title: Automated description of colours in polarized-light surface microscopy images of melanocytic lesions.
abstract: The aim of this study was to develop a computerized method for the identification and description of colour areas in melanocytic lesion images based on an approach mimicking the human perception of colours. A colour palette comprising six colour groups (black, dark brown, light brown, blue-grey, red and white) was created by selecting single colour components within melanocytic lesion images acquired using a digital videomicroscope, and was implemented in the image analysis program. For each colour region, the area, the distance from the lesion centroid, the spread, the colour area distribution in the internal and the external part of the lesion, and asymmetries were assessed on 604 melanocytic lesion images in our image database. Black, white and blue-grey colour areas were detected more frequently in melanomas compared with naevi. Moreover, significant differences in colour descriptors were observed for each colour group, showing that colour areas are more unevenly distributed in melanomas compared with naevi. Using a discriminant analysis approach, the extension of dark, white and blue-grey areas and some descriptors of the distribution of the colour areas were identified as the most relevant colour parameters for differentiating between benign and malignant lesions. In conclusion, our automatic procedure breaks down the image into the colour areas used in the clinical examination process, and also supplies a description of their extension and distribution, with parameters that correlate with the clinical concepts of regularity and homogeneity.
authors.affiliation: Department of Dermatology, University of Modena and Reggio Emila, 41100 Modena, Italy.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Pellacani
authors.forename: Costantino
authors.initials: C
authors.lastname: Grana
authors.forename: Stefania
authors.initials: S
authors.lastname: Seidenari
mesh_terms: D001331:Automation / Q000379:methods; D003116:Color; D003937:Diagnosis, Differential; D016002:Discriminant Analysis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008545:Melanoma / Q000175:diagnosis / Q000473:pathology*; D008859:Microscopy, Polarization / Q000379:methods*; D018715:Microscopy, Video; D009508:Nevus, Pigmented / Q000175:diagnosis / Q000473:pathology*; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000175:diagnosis / Q000473:pathology*