Title :
A software tool for the diagnosis of melanomas
Author :
Di Leo, G. ; Paolillo, A. ; Sommella, P. ; Fabbrocini, G. ; Rescigno, O.
Author_Institution :
Dept. of Electr. & Inf. Eng., Univ. of Salerno, Fisciano, Italy
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. It has been presented as faster and with the same accuracy than the traditional ABCD criteria in the diagnosis of melanoma. In this paper a new system for automated diagnosis of melanocytic skin lesions, based on ELM 7 point checklist, is introduced.
Keywords :
cancer; image colour analysis; image texture; medical image processing; patient diagnosis; pattern classification; skin; software packages; ELM 7 point checklist; biomedical image processing; colour parameter; dermatology; melanocytic skin lesion diagnosis; melanomas; pattern classification; software tool; texture parameter; Clinical diagnosis; Image color analysis; Image storage; Lesions; Malignant tumors; Pattern analysis; Pigmentation; Skin cancer; Skin neoplasms; Software tools; Biomedical image processing; artificial intelligence; pattern classification;
Conference_Titel :
Instrumentation and Measurement Technology Conference (I2MTC), 2010 IEEE
Conference_Location :
Austin, TX
Print_ISBN :
978-1-4244-2832-8
Electronic_ISBN :
1091-5281
DOI :
10.1109/IMTC.2010.5488165
