RESUMEN
BACKGROUND: The clinical diagnosis of melanoma could be difficult for a general practitioner and, in some cases, for dermatologists. To enhance and support the clinical evaluation of pigmented skin lesions a computer-aided diagnosis has been introduced. MATERIALS AND METHODS: Images of melanocytic lesions (477 total, 42 melanomas and 435 melanocytic nevi) evaluated in epiluminescence microscopy and recorded with x16 magnification were selected. A training set of 22 melanomas and 218 nevi was randomized from the dataset. The test set was formed by the complement (the remaining 20 melanomas and 217 nevi). Furthermore, a set of images consisting of 31 melanomas and 103 nevi was selected to compare the discrimination capacity of three general practitioners and three dermatologists with experience in dermoscopy (2 years), and with the automatic data analysis for the melanoma early detection system (ADAM). Sensitivity and specificity were estimated for observer assessments and computer diagnosis. RESULTS: The entire dataset used to test the implementation of the diagnostic algorithms ADAM showed a good sensitivity and specificity performance. Compared with the physicians, the ADAM system showed a slightly higher diagnostic performance in terms of sensitivity and a lower one in terms of specificity. Dermatologists showed higher levels of specificity, but lower levels in terms of sensitivity, when compared with the general practitioners. CONCLUSION: Image analysis has the potential to distinguish nevi and melanomas and to support the clinical diagnosis of melanocytic lesions by the general practitioner.