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

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).