title: Pigment network-based skin cancer detection.
abstract: Diagnosing skin cancer in its early stages is a challenging task for dermatologists given the fact that the chance for a patient's survival is higher and hence the process of analyzing skin images and making decisions should be time efficient. Therefore, diagnosing the disease using automated and computerized systems has nowadays become essential. This paper proposes an efficient system for skin cancer detection on dermoscopic images. It has been shown that the statistical characteristics of the pigment network, extracted from the dermoscopic image, could be used as efficient discriminating features for cancer detection. The proposed system has been assessed on a dataset of 200 dermoscopic images of the `Hospital Pedro Hispano' [1] and the results of cross-validation have shown high detection accuracy.
authors.forename: Naser
authors.initials: N
authors.lastname: Alfed
authors.forename: Fouad
authors.initials: F
authors.lastname: Khelifi
authors.forename: Ahmed
authors.initials: A
authors.lastname: Bouridane
authors.forename: Huseyin
authors.initials: H
authors.lastname: Seker
mesh_terms: D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000175:diagnosis*; D012880:Skin Pigmentation