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DETECTING IN-SITU MELANOMA USING MULTI PARAMETER EXTRACTION AND NEURAL CLASSIFICATION MECHANISMS
SUBJECT : Computer Science
AUTHOR : Dr Ruksar Fatima
PUBLISHED ON : 12/10/17
NUMBER OF PAGES : ( 18 Pages)
PRICE : Rs 9.9

Computer aided diagnostics systems are widely used for diagnosis of skin lesions. This paper discusses a Multi Parameter Extraction and Classification System () to aimed to enable early detection of skin cancer melanoma. The adopts a supervised machine learning algorithm for classification. The dermoscopic images are represented by extensive parameter sets extracted using a six phase approach. The paper discusses the operation of the  in the training and testing phase. The adoption of the Multilayer Feed Forward Neural Network () classifier is justified, its proficiency in accurately diagnosing and classifying early signs of skin cancer melanoma in dermoscopic images of skin lesions is proved through the experimental results discussed in the manuscript.

     

 
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