Deep learning‐based motion correction algorithm for coronary CT angiography: Lowering the phase requirement for morphological and functional evaluation

PURPOSE: To investigate the performance of a deep learning‐based motion correction algorithm (MCA) at various cardiac phases of coronary computed tomography angiography (CCTA), and determine the extent to which it may allow for reliable morphological and functional evaluation. MATERIALS AND METHODS:...

Descripción completa

Detalles Bibliográficos
Autores principales: Yao, Xiaoling, Zhong, Sihua, Xu, Maolan, Zhang, Guozhi, Yuan, Yuan, Shuai, Tao, Li, Zhenlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Medical Imaging
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476979/
https://www.ncbi.nlm.nih.gov/pubmed/37485892
http://dx.doi.org/10.1002/acm2.14104

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476979/
https://www.ncbi.nlm.nih.gov/pubmed/37485892
http://dx.doi.org/10.1002/acm2.14104

Ejemplares similares