A decision support system for the diagnosis of melanoma: A comparative approach

Authors:
Daniel Ruiz;Vicente Berenguer;Antonio Soriano;BeléN SáNchez
Affiliations:
Department of Computer Technology, University of Alicante, Spain;IBIS Research Group, University of Alicante, Spain;Department of Computer Technology, University of Alicante, Spain;Agost Health Centre, National Health Service, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 0
Cited 3

Pattern classification of dermoscopy images: A perceptually uniform model

Pattern Recognition
Methodological review: Computerized analysis of pigmented skin lesions: A review

Artificial Intelligence in Medicine
A two-stage approach for discriminating melanocytic skin lesions using standard cameras

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	12.05

Visualization

Abstract

Melanoma is the most deathful of all skin cancers and the number of cases grows every year. The extirpation in early phases implies a high degree of survival so it is fundamental to diagnose it as soon as possible. In this paper we present a clinical decision support system for melanoma diagnosis using as input an image set of the skin lesion to be diagnosed. The system analyses the image sequence to extract the affected area, determinates the characteristics which indicate the degree of damage and, according to them, it makes a decision. Several methods of classification are proposed: a multilayered perceptron, a Bayesian classifier and the algorithm of the K nearest neighbours. These methods work independently and also in combination making a collaborative decision support system. The classification rates obtained are around 87%.