Selecting an appropriate anisotropy index for displaying diffusion tensor imaging data with improved contrast and sensitivity

A review of the behavior of different diffusion anisotropy indices (DAIs) t o changes in diffusion anisotropy was undertaken and the limitations of sev eral previously proposed DAIs are discussed. A mathematical representation of anisotropy sensitivity was used to enable image contrast and sensitivity to noise to be predicted. This technique was utilized to devise a new DAI, the gamma-variate anisotropy, which has a low sensitivity to noise and an improved contrast range for human brain imaging. This index can be easily m odified for other applications, in that the range of anisotropy values to w hich it is highly sensitive can be altered. (C) 2000 Wiley-Liss, Inc.