Clinical Evidence

Denoising

Super-resolution

Acceleration

Artifact Reduction

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Deep learning improves quality of intracranial vessel wall MRI for better characterization of potentially culprit plaques

Improving diagnostic performance of MRI for temporal lobe epilepsy with deep learning-based image reconstruction in patients with suspected focal epilepsy

Deep learning-based reconstruction for acceleration of lumbar spine MRI: a prospective comparison with standard MRI

Highly accelerated knee magnetic resonance imaging using deep neural network (DNN)-based reconstruction: prospective, multi-reader, multi-vendor study

Peer-reviewed evidence across routine and advanced imaging. With SwiftMR®, you’re not just accelerating MRI scans. You’re enhancing clinical confidence.

Improved SNR with well-preserved tissue contrast, revealing structures that noise obscures, without changing your scan protocol.

SwiftMR provided significant improvement in SNR and spatial resolution in vessel wall imaging, leading to detection of vessel wall lesions and intraplaque hemorrhage compared to conventional image.

Seo et al.. Scientific Reports. Aug 2024.

Improved lesion and structural conspicuity, enabling thin-slice imaging that would otherwise be limited by SNR constraints.

SwiftMR resulted in significantly improved resolution and structural conspicuity in hippocampal imaging compared to routine imaging. Hippocampal striation blurring was suspected on routine 3mm MRI, but became more obvious on 1.5mm MRI + SwiftMR.

Suh et al.. Korean Journal of Radiology. 2024;25(4):374-383.

Shorter scan time means less patient movement, minimizing chances of motion artifacts, directly improving image quality as a secondary benefit.

Prospective comparison showing 32.3% average acquisition time saving versus standard protocol, with no degradation in image quality or diagnostic performance.

Yoo et al.. Eur Radiol. 2023;33(12):8656-8668.

Prospective, multi-reader, multi-vendor study demonstrating average scan time reduction of 41% using SwiftMR, without degrading image quality or diagnostic performance across readers or scanner platforms.

Lee et al.. Sci Rep. 2023;13:17264. PMID: 37828048.

Improve truncation and susceptibility artifacts, producing cleaner images from the same acquisition without reacquisition or protocol changes.

Note: This section is supported by clinical image data acquired by AIRS Medical clinical research team.

Susceptibility artifacts reduction

Geometric distortion improvement

Brain DWI b1000 · 2D EPI Diffusion · Same acquisition3.0T Siemens MAGNETOM Skyra

1:30 — Without SwiftMR · 1.5×1.9×3.0 mm

1:30 — With SwiftMR · 1.5×1.9×3.0 mm

Truncation artifact improvement

Our clinical team can provide in-depth clinical and technical presentations on SwiftMR.

In this white paper, we compared SwiftMR-processed MR exams to the standard of care. We analyzed 184 MR exam pairs from 12 anatomical locations, considering various pathologies.

This study explored the use of SwiftMR for detecting brain metastases. The findings showed significant improvements in both quantitative and qualitative metrics.

SwiftMR, an AI-powered MRI reconstruction software, offers clear economic benefits to imaging centers. In an economic model, we estimated that a typical imaging center using SwiftMR can see meaningful gains.

This study investigated the use of SwiftMR in 4D time-resolved contrast-enhanced MRA, showing measurable gains for ischemic stroke imaging.

“All-in-One Deep Learning Framework for MR Image Reconstruction” highlights a groundbreaking innovation in MRI technology that underpins SwiftMR.

Whitepaper by Geunu Jeong, MD, Head of SwiftMR Research at AIRS Medical. Introduces SwiftMR, a deep learning-based technology designed to enhance MRI quality across diverse applications.

Peer-reviewed review paper exploring existing literature on the diverse applications of deep learning reconstruction (DLR) techniques for fast MR neuroimaging.

This study explores the integration of SwiftMR in enhancing the diagnostic performance of MRI for temporal lobe epilepsy.

This study investigated the application of SwiftMR in enhancing the efficiency and quality of lumbar spine MRI scans.

AI applications can enhance imaging processes, reduce scan times, and improve image quality, increasing efficiency. Review of SwiftMR’s impact on revenue and operations.

This study evaluated the performance of SwiftMR in accelerating knee MRI without degrading image quality or diagnostic performance.

For a full list of publications, contact [email protected].

Our clinical team can provide in-depth presentations on SwiftMR — including protocol-specific performance data for your scanner and field strength.