Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks

2018/07/17 by Hongming Xu, Xu, Hongming, Tae Hyun Hwang +1
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · #AI in cancer detection #Cell Image Analysis Techniques #Computer Vision and Pattern Recognition (cs.CV) #Cutaneous Melanoma Detection and Management #FOS: Computer and information sciences

paper · pdf · doi:10.48550/arxiv.1807.06466

openalex publication_date 2018/07/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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

Related

• Automatic segmentation of skin lesions using deep learning
• Skin Lesion Analysis Towards Melanoma Detection via End-to-end Deep Learning of Convolutional Neural Networks
• ISIC 2017 - Skin Lesion Analysis Towards Melanoma Detection
• Deep attention-guided fusion network for lesion segmentation
• DSNet: Automatic Dermoscopic Skin Lesion Segmentation