Deep-Learning Segmentation of Epicardial Adipose Tissue Using Four-Chamber Cardiac Magnetic Resonance Imaging

In magnetic resonance imaging (MRI), epicardial adipose tissue (EAT) overload remains often overlooked due to tedious manual contouring in images. Automated four-chamber EAT area quantification was proposed, leveraging deep-learning segmentation using multi-frame fully convolutional networks (FCN)....

Descripción completa

Detalles Bibliográficos
Autores principales: Daudé, Pierre, Ancel, Patricia, Confort Gouny, Sylviane, Jacquier, Alexis, Kober, Frank, Dutour, Anne, Bernard, Monique, Gaborit, Bénédicte, Rapacchi, Stanislas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774679/
https://www.ncbi.nlm.nih.gov/pubmed/35054297
http://dx.doi.org/10.3390/diagnostics12010126

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774679/
https://www.ncbi.nlm.nih.gov/pubmed/35054297
http://dx.doi.org/10.3390/diagnostics12010126

Ejemplares similares