The Morphology Simulation Of Tumor Growth Process And Related Technology Research

With the development of the computer science and the continual appearance of the cross-discipline researches, computer application technology has been used widely in multitudes of subjects'researches. The virtual operation and virtual human are the products in combination with computer science and medicine. The simulation of the tumor growth using computers attracts the attentions of many researchers. This technology involves computer application, computational geometry, and visualization in scientific computing, computer graphics, biomechanics and medicine. The simulation of tumor growth using computers can help people to explore the mechanism of the tumor generation and growth and then to understand the characteristics of tumor as a self-organizing system and a dynamic evolvement system, which in turn has great significance for the diagnosis of tumor prevention and cure.The dissertation firstly sets its background in the tumor growth simulation in vein complex environment located at the skull base, then summarizes the structure of the simulation system and studies the crucial technology of simulating system.1) With the thorough research of the collision detection algorithm based on oriented bounding box, a new construct algorithm using approximate convex hull and a new test algorithm using 1-norm pre-judgment are presented in the dissertation. The constructing algorithm of OBB basing on approximate convert hull is divided into two stages. Firstly, extract the vertices near the model surface to construct OBB by way of the approximate convex hull algorithm. Secondly, constructing OBB using the extracted vertices set. The basic idea of the test algorithm on simple measure OBB is that add 2 records to record the maximum and minimum distances from the center of OBB to the vertices of bounding box when constructing the hierarchical structure. First of all, judge whether the centre distance between the two bounding boxes is less than the sum of the two bounding boxes' minimum distance. The two bounding boxes are judged whether they are overlapped when the centers'distance of the two OBBs is less than the sum of the two minimum records. Then consider whether the distance of the centers between the two bounding boxes is greater than the sum of the max records. If the condition is satisfied, the bounding boxes are not considered overlapped, otherwise, project boxes to 15 axes by way of separating axis to judge whether the two OBB are overlapped. To speed up pre-judging process, the max record, the min record and the centers distance are computed by 1-norm.2) The thesis presents a collision response algorithm basing on punishment force and implicit surface. First, obtain the intersected set of the geometrical element of model B by the collision detection between model A and model B. Then construct implicit surface using the surface vertices extracted from intersected vertices of Model B. According to the implicit function value of vertices in the model A, the vertices sets of Model A are classified into two groups:the set of collision and the set of non-collision. For the vertices involved in the set of the collision, compute gradient vector of every vertex and then normalized them. Then multiply the results derived from the previous process with the value of implicit function. And finally, the depth vector is used to compute the force vectors, the result of shape change can be obtained by means of computing the displacement of the vector of A.3) The paper proposes a method to convert a hexahedron CA mesh into a new tetrahedron CA mesh in order to construct accurate force model which helps simulate the interaction process between tumor model and tissue model. The FEM analysis of tetrahedron mesh is more accurate than the FEM analysis of hexahedron mesh, so we should convert the hexahedron mesh into tetrahedron mesh. For every hexahedron, first label the vertices belonging to tumor model and the vertices which do not belong to tumor model. Then classify the vertices according to minimum distance to vertex not belonging to tumor model, finally based on the strategies proposed in the 5.4 part of the dissertation, divide the tumor model into tetrahedron which in not overlapped. Deal with every cell of the tumor model with the same method to get tetrahedron mesh. On the other hand, with regard to the specialties of tumor model obtained from CA model, the thesis proposes an algorithm to abstract the surface vertices and surface triangles, which will make computing the normal vectors apply in rendering tumor volume model with implicit surface.4) Since the vessel model extracted by reconstructed model is inaccurate and the inaccurateness will lead to the inaccurateness of force analysis, the dissertation puts forward an algorithm on rectifying the vessel model. The basic idea of the algorithm is:computing an approximate vessel axis by extracting 2 points; then according to the statistics of the distance between the vertices and the axis, moving the vertices inwardly or outwardly along the vessel's radius direction.