OPTIMAL REGULARIZATION PARAMETER IN APPROXIMATE TPS INTERPOLATION
The thin plate splines (TPS) has been applied to landmark-based elastic image registration. However, TPS forces the corresponding landmarks to exactly match each other, which is problematic when the localization of landmarks is prone to some error. Approximating TPS (ATPS) has been proposed to weak the interpolation condition. In ATPS, the regularization parameter plays an important role. It controls the smoothness of the transformation. Unfortunately, how to estimate is not solved. In this paper, estimation of the optimal regularization parameter has been proposed. It combines two evaluation factors, smoothness and location error hypothesis testing, to evaluate transformation results using fuzzy integral. The optimal regularization parameter is the best value maximizing the evaluation function. Experiments of the artificial grids and medial images show that our technique is feasible.
Thin-Plate Spline Regularization Parameter Fuzzy Integral
SONG-NA GUO XUAN YANG HONG-YUAN SUN
College of Information Engineering, Shenzhen University, Shenzhen, 518060, China School of Chemistry and Chemical Engineering, Shenzhen University, 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
1347-1352
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）