The assessment of asymmetry is essential for melanoma (MM) diagnosis, both when using a heuristic approach and when employing semiquantitative methods on dermoscopic images. The aim of our study was to develop and validate a software for assessment of asymmetry in melanocytic lesion images, based on evaluation of color symmetry, and to compare the automatic evaluation to the one performed by human observers. An image analysis program enabling the numerical assessment of asymmetry in melanocytic lesions, based on evaluation and comparison of RGB color components inside image color blocks, was employed on 459 videomicroscopic digital images, referring to 95 melanomas (MMs), 76 atypical nevi (AN) and 288 clearly benign nevi (BN). Clinical evaluation of asymmetry on dermoscopic images was performed on the same image set employing a 0–1 scoring system. Asymmetry judgement was expressed by the clinicians for 12.8% of BN, 44.7% of AN, and for 64.2% of MMs, whereas the computer identified 6.9% of BN, 27.6% of AN, and 87.4% of MMs as asymmetric. Sensitivity and specificity of clinical judgement were 64.2 and 80.5%, respectively, whereas for computer evaluation, a sensitivity of 87.5% and a specificity of 85.7% were obtained. Numerical parameters (mean RGB distance, variance and maximum distance) referring to MMs were significantly higher both with respect to BN and AN. This innovative method for automatic asymmetry evaluation, based on the mathematical description of color distribution in different image blocks, provides numerical parameters for employment in computer-aided melanoma diagnosis.
A computer description of asymmetry in melanocytic lesion images based on color distribution / Seidenari, Stefania; Pellacani, Giovanni; A., Martella; Grana, Costantino. - In: JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY. - ISSN 0926-9959. - STAMPA. - 18 suppl.2:(2004), pp. 513-513. (Intervento presentato al convegno 13th Congress of the European Academy of Dermatology (EADV) tenutosi a Florence, Italy nel Nov 17-21).