A multiple-layer flexible mesh template matching method for non-rigid registration between a pelvis model and CT images

A robust non-rigid registration method has been developed to deform a pelvis model to match with anatomical structures in a CT image. A statistical volumetric model is constructed from a collection of training CT datasets. The model is represented as a hierarchical tetrahedral mesh equipped with embedded Bernstein polynomial density functions on the barycentric coordinates of each tetrahedron. The prior information of both shape properties and density properties is incorporated in the model. The non-rigid registration process consists of three stages: affine transformation, global deformation, and local deformation. A multiple-layer flexible mesh template matching method is developed to adjust the location of each vertex on the model to achieve an optimal match with the anatomical structure. The mesh template is retrieved directly from the tetrahedral mesh structure, with multiple-layer structure for different scales of anatomical features and flexible searching sphere for robust template matching. An adaptive deformation focus strategy is adopted to gradually deform each vertex to its matched destination. Several constraints are applied to guarantee the smoothness and continuity. A "leave-one-out" validation showed that the method can achieve about 94% volume overlap and 5.5% density error between the registered model and the ground truth model.