title: Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists.
abstract: BACKGROUND
  It is often difficult to differentiate early melanomas from benign melanocytic nevi even by expert dermatologists, and the task is even more challenging for primary care physicians untrained in dermatology and dermoscopy. A computer system can provide an objective and quantitative evaluation of skin lesions, reducing subjectivity in the diagnosis.
  
  
  OBJECTIVE
  Our objective is to make a low-cost computer aided diagnostic tool applicable in primary care based on a consumer grade camera with attached dermatoscope, and compare its performance to that of experienced dermatologists.
  
  
  METHODS
  We propose several new image-derived features computed from automatically segmented dermoscopic pictures. These are related to the asymmetry, color, border, geometry, and texture of skin lesions. The diagnostic accuracy of the system is compared with that of three dermatologists.
  
  
  RESULTS
  With a data set of 206 skin lesions, 169 benign and 37 melanomas, the classifier was able to provide competitive sensitivity (86%) and specificity (52%) scores compared with the sensitivity (85%) and specificity (48%) of the most accurate dermatologist using only dermoscopic images.
  
  
  CONCLUSIONS
  We show that simple statistical classifiers can be trained to provide a recommendation on whether a pigmented skin lesion requires biopsy to exclude skin cancer with a performance that is comparable to and exceeds that of experienced dermatologists.
authors.affiliation: Department of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, Norway. Electronic address: mzortea@gmail.com.
authors.forename: Maciel
authors.initials: M
authors.lastname: Zortea
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, 9038 Tromsø, Norway.
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Schopf
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, 9038 Tromsø, Norway.
authors.forename: Kevin
authors.initials: K
authors.lastname: Thon
authors.affiliation: Department of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, Norway.
authors.forename: Marc
authors.initials: M
authors.lastname: Geilhufe
authors.affiliation: Department of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, Norway.
authors.forename: Kristian
authors.initials: K
authors.lastname: Hindberg
authors.affiliation: Dermatology Office, Venloer Straße 107, 50259 Pulheim, Germany.
authors.forename: Herbert
authors.initials: H
authors.lastname: Kirchesch
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, 9038 Tromsø, Norway.
authors.forename: Kajsa
authors.initials: K
authors.lastname: Møllersen
authors.affiliation: Department of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, Norway.
authors.forename: Jörn
authors.initials: J
authors.lastname: Schulz
authors.affiliation: Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, 9038 Tromsø, Norway.
authors.forename: Stein Olav
authors.initials: SO
authors.lastname: Skrøvseth
authors.affiliation: Department of Mathematics and Statistics, University of Tromsø, 9037 Tromsø, Norway.
authors.forename: Fred
authors.initials: F
authors.lastname: Godtliebsen
mesh_terms: D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D008545:Melanoma / Q000175:diagnosis*; D012878:Skin Neoplasms / Q000175:diagnosis*; D012880:Skin Pigmentation
keywords: Computer-aided diagnosis; Dermoscopy; Melanoma; Pigmented skin lesions; Skin cancer detection; Supervised classification