Efficient collision detection for soft tissue simulation in a surgical planning system
In the field of cranio-maxillofacial surgery, there is a huge demand from surgeons to be able to automatically predict the post-operative face appearance in terms of a pre-specified bone-remodeling plan. Collision detection is a promising means to achieve this simulation. In this paper, therefore, an efficient collision detection method based on a new 3D signed distance field algorithm is proposed to accurately detect the contact positions and compute the penetration depth with the moving of the bones in the simulation, and thus the contact force between the bones and the soft tissues can be estimated using penalty methods. Thereafter, a nonlinear finite element model is employed to compute the deformation of the soft tissue model. The performance of the proposed collision detection algorithm has been improved in memory requirements and computational efficiency against the conventional methods. In addition, the proposed approach has the superior convergence characteristics against other methods. Therefore, the usage of the collision detection method can effectively assist surgeons in automatically predicting the pos-operative face outline.
Signed distance field collision detection soft tissue prediction surgical simulation
Shengzheng Wang Jie Yang
Merchant Marine College, Shanghai Maritime University, Shanghai, 200135, China Inst. Of Image Proces Inst. of Image Processing & Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, Ch
国际会议
黄山
英文
49-53
2009-08-19（万方平台首次上网日期，不代表论文的发表时间）