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

C. M. Wang, S. C. Yang, Pau-Choo Chung, C. I. Chang, C. S. Lo, C. C. Chen, C. W. Yang, C. H. Wen

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

Orthogonal subspace projection (OSP) approach has shown success in hyperspectral image classification. Recently, the feasibility of applying OSP to multispectral 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 spectral channels (bands), this paper presents a new application of OSP in MR image 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, cerebral spinal fluid) of interest from which each of these substances can be classified 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.

Original languageEnglish
Pages (from-to)465-476
Number of pages12
JournalComputerized Medical Imaging and Graphics
Volume25
Issue number6
DOIs
Publication statusPublished - 2001 Nov 7

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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