Advanced multi-label brain hemorrhage segmentation using an attention-based residual U-Net model.

Journal: BMC medical informatics and decision making
Published Date: Jul 31, 2025

Abstract

OBJECTIVE: This study aimed to develop and assess an advanced Attention-Based Residual U-Net (ResUNet) model for accurately segmenting different types of brain hemorrhages from CT images. The goal was to overcome the limitations of manual segmentation and current automated methods regarding precision and generalizability.

Authors

  • Xinxin Lin
    Department of Critical Care Medicine, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Enmiao Zou
    Department of General Rehabilitation, The Second Affiliated Hospital, Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, 325027, China.
  • Wenci Chen
    Department of Rehabilitation, Wenzhou Hospital of Integrated Traditional Chinese and Western Medicine, Wenzhou, Zhejiang, China.
  • Xinxin Chen
    Medical School of Changchun Sci-Tech University, Chagnchun, China.
  • Le Lin
    Fujian Provincial Hospital, Fuzhou, China.

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