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A Deep learning Framework for Eye Melanoma Detection employing Convolutional Neural Network | IEEE Conference Publication | IEEE Xplore

A Deep learning Framework for Eye Melanoma Detection employing Convolutional Neural Network


Abstract:

Eye melanoma is a rare disease but according to malignancy, it is the most common type of cancer. Just like other types of cancers, it is curable for most of the cases if...Show More

Abstract:

Eye melanoma is a rare disease but according to malignancy, it is the most common type of cancer. Just like other types of cancers, it is curable for most of the cases if diagnosed properly but the process of diagnosis is quite challenging and is the most problematic issue in the treatment of eye melanoma. This paper presents an automated eye melanoma detection method using a convolutional neural network (CNN). 170 pre-diagnosed samples are taken from a standard database followed by pre-processing to lower resolution samples and finally fed to the CNN architecture. The proposed work eliminates separate feature extraction as well as the classification for the detection of eye melanoma. Although the proposed method requires a huge computation, a high accuracy rate of 91.76% is achieved outperforming the eye melanoma detection using an artificial neural network (ANN).
Date of Conference: 18-19 January 2019
Date Added to IEEE Xplore: 20 February 2020
Electronic ISBN:978-1-7281-0697-7
Conference Location: Kolkata, India

I. Introduction

Eye Melanoma is one of the most deadly phases of cancer [1]–[2]. According to the National Cancer Institute (NCI), the young adult age group is the common victim of carcinoma, a form of eye melanoma. Though this form of cancer is a common cause of malignancy, ocular or eye melanoma is the rarest among all. 95% of cases there is a high chance of survival for patients if diagnosed at a very early stage of melanoma. But detection of this disease is just as difficult and rare as ocular melanoma is.

References

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