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

M. Emre Celebi, Hitoshi Iyatomi, William V. Stoecker, Randy H. Moss, Harold S. Rabinovitz, Giuseppe Argenziano, H. Peter Soyer

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)670-677
Number of pages8
JournalComputerized Medical Imaging and Graphics
Volume32
Issue number8
DOIs
Publication statusPublished - Dec 2008

Keywords

  • Blue-white veil
  • Contextual pixel classification
  • Decision tree classifier
  • Dermoscopy
  • Melanoma

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Health Informatics
  • Radiological and Ultrasound Technology
  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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