Elastic Matching of Diffusion Tensor Images

In this paper, we discuss matching of magnetic resonance, diffusion tensor (DT) images of the human brain. Issues concerned with matching and transforming these complex images are discussed. In particular, we outline a method for preserving the intrinsic orientation of the data during nonrigid warps of the image and a number of similarity measures are proposed, based on the DT itself, on the DT deviatoric, and on indices derived from the DT. 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 the 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.