On the role of texture and color in the classification of dermoscopy images

Annu Int Conf IEEE Eng Med Biol Soc. 2012:2012:4402-5. doi: 10.1109/EMBC.2012.6346942.

Abstract

This paper addresses the detection of melanoma lesions in dermoscopy images, using texture and color features. Although melanoma detection has been studied in several works, using different types of texture, color and shape features, it is not always clear what is the role of each set of features and which features are most discriminative. This papers aims at clarifying the role of texture and color features. Furthermore, the proposed systems is based on features which can be easily implemented and tested by other researchers. It is concluded that both types of features achieve good detection scores when used alone. The best results (SE=94.1%, SP=77.4%) are achieved by combining them both.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Colorimetry / methods*
  • Dermoscopy / methods*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Melanoma / pathology*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Skin Neoplasms / pathology*