title: An Over-Complete Independent Component Analysis (ICA) Approach to Magnetic Resonance Image Analysis.
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.
authors.affiliation: Remote Sensing Signal and Image Processing Laboratory, Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD 21250.
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.forename: C-I
authors.initials: CI
authors.lastname: Chang
authors.forename: Hsiang
authors.initials: H
authors.lastname: Ming Chen
authors.forename: C
authors.initials: C
authors.lastname: -C Chen
authors.forename: Jyh
authors.initials: J
authors.lastname: Wen Chai
authors.forename: Yen-Chieh
authors.initials: YC
authors.lastname: Ouyang