Reviewing State of the Art AI Systems for Skin Cancer Diagnosis

Authors:
Ilias Maglogiannis;Charalampos Doukas
Affiliations:
Univ. of Aegean, Dept. of Information and Communication Systems Engineering 83200 Karlovasi, Greece;Univ. of Aegean, Dept. of Information and Communication Systems Engineering 83200 Karlovasi, Greece
Venue:
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Year:
2007

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Abstract

In the recent years artificial intelligence and vision-based diagnostic systems for dermatology have demonstrated significant progress. In this chapter, we review these systems by firstly presenting the installation, the visual features used for skin lesion classification and methods for defining them. Then we describe how to extract these features through digital image processing methods, i.e., segmentation, registration, border detection, color and texture processing and then we present how to use the extracted features for skin lesion classification by employing artificial intelligence methods, i.e., Discriminant Analysis, Neural Networks, Support Vector Machines, Wavelets. We finally list all the existing systems found in literature that deal with the specific problem.