Triple branch deep network for polyp image segmentation

Muwei Jian; Yanjie Zhong; Kin-man Lam

doi:10.1117/12.3057381

5 February 2025 Triple branch deep network for polyp image segmentation

Muwei Jian, Yanjie Zhong, Kin-man Lam

Author Affiliations +

Proceedings Volume 13510, International Workshop on Advanced Imaging Technology (IWAIT) 2025; 135100A (2025) https://doi.org/10.1117/12.3057381
Event: International Workshop on Advanced Imaging Technology (IWAIT) 2025, 2025, Douliu City, Taiwan

Abstract

Medical image segmentation is essential for accurately extracting tissue structures or pathological regions from medical images. However, medical image segmentation methods are often influenced by factors such as image noise and irregular shapes, making precise segmentation challenging. To tackle these challenges, this paper proposes a triple-branch medical image segmentation network (TBIB-Net) that incorporates implicit boundary priors. The boundary map, acquired by a boundary detection algorithm, is used to restrict the results of the boundary branch. Extensive experiments indicate that TBIB-Net achieves state-of-the-art performance on publicly available polyp datasets.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Muwei Jian, Yanjie Zhong, and Kin-man Lam "Triple branch deep network for polyp image segmentation", Proc. SPIE 13510, International Workshop on Advanced Imaging Technology (IWAIT) 2025, 135100A (5 February 2025); https://doi.org/10.1117/12.3057381

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