 described above may include a central processing unit (Central Processing Unit, CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or may be configured as one or more integrated circuits implementing the present invention.
Memory 702 may include mass storage for data or instructions. By way of example, and not limitation, the memory may comprise a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, magnetic tape, or universal serial bus (Universal Serial Bus, USB) Drive, or a combination of two or more of the foregoing.
In one example, the memory 702 may include removable or non-removable (or fixed) media, or the memory is a non-volatile solid state memory. The memory may be internal or external to the integrated gateway disaster recovery device.
In one example, memory 702 may be Read Only Memory (ROM). In one example, the ROM may be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.
In one example, memory 702 may include Read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical/tangible memory storage devices. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software comprising computer-executable instructions and when the software is executed (e.g., by one or more processors) it is operable to perform the operations described with reference to methods in accordance with aspects of the present disclosure.
The processor 701 reads and executes the computer program instructions stored in the memory 702 to implement the method/steps in the embodiment shown in fig. 1, and achieve the corresponding technical effects, which are not described herein for brevity.
In one embodiment, the computing device may also include a communication interface 703 and a bus 704. As shown in fig. 7, the processor 701, the memory 702, and the communication interface 703 are connected by a bus 704 and perform communication with each other.
Communication interface 703 is primarily used to enable communication between modules, devices, units and/or apparatuses in the present invention.
Bus 704 includes hardware, software, or both that couple the components of the online data flow billing device to each other. By way of example, and not limitation, the buses may include an accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics Bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) Bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (Industry Standard Architecture, ISA) Bus, an infiniband interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a micro channel architecture (MCa) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a video electronics standards association local (VLB) Bus, or other suitable Bus, or a combination of two or more of the above. The bus may include one or more buses, where appropriate. Although a particular bus is described and illustrated, this disclosure contemplates any suitable bus or interconnect.
In addition, in combination with the spine registration method in the above embodiment, the present invention also provides a computer storage medium for implementation. The computer storage medium has stored thereon computer program instructions which, when executed by a processor, implement the spine registration method described above.
The computer storage media provided by the embodiments of the present invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The invention provides a spine registration method, a device, equipment and a storage medium, which have the following advantages compared with the prior art:
the relation between the array coordinate system of the part to be operated and the X-ray film image coordinate system is established through the image calibration module, and the parameter of the C-arm machine is not dependent, so that the C-arm machine can be adapted to C-arms of any manufacturer and any model;
performing three-dimensional reconstruction on the matching points on the X-rays at two angles, and performing point cloud registration to obtain a conversion relation from a CT coordinate system to an array coordinate system of a part to be operated, wherein the conversion relation can be used for performing robot operation navigation;
the C-arm machine is used for shooting X-ray images in the operation, and compared with a scheme of shooting CT in the operation, the method has the advantages of low radiation dose, simplicity in operation and short time consumption;
the registration is carried out based on a single vertebra, so that the problem that the posture of a patient changes during preoperative CT and intraoperative X-ray shooting is avoided, meanwhile, as the vertebra is of a bone structure, deformation can not occur like soft tissues, the registration can be carried out through rigid transformation, and the problem caused by deformation is avoided.
It should be clear that the present disclosure is not limited to the particular arrangements and processes described above and illustrated in the drawings. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present disclosure are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps, after appreciating the spirit of the present disclosure.
The functional blocks shown in the above-described structural block diagrams may be implemented in hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an application specific integrated circuit (Application SpecificIntegrated Circuit, ASIC), suitable firmware, a plug-in, a function card, or the like. When implemented in software, the elements of the present disclosure are the programs or code segments used to perform the required tasks. The computer program code for carrying out operations of the present invention may be written by those skilled in the art in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. Additionally, the program or code segments may be stored in a machine readable medium or transmitted over transmission media or communication links by data signals carried in carrier waves. A machine-readable medium may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuitry, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio Frequency (RF) links, and the like.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to being, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware which performs the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In the foregoing, only the specific embodiments of the present disclosure are described, and it will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the systems, modules and units described above may refer to the corresponding processes in the foregoing method embodiments, which are not repeated herein. It should be understood that the scope of the present disclosure is not limited thereto, and any equivalent modifications or substitutions can be easily made by those skilled in the art within the technical scope of the present disclosure, and these modifications or substitutions should be included in the scope of the present disclosure.
Claims (8)
1. A method of spinal registration comprising the steps of:
s101, selecting image segmentation and rough registration points: dividing a preoperative CT image to obtain a three-dimensional model of the vertebra, and selecting rough registration points on the three-dimensional model;
s102, calibrating an image: calibrating an X-ray film shot by a C-arm by using an image calibration tool to obtain a projection matrix from the array coordinate of a part to be operated to the image coordinate of the X-ray film; the image calibration tool is provided with at least 6 non-coplanar calibration points which are not penetrated by X rays and an optical tracking array, wherein the optical tracking array can be identified and positioned by a binocular camera, and the method specifically comprises the following steps of:
using a C-arm shooting image calibration tool to obtain two X-ray films under different angles;
identifying the calibration points of the image calibration tools on the two X-ray film images by an image processing method, and respectively obtaining the coordinates of the calibration points of the image calibration tools on the two X-ray film images;
installing an array at a part to be operated, and establishing an array coordinate system of the part to be operated; wherein the array coordinate system of the to-be-operated part is determined by the positions of three reflective patches on the array: determining a central point of the array of the part to be operated according to the positions of the three reflecting circle centers, taking the central point as an origin of a coordinate system of the array of the part to be operated, wherein a plane where the three reflecting circle centers are positioned is an XOY plane, an outward axis perpendicular to the plane is a Z axis, an extension line of a connecting line from the origin to any one reflecting circle center is a Y axis, and determining the direction of the X axis through cross multiplication;
The binocular camera identifies an array of the to-be-operated part and an optical tracking array on the image calibration tool, obtains the position conversion relation between the array of the to-be-operated part and the optical tracking array on the image calibration tool, and calculates the coordinates of the calibration point on the image calibration tool under the array coordinate system of the to-be-operated part;
according to the obtained coordinates of the calibration points on the image calibration tool on the two X-ray film images and the coordinates of a group of calibration points under the array coordinate system of the to-be-operated position, respectively obtaining the projection matrixes of the array coordinate of the to-be-operated position of the calibration points to the two groups of X-ray film image coordinates through a direct linear transformation method, namely, the projection matrixes between the array coordinate system of the to-be-operated position and the X-ray film image coordinate systems under two different angles, respectively marking as P 1 ，P 2 ；
The coordinate of the calibration point on the image calibration tool on the X-ray film image is a 2D coordinate, and the coordinate of the calibration point on the image calibration tool on the X-ray film image is a 3D coordinate under the array coordinate system of the part to be operated;
s103, CT-X ray registration: 2D-3D registration is carried out on the preoperative CT image and the X-ray film image of the part to be operated, which is shot in the operation, and the coordinate of the pre-operative coarse registration point on the X-ray film image is obtained by utilizing the registration result and the DRR algorithm, which comprises the following steps:
Shooting X-ray films of a part to be operated by using a C-type arm;
2D-3D registration is carried out on the preoperative CT image and the X-ray image of the part to be operated in the operation to obtain R x ，R y ，R z ，t x ，t y ，t z 6 parameters, wherein R x ，R y ，R z ，t x ，t y ，t z Representing the rotational component and the translational component of the preoperative CT image in the X, Y, Z axial directions of the CT coordinate system respectively;
calculating to obtain the position coordinates of the pre-operation selected rough registration point on the current X-ray film image through a DRR algorithm and a registration result, wherein the DRR algorithm is a digital reconstructed radiographic image;
taking X-ray film of the part to be operated at another angle, keeping the two shooting angles consistent with the shooting of the image calibration tool in the image calibration, repeating the steps to obtain the coordinates of the rough registration point on the X-ray film images of the two parts to be operated respectively, namely, the coordinates of the rough registration point under the X-ray film image coordinate systems under the two different angles are respectively marked as C 1 ，C 2 ；
S104, coarse registration: three-dimensional reconstruction is carried out on the rough registration points on the X-ray film image of the part to be operated based on a triangulation method, and rough registration is carried out on the rough registration points selected before operation, and the method specifically comprises the following steps:
according to the projection matrix P between the array coordinate system of the part to be operated and the X-ray film image coordinate system under two different angles 1 ，P 2 And coordinates C of the coarse registration point in the X-ray image coordinate system at two different angles 1 ，C 2 Three-dimensional reconstruction is carried out on the coarse registration points on the X-ray film images of two to-be-operated positions based on a triangulation method, so as to obtain the coordinates of the coarse registration points under the array coordinate system of the to-be-operated positions, and the coordinates are marked as C Patient ；
Marking the sitting of the rough registration point under the CT coordinate system as C CT Obtaining the result of coarse registration according to the point-to-point matching calculation, namely, converting the CT coordinate system into the array coordinate system of the to-be-operated part, and marking the matrix as T CT2Patient ；
S105, fine registration: downsampling is carried out on a spine model obtained by segmentation before operation, the downsampled points are projected onto an X-ray film image, then three-dimensional reconstruction is carried out by utilizing a projection matrix, a spine point cloud under an array coordinate system of a part to be operated is obtained, and registration is carried out with the spine model obtained by segmentation before operation through an ICP point cloud registration algorithm, so that a final spine registration result is obtained, and the method specifically comprises the following steps:
downsampling the vertexes of the spine model obtained by preoperative segmentation;
projecting the downsampled point onto X-ray film images at two different angles to obtain coordinates of the downsampled point under the X-ray film image coordinate system at two different angles, and marking the coordinates as F 1 、F 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the two projection angles are consistent with the shooting of an image calibration tool in the image calibration;
three-dimensional reconstruction is carried out on the down-sampled points on the two X-ray film images based on a triangulation method, and a projection matrix P between the X-ray film image coordinate systems under two different angles is obtained according to the array coordinate system of the part to be operated 1 ，P 2 Obtaining the coordinates of the down-sampled points in the array coordinate system of the part to be operated, and marking the coordinates as F Patient ；
Transformation matrix T from CT coordinate system to-be-operated position array coordinate system by using ICP point cloud registration algorithm CT2Patient As an initial pose, for F Patient Performing point cloud registration with the spine model;
constantly optimize T CT2Patient Obtaining the final registration result, namely the conversion relation T of the CT coordinate system to the array coordinate system of the part to be operated CT2Patient 。
2. A method of spinal registration according to claim 1 wherein at least 3 coarse registration points are selected on the three-dimensional model in S101.
3. A method of spinal registration as recited in claim 1 in which the image processing method employs one of thresholding or connected domain analysis.
4. The method of claim 1, wherein the 2D-3D registration of the pre-operative CT image with the X-ray image of the site to be operated on in the operation employs automatic registration, comprising the steps of:
Generating a DRR image of the preoperative CT image, wherein the DRR image is a digitally reconstructed radiological image;
iterative optimization of R using an optimization algorithm with the similarity of the generated DRR image and the X-ray film image of the part to be operated taken during operation as an objective function x ，R y ，R z ，t x ，t y ，t z The 6 parameters enable the registration to be considered successful when the similarity reaches a certain set threshold value;
the similarity function of the DRR image and the X-ray film image of the part to be operated shot in operation adopts one of mutual information or normalized cross correlation, and the optimization algorithm adopted when the 6 parameters are optimized in an iterative mode is one of a Powell algorithm or a Nelder-Mead algorithm.
5. A method of spinal registration as recited in claim 1 in which the point-to-point matching used in computing the result of the coarse registration uses a least squares method.
6. A spinal registration device, comprising:
the image segmentation and rough registration point selection module is used for segmenting the preoperative CT image to obtain a three-dimensional model of the vertebra, and selecting rough registration points on the three-dimensional model;
the image calibration module is used for calibrating the X-ray film shot by the C-arm by using an image calibration tool, and acquiring a projection matrix from the array coordinate of the part to be operated to the image coordinate of the X-ray film; the image calibration tool is provided with at least 6 non-coplanar calibration points which are not penetrated by X rays and an optical tracking array, wherein the optical tracking array can be identified and positioned by a binocular camera, and the method specifically comprises the following steps of:
Using a C-arm shooting image calibration tool to obtain two X-ray films under different angles;
identifying the calibration points of the image calibration tools on the two X-ray film images by an image processing method, and respectively obtaining the coordinates of the calibration points of the image calibration tools on the two X-ray film images;
installing an array at a part to be operated, and establishing an array coordinate system of the part to be operated; wherein the array coordinate system of the to-be-operated part is determined by the positions of three reflective patches on the array: determining a central point of the array of the part to be operated according to the positions of the three reflecting circle centers, taking the central point as an origin of a coordinate system of the array of the part to be operated, wherein a plane where the three reflecting circle centers are positioned is an XOY plane, an outward axis perpendicular to the plane is a Z axis, an extension line of a connecting line from the origin to any one reflecting circle center is a Y axis, and determining the direction of the X axis through cross multiplication;
the binocular camera identifies an array of the to-be-operated part and an optical tracking array on the image calibration tool, obtains the position conversion relation between the array of the to-be-operated part and the optical tracking array on the image calibration tool, and calculates the coordinates of the calibration point on the image calibration tool under the array coordinate system of the to-be-operated part;
According to the obtained coordinates of the calibration points on the image calibration tool on the two X-ray film images and the coordinates of a group of calibration points under the array coordinate system of the to-be-operated position, respectively obtaining the projection matrixes of the array coordinate of the to-be-operated position of the calibration points to the two groups of X-ray film image coordinates through a direct linear transformation method, namely, the projection matrixes between the array coordinate system of the to-be-operated position and the X-ray film image coordinate systems under two different angles, respectively marking as P 1 ，P 2 ；
The coordinate of the calibration point on the image calibration tool on the X-ray film image is a 2D coordinate, and the coordinate of the calibration point on the image calibration tool on the X-ray film image is a 3D coordinate under the array coordinate system of the part to be operated;
the CT-X-ray registration module is used for carrying out 2D-3D registration on a preoperative CT image and an X-ray image of a part to be operated, which is shot in an operation, and acquiring the coordinates of a pre-operative selected rough registration point on the X-ray image by utilizing a registration result and a DRR algorithm, and specifically comprises the following steps:
shooting X-ray films of a part to be operated by using a C-type arm;
2D-3D registration is carried out on the preoperative CT image and the X-ray image of the part to be operated in the operation to obtain R x ，R y ，R z ，t x ，t y ，t z 6 parameters, wherein R x ，R y ，R z ，t x ，t y ，t z Representing the rotational component and the translational component of the preoperative CT image in the X, Y, Z axial directions of the CT coordinate system respectively;
Calculating to obtain the position coordinates of the pre-operation selected rough registration point on the current X-ray film image through a DRR algorithm and a registration result, wherein the DRR algorithm is a digital reconstructed radiographic image;
taking X-ray film of the part to be operated at another angle, keeping the two shooting angles consistent with the shooting of the image calibration tool in the image calibration, repeating the steps to obtain the coordinates of the rough registration point on the X-ray film images of the two parts to be operated respectively, namely, the coordinates of the rough registration point under the X-ray film image coordinate systems under the two different angles are respectively marked as C 1 ，C 2 ；
Coarse registration module: three-dimensional reconstruction is carried out on the rough registration points on the X-ray film image of the part to be operated based on a triangulation method, and rough registration is carried out on the rough registration points selected before operation, and the method specifically comprises the following steps:
according to the projection matrix P between the array coordinate system of the part to be operated and the X-ray film image coordinate system under two different angles 1 ，P 2 And coordinates C of the coarse registration point in the X-ray image coordinate system at two different angles 1 ，C 2 Three-dimensional reconstruction is carried out on the coarse registration points on the X-ray film images of two to-be-operated positions based on a triangulation method, so as to obtain the coordinates of the coarse registration points under the array coordinate system of the to-be-operated positions, and the coordinates are marked as C Patient ；
Marking the sitting of the rough registration point under the CT coordinate system as C CT Obtaining the result of coarse registration according to the point-to-point matching calculation, namely, converting the CT coordinate system into the array coordinate system of the to-be-operated part, and marking the matrix as T CT2Patient ；
Fine registration module: the method is used for downsampling a spine model obtained by preoperative segmentation, projecting downsampled points onto an X-ray film image, performing three-dimensional reconstruction by utilizing a projection matrix to obtain a spine point cloud under an array coordinate system of a part to be operated, and registering the spine point cloud with the spine model obtained by preoperative segmentation by an ICP point cloud registration algorithm to obtain a final spine registration result, and specifically comprises the following steps of:
downsampling the vertexes of the spine model obtained by preoperative segmentation;
projecting the downsampled point onto X-ray film images at two different angles to obtain coordinates of the downsampled point under the X-ray film image coordinate system at two different angles, and marking the coordinates as F 1 、F 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein, the two projection angles are consistent with the shooting of an image calibration tool in the image calibration;
three-dimensional reconstruction is carried out on the down-sampled points on the two X-ray film images based on a triangulation method, and a projection matrix P between the X-ray film image coordinate systems under two different angles is obtained according to the array coordinate system of the part to be operated 1 ，P 2 Obtaining the coordinates of the down-sampled points in the array coordinate system of the part to be operated, and marking the coordinates as F Patient ；
Transformation matrix T from CT coordinate system to-be-operated position array coordinate system by using ICP point cloud registration algorithm CT2Patient As an initial pose, for F Patient Performing point cloud registration with the spine model;
constantly optimize T CT2Patient Obtaining the final registration result, namely the conversion relation T of the CT coordinate system to the array coordinate system of the part to be operated CT2Patient 。
7. A spinal registration apparatus, characterized in that,
the apparatus comprises: a processor, a memory, and computer program instructions stored in and executable on the memory, wherein the processor is configured to execute the computer program instructions stored in the memory to implement the spine registration method of any one of claims 1 to 5.
8. A spinal registration computer storage medium, characterized in that,
the computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement the spine registration method of any one of claims 1 to 5.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011144412A1 (en) * | 2010-05-18 | 2011-11-24 | Siemens Aktiengesellschaft | Determining and verifying the coordinate transformation between an x-ray system and a surgery navigation system |
| WO2018075784A1 (en) * | 2016-10-21 | 2018-04-26 | Syverson Benjamin | Methods and systems for setting trajectories and target locations for image guided surgery |
| CN110946654A (en) * | 2019-12-23 | 2020-04-03 | 中国科学院合肥物质科学研究院 | Bone surgery navigation system based on multimode image fusion |
| WO2020129034A1 (en) * | 2018-12-19 | 2020-06-25 | INDIAN INSTITUTE OF TECHNOLOGY MADRAS (IIT Madras) | Robotic surgery systems and surgical guidance methods thereof |
| CN111429491A (en) * | 2020-03-11 | 2020-07-17 | 上海嘉奥信息科技发展有限公司 | Spine preoperative three-dimensional image and intraoperative two-dimensional image registration method and system |
| CN111588467A (en) * | 2020-07-24 | 2020-08-28 | 成都金盘电子科大多媒体技术有限公司 | Method for converting three-dimensional space coordinates into two-dimensional image coordinates based on medical images |
| WO2021030406A1 (en) * | 2019-08-12 | 2021-02-18 | Integrity Implants Inc. | Spinal orientation system |
| CN113040908A (en) * | 2021-02-02 | 2021-06-29 | 武汉联影智融医疗科技有限公司 | Registration method, device, computer equipment and storage medium for surgical navigation |
| CN113870331A (en) * | 2021-10-07 | 2021-12-31 | 浙江大学 | Chest CT and X-ray real-time registration algorithm based on deep learning |
| CN114821031A (en) * | 2022-02-25 | 2022-07-29 | 上海极睿医疗科技有限公司 | Intraoperative image matching method, device and system based on C-arm machine |
| WO2023006021A1 (en) * | 2021-07-30 | 2023-02-02 | 武汉联影智融医疗科技有限公司 | Registration method and system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10102640B2 (en) * | 2016-11-29 | 2018-10-16 | Optinav Sp. Z O.O. | Registering three-dimensional image data of an imaged object with a set of two-dimensional projection images of the object |
| TWI741536B (en) * | 2020-03-20 | 2021-10-01 | 台灣骨王生技股份有限公司 | Surgical navigation image imaging method based on mixed reality |
| CN115211966A (en) * | 2022-07-27 | 2022-10-21 | 北京积水潭医院 | Orthopedic robot positioning method, system, equipment and medium |
-
2023
- 2023-10-09 CN CN202311295654.7A patent/CN117017487B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011144412A1 (en) * | 2010-05-18 | 2011-11-24 | Siemens Aktiengesellschaft | Determining and verifying the coordinate transformation between an x-ray system and a surgery navigation system |
| WO2018075784A1 (en) * | 2016-10-21 | 2018-04-26 | Syverson Benjamin | Methods and systems for setting trajectories and target locations for image guided surgery |
| WO2020129034A1 (en) * | 2018-12-19 | 2020-06-25 | INDIAN INSTITUTE OF TECHNOLOGY MADRAS (IIT Madras) | Robotic surgery systems and surgical guidance methods thereof |
| WO2021030406A1 (en) * | 2019-08-12 | 2021-02-18 | Integrity Implants Inc. | Spinal orientation system |
| CN110946654A (en) * | 2019-12-23 | 2020-04-03 | 中国科学院合肥物质科学研究院 | Bone surgery navigation system based on multimode image fusion |
| CN111429491A (en) * | 2020-03-11 | 2020-07-17 | 上海嘉奥信息科技发展有限公司 | Spine preoperative three-dimensional image and intraoperative two-dimensional image registration method and system |
| CN111588467A (en) * | 2020-07-24 | 2020-08-28 | 成都金盘电子科大多媒体技术有限公司 | Method for converting three-dimensional space coordinates into two-dimensional image coordinates based on medical images |
| CN113040908A (en) * | 2021-02-02 | 2021-06-29 | 武汉联影智融医疗科技有限公司 | Registration method, device, computer equipment and storage medium for surgical navigation |
| WO2023006021A1 (en) * | 2021-07-30 | 2023-02-02 | 武汉联影智融医疗科技有限公司 | Registration method and system |
| CN113870331A (en) * | 2021-10-07 | 2021-12-31 | 浙江大学 | Chest CT and X-ray real-time registration algorithm based on deep learning |
| CN114821031A (en) * | 2022-02-25 | 2022-07-29 | 上海极睿医疗科技有限公司 | Intraoperative image matching method, device and system based on C-arm machine |
Non-Patent Citations (2)
| Title |
|---|
| 一种基于2D/3D配准的脊柱术中校正方法;曾玲;余伟巍;席平;;中国组织工程研究与临床康复(13);59-62 * |
| 基于ICP算法的手术导航三维配准技术;王君臣;王田苗;徐源;方礼明;;北京航空航天大学学报(04);45-49 * |
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