Melanoma Prediction using Convolutional Neural Networks

Avantika Shenoy; Bhavin Shewkani; Tarun Utamchandani

Research Article

Melanoma Prediction using Convolutional Neural Networks

by Avantika Shenoy, Bhavin Shewkani, Tarun Utamchandani

International Journal of Computer Applications

Foundation of Computer Science (FCS), NY, USA

Volume 182 - Issue 33

Published: Dec 2018

Authors: Avantika Shenoy, Bhavin Shewkani, Tarun Utamchandani

10.5120/ijca2018918268

PDF

Avantika Shenoy, Bhavin Shewkani, Tarun Utamchandani . Melanoma Prediction using Convolutional Neural Networks. International Journal of Computer Applications. 182, 33 (Dec 2018), 17-20. DOI=10.5120/ijca2018918268

                        @article{ 10.5120/ijca2018918268,
                        author  = { Avantika Shenoy,Bhavin Shewkani,Tarun Utamchandani },
                        title   = { Melanoma Prediction using Convolutional Neural Networks },
                        journal = { International Journal of Computer Applications },
                        year    = { 2018 },
                        volume  = { 182 },
                        number  = { 33 },
                        pages   = { 17-20 },
                        doi     = { 10.5120/ijca2018918268 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }

                        %0 Journal Article
                        %D 2018
                        %A Avantika Shenoy
                        %A Bhavin Shewkani
                        %A Tarun Utamchandani
                        %T Melanoma Prediction using Convolutional Neural Networks%T 
                        %J International Journal of Computer Applications
                        %V 182
                        %N 33
                        %P 17-20
                        %R 10.5120/ijca2018918268
                        %I Foundation of Computer Science (FCS), NY, USA

Abstract

Melanoma is one of the most common types of skin cancer. Early detection of melanoma could prove to be the vital difference. The system proposes the use of neural networks to get a quick and accurate estimate and also determine the probability of skin cancer. The use of convolutional neural network as well as back propagation neural networks ensures that the system will have increased accuracy while the image processing techniques (RGB to grayscale, median filtering, segmentation) are in place to reduce the complexity and requirements of the system.

References

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Ekta Singhal et.al., “Skin Cancer Detection using Artificial Neural Network” Volume 6, No. 1, Jan-Feb 2015 International Journal of Advanced Research in Computer Science
Md. Mahmudur et.al., “A Multiple Expert-Based Melanoma Recognition System for Dermoscopic Images of Pigmented Skin Lesions” Conference Paper · October 2008
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N. Murata, S. Yoshizawa, and S. Amari, ―Learning curves, model selection and complexity of neural networks,‖ in Advances in Neural Information Processing Systems 5, S. Jose Hanson, J. D. Cowan, and C. Lee Giles, ed. San Mateo, CA: Morgan Kaufmann, 1993, pp. 607-614

Index Terms

Computer Science

Information Sciences

No index terms available.

Keywords

CNN-Convolutional Neural Network BPNN-Back Propagation Neural Network SVM-Suport Vector Machines Melanoma- a type of skin cancer that occurs in Melanocytes Skin cancer-abnormal multiplication of skin cells Melanocytes-skin cells that impart colour to the skin.