Local Features in Biomedical Image Clusters extracted with Independent Component Analysis

Christoph Bauer, Fabian J. Theis, Wolfgang Bäumler, Elmar W. Lang

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

A neural network model for the identification and classification of malign and benign skin lesions from ALA-induced fluorescence images is presented. A self-organizing feature map or generative topographic mapping is used to cluster images patches according to their inherent local features which then can be extracted with ICA. These components are used to distinguish skin cancer from benign lesions achieving an average classification rate of 70% so far.

Original languageEnglish
Pages81-84
Number of pages4
StatePublished - 2003
Externally publishedYes
EventInternational Joint Conference on Neural Networks 2003 - Portland, OR, United States
Duration: 20 Jul 200324 Jul 2003

Conference

ConferenceInternational Joint Conference on Neural Networks 2003
Country/TerritoryUnited States
CityPortland, OR
Period20/07/0324/07/03

Fingerprint

Dive into the research topics of 'Local Features in Biomedical Image Clusters extracted with Independent Component Analysis'. Together they form a unique fingerprint.

Cite this