Deep Learning Cross-Phase Style Transfer for Motion Artifact Correction in Coronary Computed Tomography Angiography

Motion artifacts may occur in coronary computed tomography angiography (CCTA) due to the heartbeat and impede the clinician's diagnosis of coronary arterial diseases. Thus, motion artifact correction of the coronary artery is required to quantify the risk of disease more accurately. We present...

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Bibliographic Details
Published in:IEEE Access
Main Authors: Sunghee Jung, Soochahn Lee, Byunghwan Jeon, Yeonggul Jang, Hyuk-Jae Chang
Format: Article
Language:English
Published: IEEE 2020-01-01
Subjects:
Computed tomography
deep learning
image restoration
motion correction and analysis
coronary angiography
Online Access:https://ieeexplore.ieee.org/document/9082676/

Internet

https://ieeexplore.ieee.org/document/9082676/

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