Identification of Melanoma from Hyperspectral Pathology Image Using 3D Convolutional Networks

In this work, Skin cancer is the uncontrolled growth of strange skin cells. It occurs when unrepaired DNA damages to skin cells triggers mutations, or genetic defects, that lead the skin cells to multiply readily and form malignant tumors. Image processing is a commonly used method for skin cancer detection from the appearance of affected area on the skin.

The ultimate aim of this paper is to implement cost-effective emergency support systems, to process the medical images. Which are calculated using MATLAB from skin cancer images intending to developing diagnostic algorithms that might improve triage practices in the emergency department. Here in this project, we will classify skin cancer using Convolutional Neural Networks (CNN).

Experimental results show that this model is better than Support Vector Machine (SVM) feature classifier a machine learning technique. This classification method proves to be more efficient for the skin cancer classification.

Keywords: Image processing, skin cancer, diagnostic algorithms, Convolutional Neural Networks (CNN), Support Vector Machine (SVM), Machine Learning.