Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks

TL;DR

This paper presents a deep fully convolutional network approach for automatic skin lesion segmentation, validated on the ISIC 2018 challenge dataset for melanoma detection.

Contribution

It introduces a novel deep learning method specifically designed for skin lesion segmentation and demonstrates its effectiveness on a large public dataset.

Findings

Achieved high segmentation accuracy on ISIC 2018 dataset

Outperformed previous methods in the challenge

Validated robustness across diverse lesion types

Abstract

This paper summarizes our method and validation results for the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection - Task 1: Lesion Segmentation