Multi-scale nested UNet with transformer for colorectal polyp segmentation.

Journal: Journal of applied clinical medical physics
Published Date: Jun 1, 2024

Abstract

BACKGROUND: Polyp detection and localization are essential tasks for colonoscopy. U-shape network based convolutional neural networks have achieved remarkable segmentation performance for biomedical images, but lack of long-range dependencies modeling limits their receptive fields.

Authors

  • Zenan Wang
  • Zhen Liu
    School of Pharmacy, Fudan University, PR China; Analytical Service Unit, WuXi AppTec (Shanghai) Co., Ltd, Shanghai, 200131, PR China.
  • Jianfeng Yu
    School of Big Data and Computer Science, Guizhou Normal University, Guiyang, 550025, China.
  • Yingxin Gao
    Department of Gastroenterology, Beijing Chaoyang Hospital, the Third Clinical Medical College of Capital Medical University, Beijing, China.
  • Ming Liu
    School of Land Engineering, Chang'an University, Xi'an 710064, China; Xi'an Key Laboratory of Territorial Spatial Information, School of Land Engineering, Chang'an University, Xi'an 710064, China. Electronic address: mingliu@chd.edu.cn.

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