DEMAC-Net: A Dual-Encoder Multiattention Collaborative Network for Cervical Nerve Pathway and Adjacent Anatomical Structure Segmentation.

Journal: Ultrasound in medicine & biology
Published Date:

Abstract

OBJECTIVE: Currently, cervical anesthesia is performed using three main approaches: superficial cervical plexus block, deep cervical plexus block, and intermediate plexus nerve block. However, each technique carries inherent risks and demands significant clinical expertise. Ultrasound imaging, known for its real-time visualization capabilities and accessibility, is widely used in both diagnostic and interventional procedures. Nevertheless, accurate segmentation of small and irregularly shaped structures such as the cervical and brachial plexuses remains challenging due to image noise, complex anatomical morphology, and limited annotated training data. This study introduces DEMAC-Net-a dual-encoder, multiattention collaborative network-to significantly improve the segmentation accuracy of these neural structures. By precisely identifying the cervical nerve pathway (CNP) and adjacent anatomical tissues, DEMAC-Net aims to assist clinicians, especially those less experienced, in effectively guiding anesthesia procedures and accurately identifying optimal needle insertion points. Consequently, this improvement is expected to enhance clinical safety, reduce procedural risks, and streamline decision-making efficiency during ultrasound-guided regional anesthesia.

Authors

  • H Cui
    School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • J Duan
    State Key Laboratory of Environmental Adaptability for Industrial Products, National Electric Apparatus Research Institute Co., Ltd, Guangzhou, Guangdong, China.
  • L Lin
    Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing100029, China.
  • Q Wu
    Department of Anesthesiology, The First Hospital of Putian City, Putian, China.
  • W Guo
    Department of Pathology, First Affiliated Hospital of Hunan Normal University, The People's Hospital of Hunan Province, Changsha, 410005, Hunan, China.
  • Q Zang
    Information Center, The Second Affiliated Hospital of Naval Medical University, No. 415, Fengyang Road, Huangpu District, Shanghai 200003, PR China.
  • M Zhou
    From the Stanford Center for Biomedical Informatic Research (M.Z., O.G.).
  • W Fang
    Department of Pathology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China.
  • Y Hu
    General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Z Zou
    The Department of Thoracic Surgery, The First Hospital of China Medical University, Shenyang, Liaoning, China.