Segmentation of skin cancer images

L. Xu, M. Jackowski, A. Goshtasby, D. Roseman, S. Bines, C. Yu, A. Dhawan, A. Huntley

Research output: Contribution to journalArticlepeer-review

192 Scopus citations


An automatic method for segmentation of images of skin cancer and other pigmented lesions is presented. This method first reduces a color image into an intensity image and approximately segments the image by intensity thresholding. Then, it refines the segmentation using image edges. Double thresholding is used to focus on an image area where a lesion boundary potentially exists. Image edges are then used to localize the boundary in that area. A closed elastic curve is fitted to the initial boundary, and is locally shrunk or expanded to approximate edges in its neighborhood in the area of focus. Segmentation results from 20 randomly selected images show an average error that is about the same as that obtained by four experts manually segmenting the images.

Original languageEnglish (US)
Pages (from-to)65-74
Number of pages10
JournalImage and Vision Computing
Issue number1
StatePublished - 1999
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Vision and Pattern Recognition


  • Boundary extraction
  • Double thresholding
  • Elastic curve
  • Image segmentation
  • Melanoma
  • Pigmented lesion


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