Clinical Evidence
Introduction to the Core Algorithm of SwiftMR™
The article, “All-in-One Deep Learning Framework for MR Image Reconstruction” highlights a groundbreaking innovation in MRI technology. This deep learning framework is distinguished from previously developed models by integrating all essential functions into a single, comprehensive solution. By doing so, it streamlines the process of MR image reconstruction, offering an advanced approach that surpasses traditional methods.
Clinical White Paper
Clinical Implications and Use Cases of SwiftMR™
Our summary
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,...
Economic White Paper
Demonstrating the Economic Value of SwiftMR™
Our summary
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...
Peer-Reviewed Research
Deep Learning-Based High-Resolution Magnetic Resonance Angiography (MRA) Generation Model for 4D Time-Resolved Angiography with Interleaved Stochastic Trajectories (TWIST) MRA in Fast Stroke Imaging
Our summary
This study investigated...
Technical Paper
All-in-One Deep Learning Framework for MR Image Reconstruction
Key Innovation
The article, “All-in-One Deep Learning Framework for MR Image Reconstruction,” highlights a groundbreaking innovation in MRI technology. This deep...
Technical White Paper
Optimizing SwiftMR Protocols for Diverse Applications
About
The whitepaper by Geunu Jeong, MD, Head of SwiftMR Research at AIRS Medical Inc., introduces SwiftMR™, a deep learning-based technology designed to enhance MRI quality by...
Peer-Reviewed Article
Deep Learning-based Image Enhancement Techniques for Fast MRI in Neuroimaging
Our Summary
This review paper explores existing literature on the diverse applications of deep learning reconstruction (DLR) techniques for fast MR neuroimaging....
Peer-Reviewed Research
Improving Diagnostic Performance of MRI for Temporal Lobe Epilepsy With Deep Learning-Based Image Reconstruction in Patients With Suspected Focal Epilepsy
Our summary
This study explores the integration of SwiftMR in enhancing the...
Peer-Reviewed Research
Deep learning–based reconstruction for acceleration of lumbar spine MRI: a prospective comparison with standard MRI
Our summary
This study investigated the application of SwiftMR in enhancing the efficiency and quality of MRI scans...
Review Article
Harnessing Artificial Intelligence in Radiology to Augment Population Health
Results
AI applications can enhance imaging processes, reduce scan times, and improve image quality, thereby increasing efficiency. SwiftMR’s technology...
Peer-Reviewed Research
Highly accelerated knee magnetic resonance imaging using deep neural network (DNN)–based reconstruction: prospective, multi-reader, multi-vendor study
Our summary
This study evaluated the performance of SwiftMR in accelerating the...
