Skin Cancer Detection and Segmentation Using Convolutional Neural Network Models

Abstract

Skin cancer is known as one of the killing diseases in humans around the world. In this paper, melanoma skin cancer images are classified and the cancer regions are segmented using Convolutional Neural Networks (CNN). The skin images are data augmented into high number of skin images for obtaining the high classification accuracy. Then, CNN classifier is used to classify the skin image into either melanoma or normal. Finally, morphological segmentation method is used to segment the cancer regions. The simulation results are obtained by applying the proposed methods on ISIC and HAM dataset skin images.