Deep attention-guided fusion network for lesion segmentation
Hengliang Zhu, Yangyang Hao, Lizhuang Ma, Ruixing Li, Hua Wang
TL;DR
This paper presents a deep attention-guided fusion network designed for lesion segmentation, demonstrating its effectiveness in the ISIC 2018 challenge for skin lesion analysis.
Contribution
The paper introduces a novel deep attention-guided fusion network specifically tailored for lesion segmentation tasks.
Findings
Achieved competitive results on the ISIC 2018 validation set.
Demonstrated the effectiveness of attention-guided fusion in lesion segmentation.
Provided a new approach for skin lesion analysis in melanoma detection.
Abstract
We participated the Task 1: Lesion Segmentation. The paper describes our algorithm and the final result of validation set for the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection.
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Taxonomy
TopicsCutaneous Melanoma Detection and Management · Cell Image Analysis Techniques · Visual Attention and Saliency Detection