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Local Features in Biomedical Image Clusters extracted with Independent Component Analysis

Bauer, Christoph, Theis, F., Baeumler, W. and Lang, Elmar W. (2003) Local Features in Biomedical Image Clusters extracted with Independent Component Analysis. In: Proceedings of the International Joint Conference on Neural Networks 2003, IJCNN 2003, Portland, Oregon, July 20 - 24, 2003. IEEE Service Center, Piscataway, NJ, pp. 81-84. ISBN 0-7803-7898-9, 0-7803-7899-7.

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Other URL: http://homepages.uni-regensburg.de/~thf11669/publications/bauer03biomedicalimageclusters_IJCNN03.pdf


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.

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Item type:Book section
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Dewey Decimal Classification:500 Science > 530 Physics
500 Science > 570 Life sciences
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Item ID:1572
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