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Cardiac Cine MRI in 4 Heartbeats: Reducing Breath-Hold Burden in CMR

SwiftMR reconstruction reduces 2-chamber cine acquisition from 11 heartbeats to 4, cutting breath-hold time by more than 60% while maintaining diagnostic...
Week-04

Metal Artifact Reduction MRI: Recovering Signal with SwiftMR

Metal Hardware MRI: Same Protocol. Recovering Signal Where It Counts Metal hardware is one of the biggest image quality challenges in MRI, and one of the...
AIRS-Future

Beyond Faster Scans: Where We're Taking MRI Next

Following the TA Associates growth investment, AIRS Medical CEO Jason Park shares why the future of MRI is measurable insight, not just faster scans.
Image of the Week 2026-24

Liver DCE MRI Evaluating Vessel Delineation and Lesion Conspicuity

Liver DCE MRI — Same Scan. More to See. Arterial phase imaging requires precise timing and sufficient image quality to evaluate enhancement patterns, hepatic...
Week-02

Deep Resolve and SwiftMR: Accelerated Ankle MRI to 51 Seconds

Ankle Ax PD Musculoskeletal MRI often requires balancing image quality with efficiency. This example compares standard deep resolve AI and accelerated...
Sagittal brain MRI on a Siemens Skyra 3T comparing a conventional 3:03 acquisition with SwiftMR at 1:03 using 0.9 × 1.1 × 1.0 mm acquired resolution.

Image of the Week: Brain 3D T2 FLAIR

Brain 3D T2 FLAIR FLAIR (Fluid-Attenuated Inversion Recovery) suppresses cerebrospinal fluid signal to make white matter lesions — including periventricular...
논문_IamCurious_썸네일_240619

I am curious about SwiftMR's deep learning algorithm!

Written by Geunu Jeong Head of SwiftMR Research in AIRS Medical SwiftMR is a deep learning-based product that enhances the quality of MR images. So, how...
20240517

All-in-One Deep Learning Framework for MR Image Reconstruction

Authors Geunu Jeong, Hyeonsoo Kim, Joonyoung Yang, Kyungeun Jang, Jeewook Kim AIRS Medical, Seoul, Korea   We introduce a novel, all-in-one...
NVR_240311_썸네일

Transforming MRI Efficiency: The Swift Rise of AI at Naugatuck Valley Radiology

Seven years ago at RSNA, Chris Beaulieu, Operations Director at Naugatuck Valley Radiology(NVR), was approached by a technology vendor claiming something...

Pediatric Case report

Introduction Radiologic exams including magnetic resonance imaging (MRI) for pediatric patients require utmost attention to safety and efficacy. While...

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

Authors Joohee Lee1, Min Jung2, Jiwoo Park1, Sungjun Kim1, Yunjin Im1, Nim Lee1, Ho-Taek Song1 & Young Han Lee1   1. Department of Radiology,...

Deep Learning-based MR Reconstruction Improves Robustness of Brain Volumetry in Low-Quality MR Images

Authors Woojin Jung1, Koung Mi Kang2   1AIRS Medical Inc, Korea, Republic of2Seoul National University Hospital, Korea, Republic ofwe3001@gmail.com   KCR...

High-Resolution Bone Image from shoulder MRI Using Deep Neural Network on 3-D Accelerated Dixon GRE (CAIPIRINHA Dixon)

Authors Sheen Woo Lee1, Seungwook Yang2, Jooyeon Kim1   1The Catholic University of Korea, Eunpyeong St. Mary’s Hospital, Korea, Republic...

Enhancing Radiomic Feature Correlations and Reproducibility in Knee MRI by Deep Learning-Based MR Reconstruction

Authors Minju Cho1, Seungwook Yang1, Sohyun Kim1, Young Han Lee2   1AIRS Medical, Korea, Republic of2Yonsei University College of Medicine,...

Stability of Deep Learning-based Image Quality Improvement in MRI of the Knee: Correlation with Arthroscopy

Authors Seung Hoon Choi1, Hee Rin Lee1, Joon-Yong Jung1, Seung Eun Lee1, So Hyun Kim2, Geunu Jeong2   1The Catholic University of Korea,...
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