CN117314978A - Registration method of jaw CBCT image - Google Patents
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Abstract
The invention discloses a registration method of a jaw CBCT image, which comprises the following steps: s1, obtaining coordinate values of each reflective ball of a patient tracking array under a tracking array coordinate system; s2, installing the patient tracking array on the jaw of a patient, and shooting CBCT images of the jaw of the patient comprising the patient tracking array, wherein the CBCT images are marked as image_0; s3, extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system; s4, calculating a conversion matrix from the CBCT image coordinate system to the patient tracking array coordinate system according to coordinate value data of each reflective sphere under two different coordinate systems; the invention only uses CBCT images shot by the patient and the tracking array in operation to establish the conversion relation between the CBCT image coordinate system and the patient tracking array coordinate system, and has simple operation and high registration success rate.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a registration method of a jaw CBCT image.
Background
The image navigation type dental implant surgery aims at showing the relative position relation between the jawbone of a patient and a surgical instrument in the real space in the image space, as shown in fig. 8, so as to help a surgical operator to better solve the current surgical state. In the image navigation type tooth implantation operation, each image coordinate system needs to be registered, and the specific process is as follows:
1. an optical tracking array (with a plurality of reflecting balls) is respectively fixed on the surgical instrument and the teeth on the non-operative side of the patient. The local coordinate systems of the two optical tracking arrays are respectively marked as F tool And F is equal to patient ；
2. The geometry of the end effector portion of the surgical instrument, at F tool The following are known amounts. Taking a dental drill as an example, the point and the axis vector of the dental drill are in F tool The following expressions are denoted s and
3. the binocular positioning camera can obtain the optical reference array in the camera coordinate system F by capturing the reflective sphere on the optical reference array camera Lower real-time pose (i.e. get F camera To F patient Or F tool Is a conversion matrix of (a);
4. in image space (coordinate system F image ) The CBCT image of the patient's jaw remains stationary while the axis of the dental bur in the imageWith the tip point s' along with the change of the relative position relation between the jaw part and the dental drill of a patient in real spaceA change;
5. the image registration is to establish the mapping relation between the display space and the image space, namely F is obtained image To F patient Once the rigid fixation of the patient reference array is completed, the registration matrix is uniquely determined and does not change during subsequent surgery. Recording the calculated registration matrix as T 3 ；
6. Recording a moment, collecting F camera To F patient And F tool The transformation matrix of (a) is T respectively 2 And T is 1 The axis of the dental drillAnd tip point s' can be calculated as:
to achieve image registration, it is generally necessary to attach an array of metal balls of known structure to the teeth (i.e., each metal ball having a spherical center coordinate at F) when the patient takes CBCT images of the jaw patient Known below), the positions of the sphere centers of the metal spheres in the CBCT image are extracted, namely, the sphere centers of the metal spheres are extracted to be F image The coordinate value is obtained by extracting CN115423789A with the sphere center at F patient Lower and F image And matching the lower coordinate values, so as to calculate and obtain an image registration matrix.
The disadvantages of the prior art are:
(1) A plurality of metal balls need to be arranged on the patient tracking array, the relative position relationship between the centers of the metal balls and the reflective balls of the tracking array must be very accurate, and the design and processing difficulty of hardware is high;
(2) The volume of the metal ball for positioning is generally smaller, the artifacts in CBCT are larger, and the ball center of the metal ball image is difficult to accurately position;
(3) If a metal implant exists in the oral cavity of a patient, the extraction of the metal ball for positioning can be interfered, and the calculated amount of an automatic extraction algorithm is increased.
Disclosure of Invention
The invention aims at solving the problems in the prior art and provides a jaw CBCT image registration method which only uses CBCT images shot by a patient and a tracking array thereof in operation to establish a conversion relation from a CBCT image coordinate system to a patient tracking array coordinate system, and has the advantages of simple operation and high registration success rate.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method of registration of a jaw CBCT image, comprising the steps of:
s1, obtaining coordinate values of each reflective ball of a patient tracking array under a tracking array coordinate system;
s2, installing the patient tracking array on the jaw of a patient, and shooting CBCT images of the jaw of the patient comprising the patient tracking array, wherein the CBCT images are marked as image_0;
s3, extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system;
s4, calculating a conversion matrix from the CBCT image coordinate system to the patient tracking array coordinate system according to coordinate value data of each reflective sphere under two different coordinate systems.
The step S1 specifically comprises the following steps:
s1.1, defining an establishment mode of a coordinate system of the patient tracking array by taking a reflective sphere of the patient tracking array as a reference;
s1.2, importing the patient tracking array model into hardware design software, establishing a coordinate system in the mode specified in the previous step, reading coordinate values of the sphere centers of the reflecting spheres under the coordinate system, and recording an ordered point set matrix formed by the coordinate values of the sphere centers of the reflecting spheres as Pset_1.
The step S3 specifically comprises the following steps:
s3.1, performing boundary corrosion operation on the image_0 by using a sphere structural element, and recording and outputting an obtained Image as the image_1;
s3.2, using a mobile cube method, selecting a bone CT value of 250-350 as a threshold value, and generating Surface data of image_1, namely surface_0;
s3.3, generating an axis alignment bounding Box I of surface_0, which is marked as box_0;
s3.4, using the box_0 as an Image template, performing Image masking processing on the image_0, setting values of all voxels in the image_0, which fall into the box_0, to be far smaller than a bone CT value, removing a jaw part of a patient in the image_0, and masking to obtain an Image which is the image_2;
s3.5, using the mobile cube method again, selecting the bone CT value of 250-350 as a threshold value, and generating Surface data of image_2, namely surface_1;
s3.6, detecting connectivity inside the surface_1, splitting the unconnected part of the surface_1, generating an axis alignment bounding box II of each sub-part, and recording and storing the obtained Surface data as S_i (i=1, 2 …, n), wherein n is the number of the reflective spheres;
and S3.7, regarding surface data S_i (i=1, 2 …, n), taking grid vertexes of the surface data S_i, and fitting a space spherical surface by using a least square method to obtain a spherical center sitting mark of the surface data S_i. And recording an ordered point set matrix formed by the spherical center coordinate values obtained by fitting as Pset_2.
For certain surface data, traversing each vertex coordinate value of the surface data, recording the maximum value of x-axis coordinates as x_max, the minimum value of x-axis coordinates as x_min, the maximum value of y-axis coordinates as y_max, the minimum value of y-axis as y_min, the maximum value of z-axis coordinates as z_max and the minimum value of z-axis as z_min, and obtaining the space closed hexahedral graph formed by eight vertexes, namely the axis alignment bounding box.
Step S4 specifically comprises the following steps;
s4.1, calculating a geometric center point coordinate c of the Pset_1, and carrying out integral translation on the point set Pset_1 to obtain Pset_1', so that the geometric center of the point set Pset_1' is located at the origin of a coordinate system;
s4.2, calculating a geometric center point coordinate c ' of the Pset_1, and carrying out integral translation on the point set Pset_2 to obtain Pset_2', so that the geometric center of the point set Pset_2' is located at the origin of a coordinate system;
s4.3 calculating the rotation matrix R required for the point set Pset_1 'to be rigid body matched to the point set Pset_2' by using singular value decomposition tmp ；
S4.4, with R tmp The distance between each point in Pset_1' and the corresponding point in Pset_2' is calculated when Pset_1' is multiplied by the left, if a certain distance value is larger than the actual diameter d of the reflecting ball, R is obtained tmp If the internal points are not used by mistake, changing the sequence of the internal points of the Pset_2 and returning to the step S4.1 again; if the distance between each group of corresponding points is smaller than the actual diameter d of the reflective ball, carrying out the subsequent steps;
s4.5, calculating translation vector t undergone by Pset_1 rigid body moving to Pset_2
t＝c′-R tmp ·c；
The 4x4 rigid body transformation matrix T undergone by the pset_1 rigid body moving to pset_2 can be expressed as
T is the transformation matrix from the CBCT image coordinate system to the patient tracking array coordinate system.
The step S4.3 specifically comprises the following calculation process:
s4.31, calculating the covariance matrix of B and M ' H=Pset_1 '. Cndot.Pset_2 ' T ；
S4.32. SVD of H to obtain H=U.S.V T ；
S4.33 calculating R using SVD results tmp ＝V·U T 。
A registration device for a jaw CBCT image, comprising:
the tracking array coordinate system acquisition module is used for acquiring coordinate values of each reflecting ball of the patient tracking array under the tracking array coordinate system;
the CBCT image acquisition module is used for shooting CBCT images of the jaw part of the patient comprising the patient tracking array;
the image sphere center extraction module is used for extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system;
and the transformation matrix calculation module is used for calculating a transformation matrix from the CBCT image coordinate system to the patient tracking array coordinate system.
An electronic device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the registration method described above.
A storage medium having stored thereon computer program instructions which, when executed by a processor, implement the registration method described above.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the jaw image registration scheme provided by the scheme, a metal ball for positioning is not needed, so that the hardware design requirement is reduced, and meanwhile, the influence of the failure in extracting the sphere center of the metal ball image on image registration is avoided;
2. by establishing a jaw bounding box of a patient, voxel values of a large area (containing a plurality of discrete fragmented data) which is irrelevant to a reflective sphere in the CBCT image are set to be-1000, so that the voxel values cannot appear in a subsequent isosurface, and the calculation efficiency is remarkably improved;
3. the registration scheme only needs to set up a mode of initially defining the patient reference array coordinate system by a user, and the subsequent registration can be completed fully automatically, so that the operation difficulty is low.
Drawings
FIG. 1 is a CBCT image view of a patient's jaw including a patient tracking array in accordance with the present invention;
FIG. 2 is a surface data diagram of image_1 of the present invention;
FIG. 3 is a diagram of an axis aligned bounding box of surface_0 of the present invention;
FIG. 4 is a diagram of image_2 according to the present invention;
FIG. 5 is a surface data diagram of image_2 of the present invention;
FIG. 6 is a second view of the surface_1 axis aligned bounding box of the present invention;
FIG. 7 is a fitted spatial sphere with surface data S_i according to the present invention;
fig. 8 is a schematic diagram of the background art of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made more apparent and fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by one of ordinary skill in the art without undue burden on the person of ordinary skill in the art based on embodiments of the present invention, are within the scope of the present invention.
A method of registration of a jaw CBCT image, comprising the steps of:
step S1, coordinate values of each reflective ball of the patient tracking array under the tracking array coordinate system are obtained.
And step S1.1, defining an establishment mode of the patient tracking array coordinate system by taking the reflective sphere of the patient tracking array as a reference.
The patient tracking array coordinate system is not unique in establishing mode, for example, the geometric centers of all the reflecting balls are used as the origin of the coordinate system, the connecting line direction of some two reflecting balls is the x-axis direction vector of the coordinate system, the x-axis direction vector is multiplied by the connecting line direction of the other two reflecting balls to obtain the z-axis direction vector, and the z-axis direction vector is multiplied by the x-axis direction vector to obtain the y-axis direction vector.
Step S1.2, importing the patient tracking array model into hardware design software, establishing a coordinate system in the prescribed mode, reading coordinate values of the sphere centers of the reflecting spheres under the coordinate system, recording an ordered point set matrix formed by the coordinate values of the sphere centers of the reflecting spheres as Pset_1,
；
the ith column of the matrix is the coordinate value of the ith reflecting sphere, i=1, 2 …, n.
Step S2, the patient tracking array is mounted on the jaw of the patient, and a CBCT Image of the jaw of the patient including the patient tracking array is captured in a conventional manner, so as to ensure that each reflective ball on the tracking array is located in the imaging region, and an Image including each reflective ball is required in the CBCT, and the obtained CBCT Image is denoted as image_0 as shown in fig. 1.
And S3, extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system.
Step S3.1, performing boundary corrosion operation on the image_0 by using a sphere structural element with the radius of 3 voxel size, and recording and outputting the obtained Image as image_1; image_0 itself remains in the state before the etching operation.
In step S3.2, a mobile cube method is used, a bone CT value commonly used in clinic (250-350) is selected as a threshold value, and Surface data of image_1 is generated and named surface_0, as shown in FIG. 2.
For certain surface data, traversing each vertex coordinate value of the surface data, recording the maximum value of x-axis coordinates as x_max, the minimum value of x-axis coordinates as x_min, the maximum value of y-axis coordinates as y_max, the minimum value of y-axis as y_min, the maximum value of z-axis coordinates as z_max and the minimum value of z-axis as z_min, and obtaining the space closed hexahedral graph formed by eight vertexes, namely the axis alignment bounding box.
Step S3.3, generating an axis alignment bounding Box I of surface_0, denoted as Box_0, as shown in FIG. 3.
In step S3.4, using box_0 as an Image template, performing Image masking processing on image_0, setting the value of all voxels falling inside box_0 in image_0 to-1000 or other values far smaller than the bone CT value, removing the jaw portion of the patient in image_0, leaving only the tracking array portion, and performing masking processing to obtain an Image of image_2, as shown in fig. 4.
Step S3.5, a mobile cube method is used again, a bone CT value which is commonly used in clinic (250-350) is selected as a threshold value, surface data of image_2 are generated, and the Surface data are named surface_1; as shown in fig. 5, the surface data can be internally subdivided into 3 classes: the surface data of the reflective sphere is tracked, the surface data of the array support is tracked, and some scattered noise fragmentation surface data is needed to be removed in order to extract the sphere center of the reflective sphere.
S3.6, detecting connectivity inside the surface_1, splitting the unconnected part of the surface_1 and generating an axis alignment bounding box II of each sub-part, recording the real diameter of a reflecting sphere as d as shown in FIG. 6, checking the size of each bounding box, and if the length, width and height of each bounding box are larger than 0.5d and smaller than 1.5d, storing Surface data corresponding to the bounding box (the Surface data corresponds to a reflecting sphere); the surface data obtained by the storage was s_i (i=1, 2 …, n), where n is the number of reflective spheres.
In step S3.7, for the surface data s_i (i=1, 2 …, n), the mesh vertices (the surface data is actually in a mesh shape, as shown in the following figure) are taken, and the spatial spherical surface is fitted by using a least square method, as shown in fig. 7, to obtain a spherical center sitting mark c_i. The ordered point set matrix formed by the spherical center coordinate values obtained by the record fitting is Pset_2,
the ith column of the matrix is the coordinate value of the ith fitted sphere center.
And S4, calculating a conversion matrix from the CBCT image coordinate system to the patient tracking array coordinate system according to coordinate value data of each reflective sphere under two different coordinate systems.
S4.1, calculating a geometric center point coordinate c of the Pset_1, and carrying out integral translation on the point set Pset_1 to obtain Pset_1', so that the geometric center of the point set Pset_1' is located at the origin of a coordinate system;
s4.2, calculating a geometric center point coordinate c ' of the Pset_1, and carrying out integral translation on the point set Pset_2 to obtain Pset_2', so that the geometric center of the point set Pset_2' is located at the origin of a coordinate system;
s4.3 calculating the rotation matrix R required for the point set Pset_1 'to be rigid body matched to the point set Pset_2' by using singular value decomposition tmp The method is characterized by comprising the following steps:
s4.31, calculating a covariance matrix H=Pset_1 '. Cndot (Pset_2 ') T of B and M ';
s4.32, carrying out SVD on H to obtain H=U.S.VT;
s4.33, calculating rtmp=v·ut using the SVD result.
S4.4, with R tmp The distance between each point in Pset_1' and the corresponding point in Pset_2' is calculated when Pset_1' is multiplied by the left, if a certain distance value is larger than the actual diameter d of the reflecting ball, R is obtained tmp If the internal points are not used by mistake, changing the sequence of the internal points of the Pset_2 and returning to the step S4.1 again; if the distance between each group of corresponding points is smaller than the actual diameter d of the reflective ball, carrying out the subsequent steps;
s4.5, calculating translation vector t undergone by Pset_1 rigid body moving to Pset_2
t＝c′-R tmp ·c；
The 4x4 rigid body transformation matrix T undergone by the pset_1 rigid body moving to pset_2 can be expressed as
；
T is the transformation matrix from the CBCT image coordinate system to the patient tracking array coordinate system.
The invention also provides a registration device of the jaw CBCT image, which comprises:
the tracking array coordinate system acquisition module is used for acquiring coordinate values of each reflecting ball of the patient tracking array under the tracking array coordinate system;
the CBCT image acquisition module is used for shooting CBCT images of the jaw part of the patient comprising the patient tracking array;
the image sphere center extraction module is used for extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system;
and the transformation matrix calculation module is used for calculating a transformation matrix from the CBCT image coordinate system to the patient tracking array coordinate system.
An electronic device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the registration method described above.
A storage medium having stored thereon computer program instructions which, when executed by a processor, implement the registration method described above.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. A method for registering a CBCT image of a jaw, comprising the steps of:
s1, obtaining coordinate values of each reflective ball of a patient tracking array under a tracking array coordinate system;
s2, installing the patient tracking array on the jaw of a patient, and shooting CBCT images of the jaw of the patient comprising the patient tracking array, wherein the CBCT images are marked as image_0;
s3, extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system;
s4, calculating a conversion matrix from the CBCT image coordinate system to the patient tracking array coordinate system according to coordinate value data of each reflective sphere under two different coordinate systems.
2. The method of registration of a CBCT image of a jaw as recited in claim 1, wherein step S1 specifically includes:
s1.1, defining an establishment mode of a coordinate system of the patient tracking array by taking a reflective sphere of the patient tracking array as a reference;
s1.2, importing the patient tracking array model into hardware design software, establishing a coordinate system in the mode specified in the previous step, reading coordinate values of the sphere centers of the reflecting spheres under the coordinate system, and recording an ordered point set matrix formed by the coordinate values of the sphere centers of the reflecting spheres as Pset_1.
3. The method of registration of a CBCT image of a jaw as recited in claim 2, wherein step S3 specifically includes:
s3.1, performing boundary corrosion operation on the image_0 by using a sphere structural element, and recording and outputting an obtained Image as the image_1;
s3.2, using a mobile cube method, selecting a bone CT value of 250-350 as a threshold value, and generating Surface data of image_1, namely surface_0;
s3.3, generating an axis alignment bounding Box I of surface_0, which is marked as box_0;
s3.4, using the box_0 as an Image template, performing Image masking processing on the image_0, setting values of all voxels in the image_0, which fall into the box_0, to be far smaller than a bone CT value, removing a jaw part of a patient in the image_0, and masking to obtain an Image which is the image_2;
s3.5, using the mobile cube method again, selecting the bone CT value of 250-350 as a threshold value, and generating Surface data of image_2, namely surface_1;
s3.6, detecting connectivity inside the surface_1, splitting the unconnected part of the surface_1, generating an axis alignment bounding box II of each sub-part, and recording and storing the obtained Surface data as S_i (i=1, 2 …, n), wherein n is the number of the reflective spheres;
and S3.7, regarding surface data S_i (i=1, 2 …, n), taking grid vertexes of the surface data S_i, fitting a space spherical surface by using a least square method to obtain a spherical center sitting mark of the surface data S_i, and recording an ordered point set matrix formed by spherical center coordinate values obtained by fitting as Pset_2.
4. A registration method of a CBCT image of a jaw according to claim 3, wherein the surface data is a spatial polygon formed by connecting a plurality of vertices, and for a certain surface data, each vertex coordinate value of the surface data is traversed, and among the coordinate values, an x-axis coordinate maximum value is x_max, an x-axis minimum value is x_min, a y-axis coordinate maximum value is y_max, a y-axis minimum value is y_min, a z-axis coordinate maximum value is z_max, a z-axis minimum value is z_min, and a spatial closed hexahedral figure formed by eight vertices is an axis alignment bounding box.
5. A method of registration of a CBCT image of a jaw as claimed in claim 3, wherein step S4 comprises the steps of;
s4.1, calculating a geometric center point coordinate c of the Pset_1, and carrying out integral translation on the point set Pset_1 to obtain Pset_1', so that the geometric center of the point set Pset_1' is located at the origin of a coordinate system;
s4.2, calculating a geometric center point coordinate c ' of the Pset_1, and carrying out integral translation on the point set Pset_2 to obtain Pset_2', so that the geometric center of the point set Pset_2' is located at the origin of a coordinate system;
s4.3 calculating the rotation matrix R required for the point set Pset_1 'to be matched to the point set Pset_2' in a rigid body manner by using singular value decomposition tmp ；
S4.4, with R tmp The distance between each point in Pset_1' and the corresponding point in Pset_2' is calculated when Pset_1' is multiplied by the left, if a certain distance value is larger than the actual diameter d of the reflecting ball, R is obtained tmp If the internal points are not used by mistake, changing the sequence of the internal points of the Pset_2 and returning to the step S4.1 again; if the distance between each group of corresponding points is smaller than the actual diameter d of the reflective ball, carrying out the subsequent steps;
s4.5, calculating translation vector t undergone by Pset_1 rigid body moving to Pset_2
t＝c′-R tmp ·c；
The 4x4 rigid body transformation matrix T undergone by the pset_1 rigid body moving to pset_2 can be expressed as
；
T is the transformation matrix from the CBCT image coordinate system to the patient tracking array coordinate system.
6. A registration device for a CBCT image of a jaw, comprising:
the tracking array coordinate system acquisition module is used for acquiring coordinate values of each reflecting ball of the patient tracking array under the tracking array coordinate system;
the CBCT image acquisition module is used for shooting CBCT images of the jaw part of the patient comprising the patient tracking array;
the image sphere center extraction module is used for extracting the image sphere centers of the reflective spheres in the CBCT image to obtain coordinate values of each reflective sphere under a CBCT image coordinate system;
and the transformation matrix calculation module is used for calculating a transformation matrix from the CBCT image coordinate system to the patient tracking array coordinate system.
7. An electronic device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the registration method of any one of claims 1 to 6.
8. A storage medium having stored thereon computer program instructions which, when executed by a processor, implement the registration method of any one of claims 1 to 6.
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