title: Pigment distribution in melanocytic lesion images: a digital parameter to be employed for computer-aided diagnosis.
abstract: OBJECTIVE
  Since in early melanoma (MM) and especially in in situ MM differential structures, which are diagnostic for MM may be lacking, pigment distribution asymmetry represents an important diagnostic feature. Our aim was to automatically assess pigment distribution in images referring to MMs, atypical nevi (AN) and clearly benign nevi (BN), and to evaluate the diagnostic capability of numerical parameters describing a non homogeneous distribution of pigmentation.
  
  
  METHODS
  An image analysis program enabling the numerical assessment of pigment distribution in melanocytic lesions (ML), based on evaluation and comparison of red, green, blue (RGB) colour components inside image colour blocks, was employed on 459 videomicroscopic digital images, referring to 95 MMs, 76 AN and 288 BN.
  
  
  RESULTS
  Significant differences in pigment distribution parameters (mean RGB distance, variance and maximum distance) between the three ML populations were observed, permitting a good discrimination of MMs. On the test set comprising 230 lesion images, the area under the curve value of the receiver operating characteristic curve was 0.933. For a D score equal to 0, corresponding to the best diagnostic accuracy (86.6%), a sensitivity of 87.5% and a specificity of 85.7% were obtained.
  
  
  CONCLUSIONS
  This original evaluation method for digital pigment distribution, based on mathematical description and comparison of colours in different image blocks, provides numerical parameters to be implemented in image analysis programs for computer-aided MM diagnosis.
authors.affiliation: Department of Dermatology, University of Modena and Reggio Emilia, Modena, Italy. seidenari.stefania@unimore.it
authors.forename: S
authors.initials: S
authors.lastname: Seidenari
authors.forename: G
authors.initials: G
authors.lastname: Pellacani
authors.forename: C
authors.initials: C
authors.lastname: Grana
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism; D003124:Colorimetry / Q000379:methods; D046169:Dermoscopy / Q000379:methods; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008543:Melanins / Q000378:metabolism*; D008545:Melanoma / Q000378:metabolism* / Q000473:pathology*; D008856:Microscopy, Fluorescence / Q000379:methods; D018715:Microscopy, Video / Q000379:methods; D009506:Nevus / Q000378:metabolism* / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012878:Skin Neoplasms / Q000378:metabolism* / Q000473:pathology*; D012880:Skin Pigmentation; D014018:Tissue Distribution
chemical_list: D014408:Biomarkers, Tumor; D008543:Melanins