Skin lesion extraction in dermoscopic images based on colour enhancement and iterative segmentation

  • Authors:
  • Gerald Schaefer;Maher I. Rajab;M. Emre Celebi;Hitoshi Iyatomi

  • Affiliations:
  • School of Engineering and Applied Science, Aston University, Birmingham, UK;Department of Computer Engineering, Umm Al-Qura University, Makkah, Saudi Arabia;Department of Computer Science, Louisiana State University, Shreveport;Department of Electrical Informatics, Hosei University, Tokyo, Japan

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

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Abstract

Accurate extraction of lesion borders is a crucial step in analysing dermoscopic skin lesion images. In this paper we present an effective approach to extracting lesion areas by combining an iterative segmentation algorithm with a preprocessing step that enhances colour information and image contrast. Following the pre-processing, analysis of the image background is conducted by iterative measurements based on median and standard deviation of non-lesion pixels, which in turn facilitates automatic and recurring noise reduction and enhancement. The algorithm does not depend on the use of rigid threshold values as an optimal thresholding algorithm is used to determine the optimal threshold iteratively. Extensive experimental evaluation is carried out on a dataset of 90 dermoscopy images with known ground truths obtained from three expert dermatologists. The results show that our approach is capable of providing good segmentation performance and that the colour enhancement step is indeed crucial as demonstrated by comparison with results obtained from the original RGB images.