Work

Elastic Matching of Diffusion Tensor Images

Year: 2000

Type: article

Abstract: 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.

Source: Computer Vision and Image Understanding

DOI: 10.1006/cviu.1999.0817

Authors: Daniel C. Alexander, James C. Gee

Institution: University of Pennsylvania

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,090

Funder: National Institute of Neurological Disorders and Stroke