GRAPHICAL ANALYSIS OF MR FEATURE SPACE FOR MEASUREMENT OF CSF, GRAY-MATTER, AND WHITE-MATTER VOLUMES

The problem of volume averaging in quantitating CSF, gray-matter, and white-matter fractions in the brain is solved using a three-compartmen t model and a simple graphical analysis of a multispectral MR feature space. Compartmentalization is achieved without the ambiguities of thr esholding techniques or the need to assume that the underlying pixel p robability distributions have a particular form. A 2D feature space is formed by double SE (proton density- and T2-weighted) MR data with im age nonuniformity removed by a novel technique in which the brain itse lf serves as a uniformity reference. Compartments other than the basic three were rejected by the tailoring of limits in feature space. Phan tom scans substantiate this approach, and the importance of the carefu l selection and standardization of pure tissue reference signals is de monstrated. Compartmental profiles from standardized subvolumes of thr ee normal brains, based on a 3D (Talairach) coordinate system, demonst rate slice-by-slice detail; longitudinal studies confirm reproducibili ty. Compartmentalization may be described graphically and algebraicall y, complementing data displays in feature space and images of compartm entalized brain scans. These studies anticipate the application of our compartmentalization technique to patients with neurological disorder s.