Cardiac magnetic resonance image segmentation based on convolutional neural network.

Journal: Computer methods and programs in biomedicine
Published Date: Sep 11, 2020

Abstract

OBJECTIVE: In cardiac medical imaging, the extraction and segmentation of the part of interest is the key to the diagnosis of heart disease. Due to irregular diastole and contraction, magnetic resonance imaging (MRI) images have poorly defined boundaries, and traditional segmentation algorithms have poor performance. In this paper, a cardiac MRI segmentation technique using convolutional neural network and image saliency is suggested.

Authors

  • Duqiu Liu
    Department of Cardiology, the Fifth Affiliated Hospital of Southern Medical University, Guangzhou, China.
  • Zheng Jia
    College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
  • Ming Jin
    Department of Interventional Radiology, Affiliated Hospital of Guilin Medical University, Guilin, China.
  • Qian Liu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Zhiliang Liao
    Department of Cardiology, the Fifth Affiliated Hospital of Southern Medical University, Guangzhou, China.
  • Junyan Zhong
    Department of Cardiology, the Fifth Affiliated Hospital of Southern Medical University, Guangzhou, China.
  • Haowen Ye
    Department of Cardiology, the Fifth Affiliated Hospital of Southern Medical University, Guangzhou, China.
  • Gang Chen
    Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan, China.

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