Versatile learning by sample strategy to perform statistical pattern classification in biomedical images

Bernard Fertil; Djamel Brahmi; Nathalie Cassoux; Camille Serruys; Alain Giron

doi:10.1117/12.420927

4 April 2001 Versatile learning by sample strategy to perform statistical pattern classification in biomedical images

Bernard Fertil, Djamel Brahmi, Nathalie Cassoux, Camille Serruys, Alain Giron

Proceedings Volume 4305, Applications of Artificial Neural Networks in Image Processing VI; (2001) https://doi.org/10.1117/12.420927
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

In this paper, the architecture of an all-round pattern recognition system is described together with some of the results obtained when dealing with the characterization of infected areas in retinal angiograms. Several tricky aspects of the implementation are discussed. In particular, special attention is given to the feature-extraction scheme and the learning data base pertinency.

Citation Download Citation

Bernard Fertil, Djamel Brahmi, Nathalie Cassoux, Camille Serruys, and Alain Giron "Versatile learning by sample strategy to perform statistical pattern classification in biomedical images", Proc. SPIE 4305, Applications of Artificial Neural Networks in Image Processing VI, (4 April 2001); https://doi.org/10.1117/12.420927

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