Automatic Detection of Blue-white Veil and Related Structures in Dermoscopy Images
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.
M. E. Celebi et al., "Automatic Detection of Blue-white Veil and Related Structures in Dermoscopy Images," Computerized Medical Imaging and Graphics, Elsevier, Dec 2008.
The definitive version is available at http://dx.doi.org/10.1016/j.compmedimag.2008.08.003
Electrical and Computer Engineering
James A. Schlipmann Melanoma Cancer Foundation
National Institute of Health (U.S.)
National Science Foundation (U.S.)
Texas Workforce Commission
Library of Congress Subject Headings
Article - Journal
© 2008 Elsevier, All rights reserved.