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Research on Key Techniques of Virtual Surgery Planning System for Nasopharyngeal Carcinoma Based on CT Data Set

Author: WangLei
Tutor: WangBoLiang
School: Xiamen University
Course: Computer System Architecture
Keywords: nasopharyngeal carcinoma mesh simplification collision detection bounding volume
CLC: TP399-C8
Type: Master's thesis
Year: 2008
Downloads: 38
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Abstract


The modeling and simulation of human organs is one of the frontier areas of biomedicine research. It is a multi-disciplinary topic, including computer science, physics, electronics and related medical knowledge. As one of the most important and complex organs within human body, nasopharyngeal tissue’s virtualization and surgery planning system plays a significant role in the practice of medicine.In this thesis, some key technologies of virtual surgery planning system for nasopharyngeal carcinoma are investigated systematically. With the background of surgery simulation, this paper proposes a collision detection method based on Oriented Bounding Box bounding volume tree. Bounding volume hierarchy provides an effective method to resolve the intrinsic time complexity in collision detection. The idea behind it is to approximate the object with a simpler bounding volume that is a little bigger than the object. In building hierarchies on object, one can obtain increasingly more accurate approximations of the objects. So during traversing bounding volume hierarchy, it speeds up collision detection by prune away primitive pairs, which will not intersect clearly though rapid intersection test between bounding volumes and just deal with those bounding volume is intersected.The main contributions of this thesis are mainly lie in the following aspects:1. According to the features of medical image, this paper uses a kind of mesh simplification algorithm to speed up collision detection; The algorithm also can preserve the specific features of the model during the process of simplification.2. This paper decomposes the surfaces of an object into a list of convex pieces. High efficiency of the algorithm is obtained by organizing the convex pieces into a binary tree with nodes composed of convex pieces. Furthermore, the algorithm speeds up collision detection by prune away primitive pairs, which will not intersect clearly though rapid intersection test between bounding volumes.3. This paper also uses the acknowledges of geometry to simplify the complexity of the collision detection.

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