Skin cancer is one of the most common types of cancer in the global Caucasian population [1] and is a leading cause of death in humans. Its most aggressive form is melanoma (M), for which the clinical evaluation is limited by the long time frame, the variety of interpretations, and the difficulty in distinguishing it from nevi (N). These problems necessitate the development of computer-aided diagnostic systems, which involve the automatic classification of dermoscopic images.
Convolutional Neural Networks for Skin Lesion Image Classification / Grignaffini, F.; Barbuto, F.; Troiano, M.; Simeoni, P.; Mangini, F.; Piazzo, L.; Cantisani, C.; Frezza, F.. - (2024). (Intervento presentato al convegno Workshop Sharescience 2024 tenutosi a Roma).
Convolutional Neural Networks for Skin Lesion Image Classification
F. Grignaffini;M. Troiano;P. Simeoni;F. Mangini;L. Piazzo;C. Cantisani;F. Frezza
2024
Abstract
Skin cancer is one of the most common types of cancer in the global Caucasian population [1] and is a leading cause of death in humans. Its most aggressive form is melanoma (M), for which the clinical evaluation is limited by the long time frame, the variety of interpretations, and the difficulty in distinguishing it from nevi (N). These problems necessitate the development of computer-aided diagnostic systems, which involve the automatic classification of dermoscopic images.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
