Opto-Electronic Engineering, Volume. 52, Issue 3, 240279(2025)

Colorectal polyp segmentation via Transformer-based adaptive feature selection

Liming Liang, Ting Kang*, Chengbin Wang, Kangquan Chen, and Yulin Li
Author Affiliations
  • College of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000, China
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    References(22)

    [1] Xie B, Liu Y Q, Li Y L. Colorectal polyp segmentation method combining polarized self-attention and Transformer[J]. Opto-Electron Eng, 51, 240179(2024).

    [2] Lin L, Lv G Z, Wang B et al. Polyp-LVT: polyp segmentation with lightweight vision transformers[J]. Knowledge-Based Syst, 300, 112181(2024).

    [3] Zhang Y, Ma C M, Liu S D et al. Multi-scale feature enhanced Transformer network for efficient semantic segmentation[J]. Opto-Electron Eng, 51, 240237(2024).

    [5] Diakogiannis F I, Waldner F, Caccetta P et al. ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data[J]. ISPRS J Photogramm Remote Sens, 162, 94-114(2020).

    [7] Lou A G, Guan S Y, Ko H et al. CaraNet: context axial reverse attention network for segmentation of small medical objects[J]. Proc SPIE, 12032, 120320D(2022).

    [10] Wu C, Long C, Li S J et al. MSRAformer: multiscale spatial reverse attention network for polyp segmentation[J]. Comput Biol Med, 151, 106274(2022).

    [11] Wang W H, Xie E Z, Li X et al. PVT v2: improved baselines with pyramid vision transformer[J]. Comput Visual Media, 8, 415-424(2022).

    [14] Huo X Z, Sun G, Tian S W et al. HiFuse: hierarchical multi-scale feature fusion network for medical image classification[J]. Biomed Signal Process Control, 87, 105534(2024).

    [17] Bernal J, Sánchez F J, Fernández-Esparrach G et al. WM-DOVA maps for accurate polyp highlighting in colonoscopy: validation vs. saliency maps from physicians[J]. Comput Med Imaging Graphics, 43, 99-111(2015).

    [19] Tajbakhsh N, Gurudu S R, Liang J M. Automated polyp detection in colonoscopy videos using shape and context information[J]. IEEE Trans Med Imaging, 35, 630-644(2016).

    [20] Silva J, Histace A, Romain O et al. Toward embedded detection of polyps in WCE images for early diagnosis of colorectal cancer[J]. Int J Comput Assisted Radiol Surg, 9, 283-293(2014).

    [22] Li D X, Li D H, Liu Y et al. Progressive CNN-transformer semantic compensation network for polyp segmentation[J]. Opt Precis Eng, 32, 2523-2536(2024).

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    Liming Liang, Ting Kang, Chengbin Wang, Kangquan Chen, Yulin Li. Colorectal polyp segmentation via Transformer-based adaptive feature selection[J]. Opto-Electronic Engineering, 2025, 52(3): 240279

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    Paper Information

    Category: Article

    Received: Nov. 29, 2024

    Accepted: Feb. 6, 2025

    Published Online: May. 22, 2025

    The Author Email: Ting Kang (康婷)

    DOI:10.12086/oee.2025.240279

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