CAN: Context-assisted full Attention Network for brain tissue segmentation.

Journal: Medical image analysis
Published Date: Dec 21, 2022

Abstract

Brain tissue segmentation is of great value in diagnosing brain disorders. Three-dimensional (3D) and two-dimensional (2D) segmentation methods for brain Magnetic Resonance Imaging (MRI) suffer from high time complexity and low segmentation accuracy, respectively. To address these two issues, we propose a Context-assisted full Attention Network (CAN) for brain MRI segmentation by integrating 2D and 3D data of MRI. Different from the fully symmetric structure U-Net, the CAN takes the current 2D slice, its 3D contextual skull slices and 3D contextual brain slices as the input, which are further encoded by the DenseNet and decoded by our constructed full attention network. We have validated the effectiveness of the CAN on our collected dataset PWML and two public datasets dHCP2017 and MALC2012. Our code is available at https://github.com/nwuAI/CAN.

Authors

  • Zhan Li
    School of Information Science and Technology, Northwest University, 710127, Xi'an, China. Electronic address: lizhan@nwu.edu.cn.
  • Chunxia Zhang
    School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi Province, 710049, China.
  • Yongqin Zhang
    School of Information Science and Technology, Northwest University, Xi'an 710127, China; Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA. Electronic address: zhangyongqin@nwu.edu.cn.
  • XiaoFeng Wang
    Indiana University Bloomington.
  • Xiaolong Ma
    College of Life Science and Engineering, Lanzhou University of TechnologyLanzhou 730050, P. R. China; The Key Lab of Screening, Evaluation and Advanced Processing of TCM and Tibetan Medicine, Education Department of Gansu Provincial GovernmentLanzhou 730050, P. R. China.
  • Hai Zhang
    a State Key Laboratory Breeding Base of Systematic Research Development and Utilization of Chinese Medicine Resources, Sichuan Province and Ministry of Science and Technology, College of Pharmacy and College of Ethnic Medicine , Chengdu University of Traditional Chinese Medicine , Chengdu , China.
  • Songdi Wu
    The First Affiliated Hospital of Northwest University, 710127, Xi'an, China.

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