title: Obtaining malignant melanoma indicators through statistical analysis of 3D skin surface disruptions.
abstract: OBJECTIVE
  It has been observed that disruptions in skin patterns are larger for malignant melanoma (MM) than benign lesions. In order to extend the classification results achieved for 2D skin patterns, this work intends to investigate the feasibility of lesion classification using 3D skin surface texture, in the form of surface normals acquired from a previously built six-light photometric stereo device.
  
  
  METHODS
  The proposed approach seeks to separate MM from benign lesions through analysis of the degree of surface disruptions in the tilt and slant direction of surface normals, so called skin tilt pattern and skin slant pattern. A 2D Gaussian function is used to simulate a normal region of skin for comparison with a lesion's observed tilt and slant patterns. The differences associated with the two patterns are estimated as the disruptions in the tilt and slant pattern respectively for lesion classification.
  
  
  RESULTS
  Preliminary studies on 11 MMs and 28 benign lesions have given Receiver operating characteristic areas of 0.73 and 0.85 for tilt and slant pattern, respectively, which are better than 0.65 previously obtained for the skin line direction using the same samples.
  
  
  CONCLUSIONS
  This paper has demonstrated an important application of 3D skin texture for computer-assisted diagnosis of MM in vivo. By taking advantage of the extra dimensional information, preliminary studies suggest that some improvements over the existing 2D skin line pattern approach for the differentiation between MM and benign lesions.
authors.affiliation: Machine Vision Laboratory, DuPont Building, University of the West of England, Bristol Frenchay Campus, Bristol BS16 1QY, UK. robin_ding@hotmail.com
authors.forename: Yi
authors.initials: Y
authors.lastname: Ding
authors.forename: Lyndon
authors.initials: L
authors.lastname: Smith
authors.forename: Melvyn
authors.initials: M
authors.lastname: Smith
authors.forename: Jiuai
authors.initials: J
authors.lastname: Sun
authors.forename: Robert
authors.initials: R
authors.lastname: Warr
mesh_terms: D003627:Data Interpretation, Statistical; D046169:Dermoscopy / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008545:Melanoma / Q000473:pathology*; D010780:Photogrammetry / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000473:pathology*