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Cine SSFSE for reduced susceptibility artifact and increased diagnostic accuracy in MR enterography

Diffusion Weighted Imaging using PROPELLER Acquisition and a Deep Learning based Reconstruction

High Resolution T2W imaging using Deep Learning Reconstruction and Reduced Field-of-View PROPELLER

Informed deep convolutional neural networks

Author:R. Marc Lebel  Daniel Litwiller  

Institution:GE Healthcare  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:ML: Post Processing, Analysis, & Applications  

Session Name:Machine Learning: Disease, Diagnosis, Pathology & Treatment  

Program Number:3535  

Room Live Q&A Session:

Learning how to adapt T2 PROPELLER MR prostate imaging: going beyond PIRADS requirements with MR Deep Learning reconstruction

Author:Julie Poujol  Charline Henry  Vincent Barrau  François Legou  Eric Pessis  Xinzeng Wang  Daniel Litwiller  

Institution:Centre Cardiologique du Nord  GE Healthcare  

Session Type:Digital Poster  

Session Live Q&A Date:Digital Poster (All Week)  

Topic:Abdominopelvic MRI - Cancer  

Session Name:Deep Prostatomics  

Program Number:2389  

Room Live Q&A Session:

PROPELLER Diffusion-Weighted Imaging of the Prostate with Deep-Learning Reconstruction

Unsupervised radial streak artifact reduction in time resolved MRI