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Supervised learning of melanocytic skin lesion images

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1 Author(s)
Grzegorz Surowka ; Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Krakow, Poland

We use MLP and SVM supervised learning methods to discover patterns in the pigmented skin lesion images. This methodology can be treated as a non-invasive approach to early diagnosis of melanoma. Our feature set is composed of wavelet-based multi-resolution filters of the dermoscopy images. Feature selection is done by the Ridge linear models. Discriminating malicious from benign lesion images with the selected classifiers has sensitivity of 89.2-94.7% and specificity of 85-95%.

Published in:

2008 Conference on Human System Interactions

Date of Conference:

25-27 May 2008