title: Three-phase general border detection method for dermoscopy images using non-uniform illumination correction.
abstract: BACKGROUND
  Computer-aided diagnosis of dermoscopy images has shown great promise in developing a quantitative, objective way of classifying skin lesions. An important step in the classification process is lesion segmentation. Many studies have been successful in segmenting melanocytic skin lesions (MSLs), but few have focused on non-melanocytic skin lesions (NoMSLs), as the wide variety of lesions makes accurate segmentation difficult.
  
  
  METHODS
  We developed an automatic segmentation program for detecting borders of skin lesions in dermoscopy images. The method consists of a pre-processing phase, general lesion segmentation phase, including illumination correction, and bright region segmentation phase.
  
  
  RESULTS
  We tested our method on a set of 107 NoMSLs and a set of 319 MSLs. Our method achieved precision/recall scores of 84.5% and 88.5% for NoMSLs, and 93.9% and 93.8% for MSLs, in comparison with manual extractions from four or five dermatologists.
  
  
  CONCLUSIONS
  The accuracy of our method was competitive or better than five recently published methods. Our new method is the first method for detecting borders of both non-melanocytic and melanocytic skin lesions.
authors.affiliation: BioMaPS Institute, Rutgers University, Piscataway, NJ, USA. knorton4@jhmi.edu
authors.forename: Kerri-Ann
authors.initials: KA
authors.lastname: Norton
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Iyatomi
authors.forename: M Emre
authors.initials: ME
authors.lastname: Celebi
authors.forename: Sumiko
authors.initials: S
authors.lastname: Ishizaki
authors.forename: Mizuki
authors.initials: M
authors.lastname: Sawada
authors.forename: Reiko
authors.initials: R
authors.lastname: Suzaki
authors.forename: Ken
authors.initials: K
authors.lastname: Kobayashi
authors.forename: Masaru
authors.initials: M
authors.lastname: Tanaka
authors.forename: Koichi
authors.initials: K
authors.lastname: Ogawa
mesh_terms: D001185:Artificial Intelligence; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008029:Lighting / Q000379:methods*; D008545:Melanoma / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000473:pathology*