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

fYear

2010

fDate

3-6 May 2010

Firstpage

886

Lastpage

891

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference (I2MTC), 2010 IEEE

Conference_Location

Austin, TX

ISSN

1091-5281

Print_ISBN

978-1-4244-2832-8

Electronic_ISBN

1091-5281

Type

conf

DOI

10.1109/IMTC.2010.5488165

Filename

5488165