Automatic Detection of Blue-white Veil and Related Structures in Dermoscopy Images

Abstract

Dermoscopy is a non-invasive skin imaging technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. One of the most important features for the diagnosis of melanoma in dermoscopy images is the blue-white veil (irregular, structureless areas of confluent blue pigmentation with an overlying white “ground-glass” film). In this article, we present a machine learning approach to the detection of blue-white veil and related structures in dermoscopy images. The method involves contextual pixel classification using a decision tree classifier. The percentage of blue-white areas detected in a lesion combined with a simple shape descriptor yielded a sensitivity of 69.35% and a specificity of 89.97% on a set of 545 dermoscopy images. The sensitivity rises to 78.20% for detection of blue veil in those cases where it is a primary feature for melanoma recognition.

Department(s)

Chemistry

Second Department

Electrical and Computer Engineering

Sponsor(s)

James A. Schlipmann Melanoma Cancer Foundation
National Institutes of Health (U.S.)
National Science Foundation (U.S.)
Texas Workforce Commission

Keywords and Phrases

Melanoma

International Standard Serial Number (ISSN)

0895-6111

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2008 Elsevier, All rights reserved.

Publication Date

01 Dec 2008

Link to Full Text

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