Deep learning segmentation and quantification method for assessing epicardial adipose tissue in CT calcium score scans

Epicardial adipose tissue volume (EAT) has been linked to coronary artery disease and the risk of major adverse cardiac events. As manual quantification of EAT is time-consuming, requires specialized training, and is prone to human error, we developed a deep learning method (DeepFat) for the automat...

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Detalles Bibliográficos
Autores principales: Hoori, Ammar, Hu, Tao, Lee, Juhwan, Al-Kindi, Sadeer, Rajagopalan, Sanjay, Wilson, David L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8831577/
https://www.ncbi.nlm.nih.gov/pubmed/35145186
http://dx.doi.org/10.1038/s41598-022-06351-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8831577/
https://www.ncbi.nlm.nih.gov/pubmed/35145186
http://dx.doi.org/10.1038/s41598-022-06351-z

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