Robust non-rigid registration of medical images with incomplete image information using local structure-adaptive block matching method

Abstract

A novel non-rigid registration algorithm within multi-resolution block matching framework is presented for accurate and robust image registration in the presence of incomplete image information. After getting the deformation field computed from block-matching, we introduce robust and structure-adaptive normalized convolution in spatial regularization of deformation field. Unlike traditional framework of normalized convolution, in which the local deformation is modified through a projection onto a subspace, however, the applicability function of structure-adaptive normalized convolution based on an anisotropic Gaussian kernel is adapted to local linear or edge structures in the images to be registered. This leads to more samples of regions of homogeneity being gathered for the regularization of deformation field, which can reduce deformation diffusion across discontinuities. A robust signal certainty is also adapted to each displacement vector in the deformation field to measure its accuracy. The results show that the method is sufficiently accurate and robust to incomplete image information for multi-temporal non-rigid image registration.