Results 161 to 170 of about 13,553 (263)
Directionally factorized light field reconstruction with cross-epipolar and spatial modeling. [PDF]
Salem A +4 more
europepmc +1 more source
ABSTRACT Purpose To integrate MR‐based servo navigation in MPRAGE and 3D‐TSE sequences and demonstrate its potential for prospective head motion correction in structural imaging. Methods Repeated modules of servo navigators were inserted before each preparation pulse of MPRAGE and 3D‐TSE sequences (before‐prep) for rapid convergence of motion parameter
Matthias Serger +7 more
wiley +1 more source
Video quality prediction and classification using XGBoost under variable encoding and network conditions. [PDF]
Frnda J +4 more
europepmc +1 more source
ABSTRACT Purpose We introduce DeepRelaxo, a fast and generalizable deep learning method for estimating brain R2* maps from multi‐echo gradient echo (ME‐GRE) acquisitions with arbitrary echo configurations, including shortened echo trains for accelerated scans.
Samiha Prima +3 more
wiley +1 more source
Image reconstruction from incomplete data via approximated pseudo-inverse and dual-domain coupled diffusion posterior sampling. [PDF]
Xing Q +5 more
europepmc +1 more source
Time‐Conditioned Zero‐Shot Self‐Supervised Reconstruction for Accelerated 3D Ultra‐Low‐Field MRI
ABSTRACT Purpose Ultra‐low‐field (ULF) MRI provides a cost‐effective, portable imaging option but has relatively low SNR and long acquisition times compared to standard clinical scans. This study presents a time‐conditioned zero‐shot self‐supervised learning image reconstruction framework (ULF‐ZS‐SSL) to accelerate 3D‐acquired single‐coil ULF MRI ...
Mart W. J. van Straten +6 more
wiley +1 more source
Radon-Guided Wavelet-Domain Attention U-Net for Periodic Artifact Suppression in Brain MRI. [PDF]
Rios-Perez JD +4 more
europepmc +1 more source
ABSTRACT Purpose To propose a new method using a physics‐guided neural network for quantitative parameter mapping in balanced steady‐state free precession (bSSFP) imaging. Theory and Methods We trained physics‐guided neural networks with a multilayer perceptron using simulated bSSFP signals generated from tissue parameters (T1, T2,Meffc, ∆f and φRF ...
Hye‐Ryeong Choi +2 more
wiley +1 more source
FMDNet: Spatial-frequency feature routing for low-dose CT denoising. [PDF]
Yao Y +6 more
europepmc +1 more source

