Author(s): Karthiga M, Priyadarshini R K, Bazila Banu A

Email(s): karthigam@bitsathy.ac.in

DOI: 10.5958/0974-360X.2020.00230.9   

Address: Karthiga M1, Priyadarshini R K2, Bazila Banu A3
Dept. of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India.
*Corresponding Author

Published In:   Volume - 13,      Issue - 3,     Year - 2020


ABSTRACT:
Computer based analysis has become a most important part in medical industry nowadays. Skin cancer has become a most dreadful disorders and it is can be diagnosed using computer based technique. Dermoscopy images can be used for training the classifier for correct prediction of melanoma. A novel methodology based on deep convolution neural network is utilized for absolute diagnosis of malevolent melanoma. Transfer learning technique is employed along with deep convolution neural network based Inception v3 framework. The outcomes are obtained by utilizing the proposed methodology with a total of 2700 dermoscopic images. Maximum rate of accuracy, sensitivity and specificity are obtained from the proposed implementation. The proposed results outperform the results for classification of skin lesions by dermatologists.


Cite this article:
Karthiga M, Priyadarshini R K, Bazila Banu A. Malevolent Melanoma diagnosis using Deep Convolution Neural Network. Research J. Pharm. and Tech 2020; 13(3):1248-1252. doi: 10.5958/0974-360X.2020.00230.9

Cite(Electronic):
Karthiga M, Priyadarshini R K, Bazila Banu A. Malevolent Melanoma diagnosis using Deep Convolution Neural Network. Research J. Pharm. and Tech 2020; 13(3):1248-1252. doi: 10.5958/0974-360X.2020.00230.9   Available on: https://rjptonline.org/AbstractView.aspx?PID=2020-13-3-35


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