Improvement of colon polyp segmentation method based on TransFuse model

Jinkai Ren; Zhengzhu Wen; Han Wang; Yaqian Chen; Zhaohe Wu; Hailian Zhang

doi:10.1117/12.3040492

10 September 2024 Improvement of colon polyp segmentation method based on TransFuse model

Jinkai Ren, Zhengzhu Wen, Han Wang, Yaqian Chen, Zhaohe Wu, Hailian Zhang

Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 132570W (2024) https://doi.org/10.1117/12.3040492
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

To address issues such as fuzzy boundaries, lack of small polyp detection, and image fragmentation in colon polyp segmentation, an enhanced TransFuse model is proposed. By refining the BiFusion and up modules and effectively combining deep and shallow feature information, the improved TransFuse model achieves more accurate colon polyp segmentation. Experimental results on the Kvasir-SEG dataset demonstrate enhancements in accuracy, with increases of 0.7%, 2.3%, and 1.1% in Acc, IOU, and Dice metrics, respectively. Compared to the original model, this approach detects and segments colon polyps more accurately.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinkai Ren, Zhengzhu Wen, Han Wang, Yaqian Chen, Zhaohe Wu, and Hailian Zhang "Improvement of colon polyp segmentation method based on TransFuse model", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 132570W (10 September 2024); https://doi.org/10.1117/12.3040492

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KEYWORDS

Image segmentation

Polyps

Colon

Data modeling

Transformers

Education and training

Ablation

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