Medic Vision’s generative AI-assisted technology, iQMR, revolutionizes MRI imaging by significantly enhancing image quality and enabling a substantial reduction of scan times, as demonstrated in a study led by Dr. Roni Shreter.
Presented at ASNR 2023 The purpose of this multi-site study was to evaluate image quality, image resolution, and overall diagnostic sufficiency of low-resolution brain MRI images processed by a iQMR, a deep-learning (DL) resolution enhancement algorithm, compared to images acquired with higher resolution from multiple sites and MRI scanners.
Presented at RSNA 2022 The purpose of the MRI novel study was to evaluate image quality, image resolution, and overall diagnostic sufficiency of low resolution brain MRI images processed by a novel deep learning (DL) resolution enhancement algorithm, compared to images acquired with higher resolution from multiple sites and MRI scanners. The Challenge Large-Scale Deployment of iQMR. Alliar, the third-largest diagnostic imaging …
Presented by Alliar, Brazil at RSNA 2022 The purpose of this study was to evaluate if the adoption of a proprietary Artificial Intelligence Software that reduces MRI scan time without compromising image quality is correlated with a decrease in the average scan time considering all imaging protocols (with and without the software), an increase in …
Collaborative work with Lawrence N. Tanenbaum MD FACR, RadNet PURPOSE This study aims to evaluate the scan time shortening potential of iQMR, a novel 3D image enhancement algorithm, in brain, lumbar spine, and cervical spine MRI scan . iQMR provides image enhancement and increased Signal-to-Noise Ratio (SNR), thus permitting substantial scan time reduction, without changing …
MR image quality and subsequent brain morphometric analysis are inevitably affected by noise. The purpose of this study was to evaluate the effectiveness of an artificial intelligence (AI)-based post-scan processing denoising system, intelligent Quick Magnetic Resonance (iQMR), on MR image quality and brain morphometric analysis. Fig. 1. MR images (A) without denoising, (B) processed with intelligent Quick Magnetic …
To evaluate the ability to substantially reduce neuro MRI scans time by applying Compressed Sense (CS) with Machine Learning (ML) assisted image enhancement technology. Figure 1 Axial T1w 3D images from a Philips Ingenia 1.5T scanner. (A) Accelerated routine protocol (with CS-3), AT=2:15min (B) Fast protocol (accelerated withCS-4), AT=1:42 and (C) Fast ML processed protocol (accelerated with …
Authors: R Shreter , J Brace , M Goldfeld , I Page , G Stenoien , L Mori , T Aharoni , L Lucato PURPOSE To assess scan time reduction in brain MRI scans by acquiring reduced-resolution faster protocols, post-processed by novel machine-learning (ML) assisted technology. Assessment was conducted by comparing quality, contrast, resolution, noise and …
This report was conducted with Houston Medical Imaging’s (HMI) outpatient diagnostic centers. An increase in demand for MRI scans at HMI prompted a Productivity and Service Quality improvement project. The project aimed to optimize the performance of 7 MRI scanners across 6 sites in order to facilitate more scans and ultimately improve patient service. 49% SCAN-TIME …
The report compared complete MRI brain scans exams that were acquired by the site’s routine scan (11 minutes 50 seconds) and by accelerated acquisition (5 minutes 50 seconds, 50% scan time reduction). Acquired images were processed and reviewed blindly by acknowledged neuroradiologists. The results demonstrate definite preference towards IIR-processed fast MRI brain scans, for all …
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