title: Colour histogram analysis for melanoma discrimination in clinical images.
abstract: BACKGROUND
  Malignant melanoma, the most deadly form of skin cancer, has a good prognosis if treated in the curable early stages. Colour provides critical discriminating information for the diagnosis of malignant melanoma.
  
  
  METHODS
  This research introduces a three-dimensional relative colour histogram analysis technique to identify colours characteristic of melanomas and then applies these 'melanoma colours' to differentiate benign skin lesions from melanomas. The relative colour of a skin lesion is determined based on subtracting a representative colour of the surrounding skin from each lesion pixel. A colour mapping for 'melanoma colours' is determined using a training set of images. A percent melanoma colour feature, defined as the percentage of the lesion pixels that are melanoma colours, is used for discriminating melanomas from benign lesions. The technique is evaluated using a clinical image data set of 129 malignant melanomas and 129 benign lesions consisting of 40 seborrheic keratoses and 89 nevocellular nevi.
  
  
  RESULTS
  Using the percent melanoma colour feature for discrimination, experimental results yield correct melanoma and benign lesion discrimination rates of 84.3 and 83.0%, respectively.
  
  
  CONCLUSIONS
  The results presented in this work suggest that lesion colour in clinical images is strongly related to the presence of melanoma in that lesion. However, colour information should be combined with other information in order to further reduce the false negative and false positive rates.
authors.affiliation: University of Missouri-Rolla, Department of Electrical and Computer Engineering, 229 Emerson Electric Co, Hall, MO 65409-0040, USA.
authors.forename: Yunus
authors.initials: Y
authors.lastname: Faziloglu
authors.forename: R Joe
authors.initials: RJ
authors.lastname: Stanley
authors.forename: Randy H
authors.initials: RH
authors.lastname: Moss
authors.forename: William
authors.initials: W
authors.lastname: Van Stoecker
authors.forename: Rob P
authors.initials: RP
authors.lastname: McLean
mesh_terms: D000465:Algorithms; D003124:Colorimetry / Q000379:methods*; D003937:Diagnosis, Differential; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D017492:Keratosis, Seborrheic / Q000175:diagnosis* / Q000473:pathology; D008545:Melanoma / Q000175:diagnosis* / Q000473:pathology; D009506:Nevus / Q000175:diagnosis* / Q000473:pathology; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000175:diagnosis* / Q000473:pathology