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.
Compliance White Paper SwiftMR Information Security Summary 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,...
Clinical White Paper SwiftMR™の臨床的意義と使用例 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, scanner vendors, and...
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 MR画像再構成のためのオールインワン・ディープラーニング・フレームワーク キー・イノベーション 「All-in-One Deep Learning Framework for MR Image Reconstruction」は、MRI技術における画期的な革新に焦点を当てている。このディープラーニングフレームワークは、すべての重要な機能を単一の包括的なソリューションに統合することで、これまでに開発されたモデルとは一線を画している。そうすることで、MR画像再構成のプロセスを合理化し、従来の手法を凌駕する高度なアプローチを提供する。...
Technical White Paper 多様なアプリケーションのためのSwiftMRプロトコルの最適化 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 improving the signal-to-noise...
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...
