Coronary angiography image segmentation based on PSPNet.

Journal: Computer methods and programs in biomedicine
Published Date: Dec 4, 2020

Abstract

PURPOSE: Coronary artery disease (CAD) is known to have high prevalence, high disability and mortality. The incidence and mortality of cardiovascular disease are also gradually increasing worldwide. Therefore, our paper proposes to use a more efficient image processing method to extract accurate vascular structures from vascular images by combining computer vision and deep learning.

Authors

  • Xiliang Zhu
    Department of Cardiovascular Surgery, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, Henan Cardiovascular Hospital and Zhengzhou University, Zhengzhou, China.
  • Zhaoyun Cheng
    Department of Cardiovascular Surgery, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, Henan Cardiovascular Hospital and Zhengzhou University, Zhengzhou, China.
  • Sheng Wang
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.
  • Xianjie Chen
    Department of Cardiovascular Surgery, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, Henan Cardiovascular Hospital and Zhengzhou University, Zhengzhou, China.
  • Guoqing Lu
    Department of Cardiovascular Surgery, Henan Province People's Hospital, Fuwai Central China Cardiovascular Hospital, Henan Cardiovascular Hospital and Zhengzhou University, Zhengzhou, China.

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