A Detection and Segmentation Architecture for Skin Lesion Segmentation on Dermoscopy Images
This work addresses a domain-specific problem in medical imaging for melanoma detection, with incremental improvements in segmentation accuracy.
The authors tackled skin lesion segmentation in dermoscopy images by developing a two-stage method with optimized training and ensemble post-processing, achieving state-of-the-art performance and winning first place in the ISIC 2018 challenge.
This report summarises our method and validation results for the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection - Task 1: Lesion Segmentation. We present a two-stage method for lesion segmentation with optimised training method and ensemble post-process. Our method achieves state-of-the-art performance on lesion segmentation and we win the first place in ISIC 2018 task1.