Skin Cancer Detection

Table of Contents

1. Introduction
2. How to Run

Introduction

In this project, I have designed an algorithm that can visually diagnose melanoma, the deadliest form of skin cancer. In particular, the algorithm distinguish this malignant skin tumor from two types of benign lesions (nevi and seborrheic keratoses).

The data and objective are pulled from the 2017 ISIC Challenge on Skin Lesion Analysis Towards Melanoma Detection. As part of the challenge, participants were tasked to design an algorithm to diagnose skin lesion images as one of three different skin diseases (melanoma, nevus, or seborrheic keratosis).

How to Run

• Create an anaconda environment
• Install all the requirements
• Make changes to torchvision present in the environment as in this repo.
• Run the notebook to get the results.