Paper Info
Title
Separability analysis of color classes on dermoscopic images
Abstract
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.
Year
DOI
Venue
2012
10.1007/978-3-642-31298-4_32
ICIAR (2)
Keywords
Field
DocType
automatic dermoscopic image analysis,feature extraction,automatic image analysis method,separability analysis,lesion classification,alternative approach,color class separability,pigmented skin lesion,lesion segmentation,color class,menzies method
Computer vision,Pattern recognition,Pigmented skin,Lesion,Computer science,Segmentation,Feature extraction,Artificial intelligence,Class separability,Lesion segmentation
Conference
Volume
ISSN
Citations 
7325
0302-9743
0
PageRank 
References 
Authors
0.34
2
5
Name
Order
Citations
PageRank
Cátia S. P. Silva161.16
André R. S. Marçal213714.47
Marta A. Pereira330.78
Teresa Mendonça49819.85
Jorge Rozeira51327.44