Similarity Measures for Matching Diffusion Tensor Images

Abstract

In this paper, we discuss matching of diffusion tensor (DT) MRIs of the human brain. Issues concerned with matching and transforming these complex images are discussed. A number of similarity measures are proposed, based on indices derived from the DT, the DT itself and the DT deviatoric. Each measure is used to drive an elastic matching algorithm applied to the task of registration of 3D images of the human brain. The performance of the various similarity measures is compared empirically by use of several quality of match measures computed over a pair of matched images. Results indicate that the best matches are obtained from a Euclidean difference measure using the full DT.