CN113034532B - Method for predicting soft tissue deformation after plastic surgery based on mesh-free model - Google Patents
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- 238000006073 displacement reaction Methods 0.000 claims abstract description 18
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- 238000001356 surgical procedure Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 3
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Abstract
The invention relates to the field of medical plastic prediction, and discloses a mesh-free model-based prediction method for soft tissue deformation after plastic surgery, which is used for improving the accuracy of plastic surgery effect prediction. The invention comprises the following steps; s1, extracting the inner surface and the outer surface of soft tissue of an affected area of an operation from CT data of a plastic department before the operation of a patient; s2, extracting mesh-free soft tissue nodes in the operation influence range between the inner surface and the outer surface of the soft tissue; s3, constructing a non-grid shape function and a partial derivative of the non-grid shape function of the soft tissue node by adopting a non-grid modeling method; s4, carrying out non-grid deformation simulation on the soft tissue nodes according to the bone displacement; and S5, interpolating and smoothing the node displacement of the outer surface of the soft tissue to obtain a position simulation predicted value of the outer surface of the whole soft tissue. The invention is suitable for soft tissue deformation prediction after various plastic surgeries, such as maxillofacial plastic surgeries, orthodontic surgeries and the like, wherein the soft tissue appearance is changed by correcting bones.
Description
Technical Field
The invention relates to the field of medical plastic prediction, in particular to a mesh-free model-based prediction method for soft tissue deformation after plastic surgery.
Background
With the economic development and the improvement of the mental culture level of people, the number of patients requiring the physical plastic surgery is increased year by year, and the maxillofacial bone plastic surgery is a representative one. In maxillofacial bone plastic operation, one of the most concerned problems of patients is how much the face of the patients is improved after operation, but the current commercial plastic operation simulation software mainly aims at the operation simulation and scheme design of hard tissues such as osteotomy, orthodontics and the like, and the contour deformation prediction of a face 3D image is carried out on the change of the soft tissues and the face after operation only based on computer graphics, so that the effect is greatly different from the real effect after operation. The inventor researches and finds that the main reasons causing the problems are that the prior art lacks qualitative analysis and prediction on objective quantification of postoperative effects of patients, and the postoperative real effects are far away from the expected improvement effects of the patients, so that the patients are caused to have discontent treatment results and the like.
At present, a patent with publication number CN107134010 relates to the use of a finite element method for the shape prediction of breast elastic soft tissue, but the finite element method is established based on a mesh model, and the mesh model has great difficulty in processing the problems of mesh initialization, large deformation (such as large displacement of bones by an operation scheme), discontinuous mesh distribution (such as the continuity of soft tissue mesh is damaged at the mouth and nose of a jaw face), and the like, so that pathological meshes are easy to appear, and the accuracy and stability of calculation are affected.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method for predicting the soft tissue deformation after the plastic surgery based on the mesh-free model is used for improving the accuracy of prediction of the plastic surgery effect.
In order to achieve the purpose, the invention adopts the technical scheme that: a mesh-free model based method for predicting soft tissue deformation after plastic surgery comprises the following steps:
s1, extracting the inner surface and the outer surface of soft tissue of an affected area of an operation from CT data of a plastic department before the operation of a patient;
s2, extracting mesh-free soft tissue nodes in the operation influence range between the inner surface and the outer surface of the soft tissue;
s3, constructing a non-grid shape function and a partial derivative of the non-grid shape function of the soft tissue node by adopting a non-grid modeling method;
s4, performing non-grid deformation simulation on the soft tissue nodes according to the bone displacement;
and S5, interpolating and smoothing the node displacement of the outer surface of the soft tissue to obtain a position simulation predicted value of the outer surface of the whole soft tissue.
Specifically, the shaping part can be a jaw part.
Further, step S1 specifically includes:
s1-1, extracting three-dimensional voxel data from a CT image data file of a preoperative plastic department of a patient, and adjusting each dimension of the three-dimensional voxel to be uniform resolution;
s1-2, setting a density segmentation threshold value of the skeleton and the soft tissue according to the density difference of the soft tissue and the skeleton in the CT of the plastic part, and extracting an isosurface of the three-dimensional voxel under the skeleton density threshold value as a soft tissue inner surface1 and an isosurface of the three-dimensional voxel under the soft tissue density threshold value as a soft tissue outer surface2 by using a three-dimensional isosurface extraction algorithm.
Further, step S2 specifically includes:
s2-1, determining a three-dimensional coordinate range of a bone region area1 subjected to the operation of the plastic part and affected by the operation in the three-dimensional voxel data according to an operation scheme;
s2-2, setting a soft tissue distance range threshold value threshold1 influenced by the operation, and extending the three-dimensional coordinate range of the bone region obtained in the step S2-1 to the outside by the distance threshold1 to obtain a soft tissue region coordinate range area2 influenced by the operation of the plastic part;
and S2-3, extracting soft tissue nodes on the inner surface of the soft tissue, the outer surface of the soft tissue and between the inner surface and the outer surface of the soft tissue in the step S1-2 according to a set node distance threshold value threshold2 in the coordinate range area2 of the soft tissue affected by the plastic surgery.
Further, in step S3, the shape function and the partial derivative thereof are calculated by a mesh-free moving least square method or a mesh-free radial basis interpolation method.
Further, step S4 specifically includes:
s4-1, constructing an elastic mechanical overall stiffness matrix K of all soft tissue nodes by using a meshless method;
s4-2, constructing an elastic mechanical punishment stiffness matrix Ka and a punishment external force matrix F of the meshless method by taking node displacement on the inner surface of the soft tissue as an essential boundary condition a ；
S4-3, constructing an elastic mechanics discrete control equation (K + K) a )U＝F a And solving all node displacement vectors U in the formula by using a least square method.
The invention has the beneficial effects that: the invention is based on a mesh-free modeling method, carries out accurate biomechanical modeling simulation on the displacement change of the soft tissue at the back of the maxillofacial plastic, has the advantages of novel method, reliable result, accurate prediction and the like, can improve the accuracy of the prediction of the plastic surgery effect, and provides important preoperative reference for doctors and patients. The invention can be suitable for soft tissue deformation prediction after various plastic surgeries, such as maxillofacial plastic surgeries, orthodontic surgeries and the like, wherein the soft tissue shape is changed by correcting bones.
Drawings
Fig. 1 is a flowchart of predicting soft tissue deformation after a maxillofacial plastic surgery based on a mesh-free model according to an embodiment.
FIG. 2 is a schematic diagram of a soft tissue superior surface1 and a soft tissue inferior surface2 extracted from dicom according to an embodiment.
Fig. 3 is a schematic diagram of soft tissue mesh-free nodes extracted in the embodiment.
FIG. 4 is a schematic diagram of the upper surface of soft tissue predicted according to simulation results according to the embodiment.
Detailed Description
In order to improve the accuracy of the prediction of the plastic surgery effect, the invention provides a mesh-free model-based prediction method of soft tissue deformation after plastic surgery, which comprises the following steps:
s1, extracting the inner surface and the outer surface of soft tissue of an affected area of an operation from CT data of a plastic department before the operation of a patient;
s2, extracting mesh-free soft tissue nodes in the operation influence range between the inner surface and the outer surface of the soft tissue;
s3, constructing a non-grid shape function and a partial derivative of the non-grid shape function of the soft tissue node by adopting a non-grid modeling method;
s4, carrying out non-grid deformation simulation on the soft tissue nodes according to the bone displacement;
and S5, interpolating and smoothing the node displacement of the outer surface of the soft tissue to obtain a position simulation predicted value of the outer surface of the whole soft tissue.
The method simulates the postoperative deformation of the soft tissue of the jaw face by a mesh-free method, improves the accuracy of the prediction of the operation effect, and provides important preoperative reference for doctors and patients.
The technical solution of the present invention will be described clearly and completely by taking the prediction of soft tissue deformation after maxillofacial plastic surgery as an example, it is obvious that the described embodiment is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and it should be obvious to those skilled in the art that modifications to the technical solution described in the foregoing embodiments or equivalent substitutions of some technical features are made, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
As shown in fig. 1, the embodiment provides a mesh-free model-based soft tissue deformation prediction method after maxillofacial plastic surgery, which includes the following specific steps:
s1, extracting the inner surface and the outer surface of soft tissue of an affected region by an operation from CT data before the operation of a patient:
s1-1, extracting three-dimensional voxel data from a dicom file of head CT image data before operation of a patient, and adjusting all dimensions of the three-dimensional voxel to be uniform in resolution, such as 1mm < 1mm > 1mm, according to pixel resolution information and layer thickness information in the dicom data;
s1-2, setting a density segmentation threshold of bones and soft tissues according to density difference of the soft tissues and the bones in CT, wherein the typical bone density threshold is 2000, the typical soft tissue density segmentation threshold is 800, extracting an isosurface of a three-dimensional voxel under the bone density threshold as a soft tissue inner surface1 by utilizing a three-dimensional isosurface extraction algorithm such as a Dual contour algorithm, extracting an isosurface of the three-dimensional voxel under the soft tissue density threshold as a soft tissue outer surface2, wherein the surface1 corresponds to an innermost soft tissue layer attached to the surfaces of the bones, and the surface2 corresponds to an epidermal layer of skin, as shown in FIG. 2.
S2, extracting mesh-free soft tissue nodes in the operation influence range between the inner surface and the outer surface of the soft tissue:
s2-1, according to the operation scheme, determining a three-dimensional coordinate range of a bone region area1 subjected to the maxillofacial operation and affected by the operation in the three-dimensional voxel data, for example, in a chin shaping operation, the coordinate range includes a chin top bone cut and moved by the operation scheme, and in an inverted L-shaped mandibular osteotomy operation, the coordinate range includes not only an inverted L-shaped osteotomy part cut and moved but also an entire mandibular part simultaneously displaced with the inverted L-shaped bone;
s2-2, setting a threshold value threshold1 of the soft tissue distance range affected by the operation, wherein the typical threshold value is 30-50 mm, and extending the three-dimensional coordinate range of the bone region obtained in the step S2-1 outwards by the distance threshold1 to obtain a soft tissue region coordinate range area2 affected by the maxillofacial operation;
s2-3, extracting soft tissue nodes P on the inner surface of the soft tissue, on the outer surface of the soft tissue and between the inner surface and the outer surface of the soft tissue in the step S1-2 according to a set node distance threshold2 in the coordinate range area2 of the soft tissue affected by the maxillofacial surgery, as shown in fig. 3.
S3, constructing a non-grid shape function and a partial derivative thereof of the soft tissue node by adopting a non-grid modeling method, wherein the shape function and the partial derivative thereof can be calculated by adopting a non-grid moving least square Method (MLS) or a non-grid radial basis interpolation method (RPIM);
s4, carrying out non-grid deformation simulation on the soft tissue nodes according to the bone displacement:
s4-1, constructing an elastic mechanical overall stiffness matrix K of all soft tissue nodes by using a gridless method;
s4-2, constructing an elastic mechanical punishment stiffness matrix Ka and a punishment external force matrix F of a meshless method by taking node displacement on the inner surface of soft tissue as an essential boundary condition a ；
S4-3, constructing an elastic mechanics discrete control equation (K + K) a )U＝F a And solving all node displacement vectors U in the formula by using a least square method.
S5, interpolating and smoothing the node displacement of the outer surface of the soft tissue to obtain a position simulation predicted value of the outer surface of the whole soft tissue, wherein the obtained predicted outer surface of the soft tissue is shown in FIG. 4.
Claims (6)
1. A mesh-free model-based soft tissue deformation prediction method after plastic surgery is characterized by comprising the following steps:
s1, extracting the inner surface and the outer surface of soft tissue of an affected area of an operation from CT data of a plastic department before the operation of a patient;
s2, extracting mesh-free soft tissue nodes in an operation influence range between the inner surface and the outer surface of the soft tissue;
s3, constructing a non-grid shape function and a partial derivative of the non-grid shape function of the soft tissue node by adopting a non-grid modeling method;
s4, carrying out non-grid deformation simulation on the soft tissue nodes according to the bone displacement;
and S5, interpolating and smoothing the node displacement of the outer surface of the soft tissue to obtain a position simulation predicted value of the outer surface of the whole soft tissue.
2. The mesh-free model-based soft tissue deformation prediction method after plastic surgery according to claim 1, wherein the plastic part is a jaw part.
3. The method for predicting soft tissue deformation after plastic surgery based on mesh-free model according to claim 1 or 2, wherein the step S1 specifically comprises:
s1-1, extracting three-dimensional voxel data from a CT image data file of a preoperative plastic department of a patient, and adjusting each dimension of the three-dimensional voxel to be uniform resolution;
s1-2, setting a density segmentation threshold value of the bone and the soft tissue according to the density difference of the soft tissue and the bone in the CT of the plastic part, extracting an isosurface of the three-dimensional voxel under the bone density threshold value as soft tissue inner surface1 by utilizing a three-dimensional isosurface extraction algorithm, and extracting an isosurface of the three-dimensional voxel under the soft tissue density threshold value as soft tissue outer surface2.
4. The mesh-free model-based soft tissue deformation prediction method after plastic surgery according to claim 3, wherein the step S2 specifically comprises:
s2-1, determining a three-dimensional coordinate range of a bone region area1 subjected to the operation of the plastic part and affected by the operation in the three-dimensional voxel data according to an operation scheme;
s2-2, setting a soft tissue distance range threshold value threshold1 influenced by the operation, and extending the three-dimensional coordinate range of the bone region obtained in the step S2-1 to the outside by the distance threshold1 to obtain a soft tissue region coordinate range area2 influenced by the operation of the plastic part;
and S2-3, extracting soft tissue nodes on the inner surface of the soft tissue, the outer surface of the soft tissue and between the inner surface and the outer surface of the soft tissue in the step S1-2 according to a set node distance threshold value threshold2 in the coordinate range area2 of the soft tissue affected by the plastic surgery.
5. The method for predicting soft tissue deformation after plastic surgery based on mesh-free model as claimed in claim 1 or 2, wherein in step S3, the shape function and its partial derivative are calculated by mesh-free moving least squares method or mesh-free radial basis interpolation method.
6. The method for predicting soft tissue deformation after plastic surgery based on mesh-free model according to claim 1 or 2, wherein the step S4 specifically comprises:
s4-1, constructing an elastic mechanical overall stiffness matrix K of all soft tissue nodes by using a gridless method;
s4-2, constructing an elastic mechanical punishment stiffness matrix Ka and a punishment external force matrix F of the meshless method by taking node displacement on the inner surface of the soft tissue as an essential boundary condition a ；
S4-3, constructing an elastic mechanics discrete control equation (K + K) a )U＝F a And solving all node displacement vectors U in the formula by using a least square method.
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