Separability Analysis of Color Classes on Dermoscopic Images

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Catia S P Silva (Author) Other; Andre R S Marcal (Author) FCUP; Marta A Pereira (Author) Other; Teresa Mendonca (Author) FCUP; Jorge Rozeira (Author) Other

Conference proceedings International

Title: IMAGE ANALYSIS AND RECOGNITION, PT II

Pages: 268-277

9th International Conference on Image Analysis and Recognition (ICIAR)

Aveiro, PORTUGAL, JUN 25-27, 2012

Indexing

ISI Web of Knowledge - 4 Citations

Scopus - 7 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-005-K1H

DOI: 10.1007/978-3-642-31298-4_32

Abstract (EN): Dermoscopy is a non-invasive diagnostic technique for the in vivo observation of pigmented skin lesions used in dermatology. There is currently a great interest in the prospects of automatic image analysis methods for dermoscopy, both to provide quantitative information about a lesion, which can be of relevance for the clinician, and as a stand alone early warning tool. The standard approach in automatic dermoscopic image analysis has usually three stages: (i) segmentation, (ii) feature extraction and selection, (iii) lesion classification. This paper evaluates the potential of an alternative approach based on the Menzies method presence of 1 or more of 6 color classes, indicating that the lesion should be considered a potential melanoma. This method does not require stages (i) and (ii) - lesion segmentation and feature extraction. The Jeffries-Matusita and Transformed Divergence metrics were used to evaluate the color class separability. The preliminary results presented in this paper suggest that a system based on the Menzies method could provide valuable information for automatic dermoscopic image analysis.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 10