Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study

PURPOSE: To evaluate the performance of deep learning for robust and fully automated quantification of epicardial adipose tissue (EAT) from multicenter cardiac CT data. MATERIALS AND METHODS: In this multicenter study, a convolutional neural network approach was trained to quantify EAT on non–contra...

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Publicado en:Radiol Artif Intell
Autores principales: Commandeur, Frederic, Goeller, Markus, Razipour, Aryabod, Cadet, Sebastien, Hell, Michaela M., Kwiecinski, Jacek, Chen, Xi, Chang, Hyuk-Jae, Marwan, Mohamed, Achenbach, Stephan, Berman, Daniel S., Slomka, Piotr J., Tamarappoo, Balaji K., Dey, Damini
Formato: Artigo
Lenguaje:Inglês
Publicado: Radiological Society of North America 2019
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Original Research
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC6884062/
https://ncbi.nlm.nih.gov/pubmed/32090206
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2019190045
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