title: Lesion border detection in dermoscopy images.
abstract: BACKGROUND
  Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, computerized analysis of dermoscopy images has become an important research area. One of the most important steps in dermoscopy image analysis is the automated detection of lesion borders.
  
  
  METHODS
  In this article, we present a systematic overview of the recent border detection methods in the literature paying particular attention to computational issues and evaluation aspects.
  
  
  CONCLUSIONS
  Common problems with the existing approaches include the acquisition, size, and diagnostic distribution of the test image set, the evaluation of the results, and the inadequate description of the employed methods. Border determination by dermatologists appears to depend upon higher-level knowledge, therefore it is likely that the incorporation of domain knowledge in automated methods will enable them to perform better, especially in sets of images with a variety of diagnoses.
authors.affiliation: Dept. of Computer Science, Louisiana State Univ., Shreveport, LA, USA. ecelebi@lsus.edu
authors.forename: M Emre
authors.initials: ME
authors.lastname: Celebi
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Iyatomi
authors.forename: Gerald
authors.initials: G
authors.lastname: Schaefer
authors.forename: William V
authors.initials: WV
authors.lastname: Stoecker
mesh_terms: D001185:Artificial Intelligence; D046169:Dermoscopy / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D012878:Skin Neoplasms / Q000175:diagnosis* / Q000473:pathology*