BiU-net: A dual-branch structure based on two-stage fusion strategy for biomedical image segmentation.

Journal: Computer methods and programs in biomedicine
Published Date: May 18, 2024

Abstract

BACKGROUND AND OBJECTIVE: Computer-based biomedical image segmentation plays a crucial role in planning of assisted diagnostics and therapy. However, due to the variable size and irregular shape of the segmentation target, it is still a challenge to construct an effective medical image segmentation structure. Recently, hybrid architectures based on convolutional neural networks (CNNs) and transformers were proposed. However, most current backbones directly replace one or all convolutional layers with transformer blocks, regardless of the semantic gap between features. Thus, how to sufficiently and effectively eliminate the semantic gap as well as combine the global and local information is a critical challenge.

Authors

  • Zhiyong Huang
    Department of Computer Science, NUS School of Computing, National University of Singapore, Singapore.
  • Yunlan Zhao
    School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
  • Zhi Yu
    ModiFace - A L'Oréal Group Company, Toronto, ON, Canada.
  • Pinzhong Qin
    School of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China.
  • Xiao Han
    College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Center of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Provincial Key Laboratory of Clean Production of Fine Chemicals, Shandong Normal University Jinan 250014 China cyzhang@sdnu.edu.cn.
  • Mengyao Wang
    Key Laboratory of Luminescence and Real-Time Analytical Chemistry (Ministry of Education), College of Pharmaceutical Sciences, Southwest University, Chongqing 400716, China.
  • Man Liu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Hans Gregersen
    California Medical Innovations Institute, San Diego 92121, California.

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