ELASTIC IMAGE REGISTRATION USING IMPROVED ROBUST POINT MATCHING
We present an improved Robust Point Matching (RPM) framework to register elastic deformed images. The framework accelerates its convergence speed and improves its robustness to match landmark sets. In RPM, the initial value of temperature parameter T plays an importance role to estimates the correspondence matrix by deterministic annealing. In this paper, estimation of T based on the location relation of data point sets automatically is presented, and convergence speed of RPM improved greatly. Moreover, estimation principles of the regularization parameters are introduced also. We compared the convergence speed and the robustness of our technique to standard RPM for synthetic data. Finally, we demonstrate the superior performance of the improved RPM to multimodal medical image elastic registration.
Elastic image registration Robust point matching Thin-Plate spline
XUAN YANG JI-HONG PEI
College of Information Engineering, Shenzhen University, Shenzhen 518060, China Intelligent Information Processing Laboratory of Shenzhen University, Shenzhen, 518060, China
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
2835-2840
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）