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ISMRM 2022 presentations

GE Healthcare is pleased to announce the following abstracts on AIR™ Recon DL and other new DL-based reconstruction applications that were accepted for presentation at the 2022 Annual Meeting of the International Society for Magnetic Resonance in Medicine (ISMRM) scheduled to be held May 7-12 in London, England. AIR™ Recon DL is a GE-first, deep-learning MR reconstruction algorithm designed to improve SNR and image sharpness and enable shorter scan times.

1.5T prostate MRI utilizing deep learning reconstruction in patients with hip prosthesis
Fairfax Radiological Consultants, GE Healthcare
3D T2-weighted rectal cancer imaging using a 3D fast spin echo sequence with deep learning reconstruction
MD Anderson Cancer Center, GE Healthcare
Comparison between image quality of 3D T1 GRE sequence with and without deep learning reconstruction at gadoxetic acid-enhanced liver MRI
Seoul National University Hospital, GE Healthcare
Image quality of deep-learning reconstructed near-isotropic (3D) enhanced MR enterography with LAVA HyperSense in Crohn’s disease patients
Haeundae Paik Hospital, GE Healthcare
Rapid and high resolution pelvic MRI using deep learning reconstruction
Fairfax Radiological Consultants, GE Healthcare
Improved myocardial T1 mapping accuracy with deep learning reconstruction of low flip angle MOLLI series
Hospital Universitario Quirónsalud, Onewelbeck, GE Healthcare
Deep learning reconstruction-enabled 2D and 3D neurography
Hospital for Special Surgery, GE Healthcare
Evaluation of deep-learning reconstructed high-resolution 3D cervical spine MRI to improve foraminal stenosis evaluation
Hospital for Special Surgery, GE Healthcare
Improving diagnostic confidence using a deep-learning reconstructed fast motion-robust PROPELLER protocol for shoulder imaging
Clínica CEMTRO, Rey Juan Carlos University, GE Healthcare
Quantitative & qualitative evaluation of accelerated T2 mapping technique using deep learning reconstruction in knee cartilage
Clínica CEMTRO, Rey Juan Carlos University, GE Healthcare
Shoulder PROPELLER MRI with deep learning-based reconstruction: image quality and agreement between standard and accelerated sequence
Haeundae Paik Hospital, Inje University College of Medicine, GE Healthcare
Neuro & spine
A clinical protocol for 3D imaging of the locus coeruleus with super-resolution at 3 Tesla
Invicro (Imperial College London), GE Healthcare
Axial T2 weighted MR imaging of the cervical spine using PROPELLER with deep learning reconstruction to improve image quality
Pusan National University Hospital, GE Healthcare
Deep learning based image reconstruction for improved 3D multiparameter mapping and synthetic MR imaging
MD Anderson Cancer Center, GE Healthcare
Deep learning reconstruction enables accelerated acquisitions with consistent volumetric measurements
Cortechs, GE Healthcare
Development of a high-speed MRI protocol with deep learning reconstruction method for brain imaging in a clinical setting
Columbia University, GE Healthcare
Evaluation of the efficacy of a deep learning-based reconstruction in the connectomic deep brain stimulation
Mount Sinai, GE Healthcare
Fast and high-resolution T2* weighted and susceptibility-based MRI using 3D EPI with deep learning reconstruction
Karolinska University Hospital, Karolinska Institutet
Highly accelerated volumetric brain imaging with META and deep learning reconstruction
Juntendo University, GE Healthcare
High resolution diffusion tensor imaging at 7T with multi-band multi-shot EPI acquisition and deep learning reconstruction
University of Minnesota, GE Healthcare
Improving motion-robust structural imaging at 7T with deep learning-based PROPELLER reconstruction
GE Healthcare
K-space based deep learning reconstruction empowers 60-70% acceleration of MR imaging of the spine
Radnet, GE Healthcare
Mitigation of partial-volume artifacts in synthetic T2 FLAIR using separately acquired fast T2 FLAIR contrast information combined with keyhole and deep learning-based image reconstruction
GE Healthcare
Robust diffusion weighted imaging with deep learning-based DW PROPELLER reconstruction
MD Anderson Cancer Center, GE Healthcare
For more information on ISMRM 2022, visit: