CVJul 24, 2018
ISIC 2017 Skin Lesion Segmentation Using Deep Encoder-Decoder Network
arXiv:1807.09083v11 citations
Originality Synthesis-oriented
AI Analysis
This work addresses skin lesion segmentation for medical imaging, but it appears incremental as it builds on existing encoder-decoder methods for a specific challenge.
The paper tackled skin lesion segmentation for the ISBI Challenge 2018 by using a deep encoder-decoder network with novel data augmentation and multi-model comparison, achieving results as part of the challenge validation.
This paper summarizes our method and validation results for part 1 of the ISBI Challenge 2018. Our algorithm makes use of deep encoder-decoder network and novel skin lesion data augmentation to segment the challenge objective. Besides, we also propose an effective testing strategy by applying multi-model comparison.