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Proceedings Paper

ICE: a statistical approach to identifying constituents of biomedical hyperspectral images
Author(s): Mark Berman; Aloke Phatak; Ryan Lagerstrom
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Paper Abstract

A problem of considerable interest in the hyperspectral and chemical imaging communities in recent years has been the automated identification and mapping of the constituent materials ("endmembers") present in a hyperspectral image. Several of the more important endmember-finding algorithms are discussed and some of their shortcomings highlighted. A relatively new algorithm, ICE, which attempts to address these shortcomings, is introduced. Although ICE was originally developed for exploration applications of airborne hyperspectral data, its performance on two biomedical data sets is investigated. Possible future research directions are outlined.

Paper Details

Date Published: 23 March 2005
PDF: 12 pages
Proc. SPIE 5694, Spectral Imaging: Instrumentation, Applications, and Analysis III, (23 March 2005); doi: 10.1117/12.600291
Show Author Affiliations
Mark Berman, CSIRO Mathematical and Information Sciences (Australia)
Aloke Phatak, CSIRO Mathematical and Information Sciences (Australia)
Ryan Lagerstrom, CSIRO Mathematical and Information Sciences (Australia)


Published in SPIE Proceedings Vol. 5694:
Spectral Imaging: Instrumentation, Applications, and Analysis III
Gregory H. Bearman; Anita Mahadevan-Jansen; Richard M. Levenson, Editor(s)

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