Adaptive FEM-based nonrigid image registration using truncated hierarchical B-splines
For medical image registration, this work offers an incremental improvement in computational efficiency over existing FEM-based methods.
The paper presents an adaptive FEM-based nonrigid image registration method using truncated hierarchical B-splines, which reduces computational cost by refining only areas with large deformation. The method improves matrix sparsity and efficiency, demonstrated on 2D synthetic and medical images.
We present an efficient approach of Finite Element Method (FEM)-based nonrigid image registration, in which the spatial transformation is constructed using truncated hierarchical B-splines (THB-splines). The image registration framework minimizes an energy functional using an FEM-based method and thus involves solving a large system of linear equations. This framework is carried out on a set of successively refined grids. However, due to the increased number of control points during subdivision, large linear systems are generated which are generally demanding to solve. Instead of using uniform subdivision, an adaptive local refinement scheme is carried out, only refining the areas of large change in deformation of the image. By incorporating the key advantages of THB-spline basis functions such as linear independence, partition of unity and reduced overlap into the FEM-based framework, we improve the matrix sparsity and computational efficiency. The performance of the proposed method is demonstrated on 2D synthetic and medical images.