Automated cardiac volume assessment and cardiac long- and short-axis imaging plane prediction from electrocardiogram-gated computed tomography volumes enabled by deep learning

AIMS: To develop an automated method for bloodpool segmentation and imaging plane re-slicing of cardiac computed tomography (CT) via deep learning (DL) for clinical use in coronary artery disease (CAD) wall motion assessment and reproducible longitudinal imaging. METHODS AND RESULTS: One hundred pat...

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Detalles Bibliográficos
Autores principales: Chen, Zhennong, Rigolli, Marzia, Vigneault, Davis Marc, Kligerman, Seth, Hahn, Lewis, Narezkina, Anna, Craine, Amanda, Lowe, Katherine, Contijoch, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242184/
https://www.ncbi.nlm.nih.gov/pubmed/34223176
http://dx.doi.org/10.1093/ehjdh/ztab033

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8242184/
https://www.ncbi.nlm.nih.gov/pubmed/34223176
http://dx.doi.org/10.1093/ehjdh/ztab033

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