Classification of melanocytic lesions with color and texture analysis using digital image processing

Anal Quant Cytol Histol. 1993 Feb;15(1):1-11.


The incidence of malignant melanoma, the most dangerous skin cancer, has increased rapidly during the last decade, and the figures are still rising. Since well-trained and experienced dermatologists are able to reach only a diagnostic accuracy of about 75% in visual preoperative classification, the discriminating ability of digital image analysis was evaluated in more than 350 malignant melanoma and benign melanocytic lesions that had all been confirmed histologically. Color slides of melanocytic lesions were scanned and digitized. Computer algorithms were programmed in FORTRAN on a DECstation 5000/200. A feature set was calculated describing the texture, color and their distributions as well as asymmetry, size and border of each lesion. These features, together with the histologic diagnosis, were the input in a commercial statistical classification program. In contrast to the accuracy of 75% achievable by the human eye, a correct classification rate of about 92% was reached with the mathematical classifier as compared with the histologic diagnosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Evaluation Studies as Topic
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Melanoma / classification
  • Melanoma / diagnosis
  • Melanoma / pathology*
  • Nevus, Pigmented / classification
  • Nevus, Pigmented / diagnosis
  • Nevus, Pigmented / pathology*
  • Skin Neoplasms / classification
  • Skin Neoplasms / diagnosis
  • Skin Neoplasms / pathology*
  • Skin Pigmentation
  • Software
  • Software Design