Motion artefact reduction in coronary CT angiography images with a deep learning method

Motion artefact reduction in coronary CT angiography images with a deep learning method

Abstract Background The aim of this study was to investigate the ability of a pixel-to-pixel generative adversarial network (GAN) to remove motion artefacts in coronary CT angiography (CCTA) images. Methods Ninety-seven patients who underwent single-cardiac-cycle multiphase CCTA were retrospectively...

Full description

Bibliographic Details
Main Authors: Pengling Ren, Yi He, Yi Zhu, Tingting Zhang, Jiaxin Cao, Zhenchang Wang, Zhenghan Yang
Format: Article
Language:English
Published: BMC 2022-10-01
Series:BMC Medical Imaging
Subjects:
Coronary CT angiography
Motion artefacts
Artificial intelligence
Deep learning
Online Access:https://doi.org/10.1186/s12880-022-00914-2

Internet

https://doi.org/10.1186/s12880-022-00914-2

Similar Items