Artificial intelligence in coronary computed tomography angiography
Peng-Peng Xu,
Tong-Yuan Liu,
Fan Zhou,
Qian Chen,
Jacob Rowe,
Christian Tesche,
Long-Jiang Zhang
Affiliations
Peng-Peng Xu
Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
Tong-Yuan Liu
Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
Fan Zhou
Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
Qian Chen
Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210002, China
Jacob Rowe
Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC 29054, USA
Christian Tesche
Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC 29054, USA; Department of Cardiology, Munich University Clinic, Ludwig-Maximilian-University, Munich 80539, Germany; Corresponding authors.
Long-Jiang Zhang
Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China; Corresponding authors.
The rapid development of artificial intelligence (AI) technologies, like machine learning, deep learning, and other algorithms applied to the intelligent diagnostic and decision making, image interpretation, accurate classification, and prognostication of cardiovascular diseases, has led to broad application prospects and innovation potential. The digital and intelligent management model of cardiovascular disease is expected to improve the management level and efficiency of diseases and provide patients with more accurate, safe, and appropriate diagnosis and treatment methods. This review systematically introduces the common AI techniques in the field of cardiovascular computed tomography (CT), summarizes the current research and application progress of AI in cardiovascular CT, and provides its future perspectives.
