A U-Shaped Network Based on Multi-level Feature and Dual-Attention Coordination Mechanism for Coronary Artery Segmentation of CCTA Images.

Journal: Cardiovascular engineering and technology
Published Date: Feb 27, 2023

Abstract

PURPOSE: Computed tomography coronary angiography (CCTA) images provide optimal visualization of coronary arteries to aid in diagnosing coronary heart disease (CHD). With the deep convolutional neural network, this work aims to develop an intelligent and lightweight coronary artery segmentation algorithm that can be deployed in hospital systems to assist clinicians in quantitatively analyzing CHD.

Authors

  • Peng Hong
    Department of Urology, Peking University Third Hospital, Haidian District, 49 North Garden Road, Haidian, Beijing, 100191, People's Republic of China.
  • Yong Du
    Biomedical Engineering DepartmentUniversity of Houston Houston TX 77204 USA.
  • Dongming Chen
    Software College, Northeastern University, Shenyang 110169, China.
  • Chengbao Peng
    Neusoft Research of Intelligent Healthcare Technology, Co. Ltd, Shenyang, 110169, China. pengcb@neusoft.com.
  • Benqiang Yang
  • Lisheng Xu
    College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.

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