Results 171 to 180 of about 72,692 (245)
Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals
ABSTRACT Purpose To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR training datasets.
Anirudh Raman +10 more
wiley +1 more source
ABSTRACT We present p‐Brain, a modular, open‐source framework for reproducible, automated quantitative DCE‐MRI at scale. Rather than a fixed pipeline, p‐Brain is built from interchangeable stages (ingestion, T1/M0$$ {T}_1/{M}_0 $$ fitting, vascular and tissue ROI extraction, signal‐to‐concentration conversion, kinetic modeling, and quality control ...
Edis D. Tireli +5 more
wiley +1 more source
Multi‐Vendor and Multi‐Site Characterization of 13C Coils for Clinical Studies
ABSTRACT Purpose Due to the inherently low signal‐to‐noise ratio (SNR) domain for 13C imaging, optimal coil performance is essential to maximize data quality. Quality control (QC) for 13C coils employed in magnetic resonance spectroscopy (MRS) is of paramount importance.
Emil S. Christensen +7 more
wiley +1 more source
ABSTRACT Purpose The feasibility and reproducibility of adapting the T2‐Relaxation‐Under‐Spin‐Tagging (TRUST) MRI sequence for noninvasive measurement of venous oxygenation in the upper arm were investigated, aiming to enable future in vivo validation of T2b‐oxygenation calibration curves in sickle cell disease (SCD).
J. Diogo Fernandes +5 more
wiley +1 more source
ABSTRACT Purpose The Soma and Neurite Density Imaging (SANDI) model enables characterization of gray matter (GM) microstructure by estimating soma and neurite signal fractions, but its clinical applicability is limited by the need for multi‐shell acquisitions (at least five b‐values up to 6000 s/mm2), requiring high‐gradient MRI systems. We developed a
Hansol Lee +12 more
wiley +1 more source
ABSTRACT Purpose 4D cardiac cine is a powerful tool for comprehensive cardiac function assessment; however, current methods rely on regular breathing and are sensitive to bulk motion and arrhythmia. We aim to develop a 4D cardiac cine approach that requires no patient cooperation and is robust to irregular breathing, bulk motion, and cardiac arrhythmia.
Ye Tian +4 more
wiley +1 more source
ABSTRACT Purpose To investigate the impact of intra/extracellular water exchange (WX) on quantitative dynamic contrast‐enhanced (DCE) MRI in patients with severe aortic stenosis (AS). The aims were to compare low‐dose (WX insensitive) and high‐dose (WX sensitive) DCE‐MRI measurements, and to compare data acquired before and after aortic valve ...
Alex Makins +5 more
wiley +1 more source
ABSTRACT Purpose To develop, optimize, and characterize a respiratory motion‐resolved free‐running isotropic 3D carotid vessel wall T1 mapping technique named CARISMAT1C. Methods An inversion‐recovery gradient‐echo free‐running pulse sequence with interleaved double flip‐angle (2FA) was implemented, and an extended‐phase‐graph dictionary was used to ...
Isabel Montón Quesada +7 more
wiley +1 more source
ABSTRACT Purpose Left ventricular (LV) strain is an early indicator of myocardial dysfunction. However, conventional strain metrics do not fully account for the multidirectional nature of myocardial deformation. The strain rate tensor, derived from velocity‐encoded MRI, represents the time‐resolved magnitude and direction of strain rate without the ...
Lasse Totland +7 more
wiley +1 more source
Reachable Workspace as a Clinical Outcome for Upper Extremity Function: A Narrative Review
ABSTRACT Motion sensing technology can be utilized to capture detailed upper extremity (UE) motion to reconstruct an individual's three‐dimensional (3D) reachable workspace (RWS). The RWS can be quantified as relative surface area (RSA), providing an innovative surrogate measure to assess UE mobility and function.
Jay J. Han +3 more
wiley +1 more source

