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 language | English |
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Pages | 81-84 |
Number of pages | 4 |
State | Published - 2003 |
Externally published | Yes |
Event | International Joint Conference on Neural Networks 2003 - Portland, OR, United States Duration: 20 Jul 2003 → 24 Jul 2003 |
Conference
Conference | International Joint Conference on Neural Networks 2003 |
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Country/Territory | United States |
City | Portland, OR |
Period | 20/07/03 → 24/07/03 |