An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Colour Image Processing Model for Melanoma Detection
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
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Diagnosis of benign and malign skin lesions is currently mostly relying on visual assessment and frequent biopsies performed by dermatologists. As the timely and correct diagnosis of these skin lesions is one of the most important factors in the therapeutic outcome, leveraging new technologies to assist the dermatologist seems natural. Complicating matters is a blood cancer called Cutaneous T-Cell Lymphoma, which also exhibits symptoms as skin lesions. We propose a framework using optical spectroscopy and a multi-spectral classification scheme using support vector machines to assist dermatologists in diagnosis of normal, benign and malign skin lesions. As a first step we show successful classification (94.9%) of skin lesions from regular skin in 48 patients based on 436 measurements. This forms the basis for future automated classification of different skin lesions in diseased patients.