Distance-Intensity for Image Registration

In this paper, a novel one-element voxel attribute, namely distance-intensity (DI), is defined for associating spatial information with image intensity for registration tasks. For each voxel in an image, the DI feature encodes spatial information at a global level, and is about the distance of the voxel to its closest object boundary, together with the original intensity information. Without the help of image segmentations, the computation of the DI map is carried out by applying a Poisson process on a vector field that combines both gradient and distance-gradient. Mutual information (MI) is adopted as a similarity measure on the DI feature space. A multi-resolution registration method is then used for aligning multi-modal images. Experimental results show that, as compared with the conventional MI-based method, the proposed method has longer capture ranges at different image resolutions. This leads to more robust registrations. Randomized registration experiments on clinical 3D CT, MR-T1 and MR-T2 datasets demonstrate that the new method gives higher success rates than the traditional MI-based method.