Early detection of melanoma is one of the greatest challenges of dermatologic practice today. A new diagnostic method, the "ELM 7 point checklist", defines a set of seven features, based on colour and texture parameters, which describe the malignancy of a lesion. This paper describes image processing algorithms which estimate chromatic and shape parameters involved in the detection of the occurrence of two important criteria of the "7-point checklist" method.
Automated application of the "7-point checklist" diagnosis method for skin lesions: Estimation of chromatic and shape parameters / Betta, G; Di Leo, G; Fabbrocini, Gabriella; Paolillo, A; Scalvenzi, Massimiliano. - 3:(2005), pp. 1818-1822. (Intervento presentato al convegno IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference tenutosi a Ottawa, Canada nel 16-19/05/2005) [10.1109/IMTC.1999.776134].
Automated application of the "7-point checklist" diagnosis method for skin lesions: Estimation of chromatic and shape parameters
FABBROCINI, GABRIELLA;SCALVENZI, MASSIMILIANO
2005
Abstract
Early detection of melanoma is one of the greatest challenges of dermatologic practice today. A new diagnostic method, the "ELM 7 point checklist", defines a set of seven features, based on colour and texture parameters, which describe the malignancy of a lesion. This paper describes image processing algorithms which estimate chromatic and shape parameters involved in the detection of the occurrence of two important criteria of the "7-point checklist" method.| File | Dimensione | Formato | |
|---|---|---|---|
|
Automated application of the.docx
non disponibili
Tipologia:
Abstract
Licenza:
Accesso privato/ristretto
Dimensione
13.46 kB
Formato
Microsoft Word XML
|
13.46 kB | Microsoft Word XML | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
