Automatic detection of blue-white veil and related structures in dermoscopy images

Comput Med Imaging Graph. 2008 Dec;32(8):670-7. doi: 10.1016/j.compmedimag.2008.08.003. Epub 2008 Sep 19.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Artificial Intelligence*
  • Decision Trees
  • Dermatology / methods
  • Dermoscopy / methods*
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Melanoma / diagnosis*
  • Melanoma / pathology*
  • Nevus, Blue / diagnosis*
  • Nevus, Blue / pathology
  • Pattern Recognition, Automated / methods
  • Sensitivity and Specificity
  • Skin Neoplasms / diagnosis*
  • Skin Neoplasms / pathology*
  • Skin Pigmentation