title: Can early malignant melanoma be differentiated from atypical melanocytic nevus by in vivo techniques?: Part II. Automatic machine vision classification.
abstract: OBJECTIVE
  Differentiation between early (Breslow thickness less than 1 mm) malignant melanoma (MM) and atypical melanocytic nevus (AMN) remains a challenge even to trained clinicians. The purpose of this study is to determine the feasibility of reliable discrimination between early MM and AMN with noninvasive, objective, automatic machine vision techniques.
  
  
  METHODS
  A data base of 104 digitized dermoscopic color transparencies of melanocytic lesions was used to develop and test our computer-based algorithms for classification of such lesions as malignant (MM) or benign (AMN). Histopathologic diagnoses (30 MM and 74 AMN) were used as the "gold standard" for training and testing the algorithms.
  
  
  RESULTS
  A fully automatic, objective technique for differentiating between early MM and AMN from their dermoscopic digital images was developed. The multiparameter linear classifier was trained to provide 100% sensitivity for MM. In the blind test, this technique did not miss a single MM and its specificity was comparable to that of skilled dermatologists.
  
  
  CONCLUSIONS
  Reliable differentiation between early MM and AMN with high sensitivity is possible using machine vision techniques to analyze digitized dermoscopic lesion images.
authors.affiliation: Electro-Optical Sciences, Inc., Irvington, NYThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, Skin and Cancer Unit, New York, NY, USA.
authors.forename: D
authors.initials: D
authors.lastname: Gutkowicz-Krusin
authors.affiliation: Electro-Optical Sciences, Inc., Irvington, NYThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, Skin and Cancer Unit, New York, NY, USA.
authors.forename: M
authors.initials: M
authors.lastname: Elbaum
authors.affiliation: Electro-Optical Sciences, Inc., Irvington, NYThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, Skin and Cancer Unit, New York, NY, USA.
authors.forename: P
authors.initials: P
authors.lastname: Szwaykowski
authors.affiliation: Electro-Optical Sciences, Inc., Irvington, NYThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, Skin and Cancer Unit, New York, NY, USA.
authors.forename: A W
authors.initials: AW
authors.lastname: Kopf
keywords: atypical melanocytic nevus; classification; malignant melanoma; multispectral imaging