Abstracts accepted at RSNA 2019

GE Healthcare is pleased to announce that four abstracts on AIR™ Recon DL‡ have been accepted for presentations at the 2019 Annual Meeting of the Radiological Society of North America (RSNA).

Congratulations to these clinicians and institutions, and a heartfelt thank you to all who submitted an abstract on AIR™ Recon DL for consideration at this year’s meeting.

Sunday, Dec. 1

10:45 AM – 12:15 PM

SSA22-06

Session: Physics (MRI – New Techniques and Image Quality)

Improvement of Late Gadolinium Enhancement Image Quality Using a Novel, Deep Learning Based, Reconstruction Algorithm and its Influence on Myocardial Scar Quantification Van der Velde N, Bakker B, Hassing C, Wielopolski PA, Lebel RM, Janich MA, Budde RP, Hirsch A Erasmus Medical Center, Rotterdam, Netherlands

Monday, Dec. 2 12:15 – 12:45 PM

R370-SD-MOA1

Session: Neuroradiology Monday Poster Discussions

Deep-Learning Reconstruction Improves Quality of Clinical Brain and Spine MR Imaging Bash SC, Thomas M, Fung M, Lebel RM, Tanenbaum LN RadNet, Inc., Baltimore, MD

Tuesday, Dec. 3 10:30 AM – 12:00 PM

SSG08-08

Session: Musculoskeletal (Machine Learning and Artificial Intelligence)

Performance of a Deep Learning-Based MR Reconstruction Algorithm for the Evaluation of Peripheral Nerves Argentieri EC, Zochowski KC, Potter HG, Shin J, Lebel RM, Sneag DB Hospital for Special Surgery, New York, NY

Thursday, Dec. 5 10:30 AM – 12:00 PM

SSQ15-08

Session: Neuroradiology/Head and Neck (Artificial Intelligence)

Denoising MR Images of the Cervical Spine: Multi-Reader Assessment of a Deep Learning Approach Villaneueva-Meyer J, Shin D, Li Y, Leon III PA, Banerjee S, Brau AC, Lebel RM, Glastonbury CM University of California San Francisco

To learn more about AIR™ Recon DL, visit: gehealthcare.com/unmissable