Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19

Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epicardial adipose tissue (EAT) from low-dose computed tomography (LDCT) and investigate the link between EAT and COVID-19 clinical outcomes. Methods: This monocentric retrospective study included 353 pati...

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Detalles Bibliográficos
Autores principales: Bartoli, Axel, Fournel, Joris, Ait-Yahia, Léa, Cadour, Farah, Tradi, Farouk, Ghattas, Badih, Cortaredona, Sébastien, Million, Matthieu, Lasbleiz, Adèle, Dutour, Anne, Gaborit, Bénédicte, Jacquier, Alexis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947414/
https://www.ncbi.nlm.nih.gov/pubmed/35326485
http://dx.doi.org/10.3390/cells11061034

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8947414/
https://www.ncbi.nlm.nih.gov/pubmed/35326485
http://dx.doi.org/10.3390/cells11061034

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