A cooperative approach for the diagnosis of the melanoma.
In this work we present a decision support system for the melanoma diagnosis using individual methods and the collaboration between these methods. The system designed uses a photograph of the lesion and it makes a preprocessing task to extract the region of interest. Then, several characteristics of the image are analyzed, studying with different methods the degree of malignity; the methods used are based in Bayesian rules and in neural networks. Finally, each individual decision from each method contributes in some way to the final decision. The classification rate obtained with the cooperative approach is above 92%.
Ruiz
D
D
Computer Technology Department, University of Alicante, P.O 99 03080 Spain. druiz@dtic.ua.es
Berenguer
V J
VJ
Soriano
A
A
Martin
J
J
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008545:Melanoma / Q000175:diagnosis*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000175:diagnosis*