Super-resolution deep learning reconstruction at coronary computed tomography angiography to evaluate the coronary arteries and in-stent lumen: an initial experience

Super-resolution deep learning reconstruction at coronary computed tomography angiography to evaluate the coronary arteries and in-stent lumen: an initial experience

Abstract A super-resolution deep learning reconstruction (SR-DLR) algorithm trained using data acquired on the ultrahigh spatial resolution computed tomography (UHRCT) has the potential to provide better image quality of coronary arteries on the whole-heart, single-rotation cardiac coverage on a 320...

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Bibliographic Details
Main Authors: Makoto Orii, Misato Sone, Takeshi Osaki, Yuta Ueyama, Takuya Chiba, Tadashi Sasaki, Kunihiro Yoshioka
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Medical Imaging
Subjects:
Coronary computed tomography angiography
Super-resolution deep learning reconstruction
Model-based iterative reconstruction
Signal-to-noise ratio
Contrast-to-noise ratio
Online Access:https://doi.org/10.1186/s12880-023-01139-7

Internet

https://doi.org/10.1186/s12880-023-01139-7

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