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...

Full beskrivning

Sparad:
Bibliografiska uppgifter
I publikationen:Radiol Artif Intell
Huvudupphovsmän: 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
Materialtyp: Artigo
Språk:Inglês
Publicerad: Radiological Society of North America 2019
Ämnen:
Original Research
Länkar: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
Taggar: Lägg till en tagg
Inga taggar, Lägg till första taggen!

Liknande verk