Orthogonal subspace projection-based approaches to classification of MR image sequences

Orthogonal subspace projection (OSP) approach has shown success in hyperspe ctral image classification. Recently, the feasibility of applying OSP to mu ltispectral image classification was also demonstrated via SPOT (Satellite Pour l'Observation de la Terra) and Landsat (Land Satellite) images. Since an MR (magnetic resonance) image sequence is also acquired by multiple spec tral channels (bands), this paper presents a new application of OSP in MR i mage classification. The idea is to model an MR image pixel in the sequence as a linear mixture of substances (such as white matter, gray matter, cere bral spinal fluid) of interest from which each of these substances can be c lassified by a specific subspace projection operator followed by a desired matched filter. The experimental results show that OSP provides a promising alternative to existing MR image classification techniques. (C) 2001 Elsev ier Science Ltd. All rights reserved.