Our multi-site study demonstrates that the iQMR, a machine learning-based technology, allows the use of 30% faster MRI brain and spine protocols while maintaining equivalent image quality and diagnostic value. These significant reductions in scan time improve our patient’s experience and may minimize motion artifacts and repeated scan rate.
Wende Gibbs, MD, Director of Spine Imaging and Intervention, Kech School of Medicine, University of Southern California.
The overall image quality, diagnostic utility, artifact appearance and GW-matter differentiation of the short protocols were equal and sometimes better than those of routine protocols when processed and enhanced with iQMR, a machine-learning based algorithm
Blake Johnson, M.D., F.A.C.R, Medical Director and Director of Neuroimaging at the Center for Diagnostic Imaging, Minneapolis, MN.
Our clinical studies demonstrate that iQMR, a machine learning-based technology, allow the use of short MRI protocols whilst keeping equivalent diagnostic value, thus enhancing overall productivity
Roni Shreter, MD, Director of Imaging Institute Hillel Yaffe Medical Center, Israel.