An over-complete independent component analysis (ICA) approach to magnetic resonance image analysis

Jing Wang, Chein I. Chang, Hsiang Ming Chen, Clayton Chi Chang Chen, Jyh Wen Chai, Yen Chieh Ouyang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper presents a new application of independent component analysis (ICA) in magnetic resonance (MR) image analysis. One of most successful applications for ICA-based approaches in MR imaging is functional MRI (fMRI) which basically deals with one-dimensional temporal signals. The ICA approach proposed in this paper is rather different and considers a set of MR images acquired by different pulse sequences as a 3-dimensional image cube and performs image analysis rather than signal analysis. One major difference between the fMRI-based ICA approaches and our proposed ICA-based image analysis is that the ICA used in the former is under-complete as opposed to the latter which uses over-complete ICA. Such a fundamental difference results in completely different applications.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages3108-3111
Number of pages4
Publication statusPublished - 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 2005 Sept 12005 Sept 4

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period05-09-0105-09-04

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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