Independent component imaging of disease signatures

Yue Wang, Junying Zhang, Kun Huang, Javed Khan, Zsolt Szabo

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

Abstract

This paper describes a neural computation approach to independent component imaging of disease signatures. The novel feature is to separate mixed imagery sources blindly over an informative index subspace. The recovery of patterns is achieved by independent component analysts, whose parameters are estimated using the infomax principle. We discuss the theoretic roadmap of the approach, and its applications to the partial volume correction in cDNA microarray expression and the neuro-transporter binding separation in positron emission tomography.

Original languageEnglish (US)
Title of host publication2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
PublisherIEEE Computer Society
Pages457-460
Number of pages4
ISBN (Electronic)078037584X
DOIs
StatePublished - 2002
EventIEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States
Duration: Jul 7 2002Jul 10 2002

Publication series

NameProceedings - International Symposium on Biomedical Imaging
Volume2002-January
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Other

OtherIEEE International Symposium on Biomedical Imaging, ISBI 2002
CountryUnited States
CityWashington
Period7/7/027/10/02

Keywords

  • Independent component analysis
  • Microarrays
  • Neural computation
  • Positron emission tomography

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Independent component imaging of disease signatures'. Together they form a unique fingerprint.

Cite this