ISIC 2017 - Skin Lesion Analysis Towards Melanoma Detection

TL;DR

This paper presents a deep learning system for skin lesion segmentation and classification, advancing melanoma detection by participating in the ISIC 2017 challenge.

Contribution

It introduces deep convolutional network algorithms specifically designed for lesion segmentation and classification in melanoma detection.

Findings

Achieved competitive performance in the ISIC 2017 challenge

Demonstrated effectiveness of deep convolutional networks for skin lesion analysis

Contributed to improved accuracy in melanoma detection

Abstract

Our system addresses Part 1, Lesion Segmentation and Part 3, Lesion Classification of the ISIC 2017 challenge. Both algorithms make use of deep convolutional networks to achieve the challenge objective.