A novel end-to-end deep learning solution for coronary artery segmentation from CCTA.

Journal: Medical physics
Published Date: Jul 11, 2022

Abstract

PURPOSE: Coronary computed tomographic angiography (CCTA) plays a vital role in the diagnosis of cardiovascular diseases, among which automatic coronary artery segmentation (CAS) serves as one of the most challenging tasks. To computationally assist the task, this paper proposes a novel end-to-end deep learning-based (DL) solution for automatic CAS.

Authors

  • Caixia Dong
    Institute of Medical Artificial Intelligence, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.
  • Songhua Xu
    Institute of Medical Artificial Intelligence, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China. Electronic address: songhua_xu1@163.com.
  • Zongfang Li
    Department of Oncology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

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