Accelerating multi-modal image registration using a supervoxel-based variational framework.

Accelerating multi-modal image registration using a supervoxel-based variational framework. Phys Med Biol. 2018 Nov 23;63(23):235009 Authors: Lafitte L, Zachiu C, Kerkmeijer LGW, Ries M, Denis de Senneville B Abstract For the successful completion of medical interventional procedures, several concepts, such as daily positioning compensation, dose accumulation or delineation propagation, rely on establishing a spatial coherence between planning images and images acquired at different time instants over the course of the therapy. To meet this need, image-based motion estimation and compensation relies on fast, automatic, accurate and precise registration algorithms. However, image registration quickly becomes a challenging and computationally intensive task, especially when multiple imaging modalities are involved. In the current study, a novel framework is introduced to reduce the computational overhead of variational registration methods. The proposed framework selects representative voxels of the registration process, based on a supervoxel algorithm. Costly calculations are hereby restrained to a subset of voxels, leading to a less expensive spatial regularized interpolation process. The novel framework is tested in conjunction with the recently proposed EVolution multi-modal registration method. This results in an algorithm requiring a low number of input parameters, is easily parallelizable and provides an elastic voxel-wise defor...
Source: Physics in Medicine and Biology - Category: Physics Authors: Tags: Phys Med Biol Source Type: research