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DL-based reconstruction abstracts to be presented at ISMRM 2021

Demonstrating advances in MR and deep learning, GE Healthcare is pleased to announce that abstracts on AIR™ Recon DL and other new DL-based reconstruction applications were accepted for presentation at the 2021 Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) scheduled to be held virtually, May 15-20. AIR™ Recon DL, an Edison application providing TrueFidelity™ MR images, is a GE-first, deep-learning MR reconstruction algorithm designed to improve SNR and image sharpness and enable shorter scan times.

Deep-learning-based Radial De-streaking for Free-breathing, Time-resolved Volumetric DCE MRI
GE Healthcare Program #529
Motion Robust, High-Resolution Pelvic Imaging Using PROPELLER and Deep-learning Reconstruction
University of Wisconsin-Madison Program #2998
Motion-Robust, High-SNR Diffusion MRI of the Liver Using Optimized Gradient Waveforms and Deep-learning Reconstruction
University of Wisconsin-Madison, Stanford University Program #2123
T2-weighted Pelvic MR Imaging Using PROPELLER with Deep- learning Reconstruction for Improved Motion Robustness
MD Anderson Cancer Center Program #3000
Feasibility of Using A Deep-learning Reconstruction to Increase Protocol Flexibility for Breast MRI
University of Wisconsin-Madison Program #1129
Deep-learning Reconstruction Including De-streaking Capability for Motion Robust T1-weighted Breast Imaging
University of Wisconsin-Madison Program #1442
Deep-learning Reconstruction of 3D Zero Echo Time Magnetic Resonance Images for the Creation of 3D Printed Anatomic Models
Montefiore Medical Center, NY Program #4061
Accelerating Neuroradiology Protocols with Deep-learning MR Image Reconstruction. Which Methods Result in the Highest Perceived Image Quality?
University of Wisconsin-Madison Program #3828
Deep-learning-based Image Reconstruction Improves CEST MRI
MD Anderson Cancer Center Program #1457
Improved Image Quality with Deep-learning-based Denoising of Diffusion MRI Data
GE Healthcare Program #2439
Deep-learning-based, MR-only Radiation Therapy Planning for Head & Neck and Pelvis
GE Healthcare, Newcastle University, Erasmus MC Program #4248
Evaluation of Deep-learning- reconstructed, High-resolution 3D Lumbar Spine MRI to Improve Image Quality
Hospital for Special Surgery, NY Program #805
Peer-reviewed articles from high-impact journals
Kim M, Kim HS, Kim HJ, et al. Thin-Slice Pituitary MRI with Deep Learning-based Reconstruction: Diagnostic Performance in a Postoperative Setting. Radiology. 2021 Jan;298(1):114-122. Asan Medical Center, Seoul, Korea
van der Velde N, Hassing HC, Bakker BJ, et al. Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification. Eur Radiol. 2020 Nov 21. Erasmus Medical Center, Rotterdam, The Netherlands
Wang X, Ma J, Bhosale P, et al. Novel deep learning-based noise reduction technique for prostate magnetic resonance imaging. Abdom Radiol (NY). 2021 Feb 12. The University of Texas MD Anderson Cancer Center, Houston, TX
For more information on ISMRM 2021, visit: