AIMC Journal:
Magnetic resonance in medicine

Showing 151 to 160 of 217 articles

Automating in vivo cardiac diffusion tensor postprocessing with deep learning-based segmentation.

Magnetic resonance in medicine Apr 23, 2020
PURPOSE: In this work we develop and validate a fully automated postprocessing framework for in vivo diffusion tensor cardiac magnetic resonance (DT-CMR) data powered by deep learning.
Humans Neural Networks, Computer Heart Artifacts Deep Learning Magnetic Resonance Imaging
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Deep learning-based reconstruction of in vivo pelvis conductivity with a 3D patch-based convolutional neural network trained on simulated MR data.

Magnetic resonance in medicine Apr 21, 2020
PURPOSE: To demonstrate that mapping pelvis conductivity at 3T with deep learning (DL) is feasible.
Magnetic Resonance Imaging Humans Pelvis Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted
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Accelerating GluCEST imaging using deep learning for B correction.

Magnetic resonance in medicine Apr 17, 2020
PURPOSE: Glutamate weighted Chemical Exchange Saturation Transfer (GluCEST) MRI is a noninvasive technique for mapping parenchymal glutamate in the brain. Because of the sensitivity to field (B ) inhomogeneity, the total acquisition time is prolonged...
Humans Brain Brain Mapping Glutamic Acid Deep Learning Magnetic Resonance Imaging
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Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning.

Magnetic resonance in medicine Mar 13, 2020
PURPOSE: To generate fully automated and fast 4D-flow MRI-based 3D segmentations of the aorta using deep learning for reproducible quantification of aortic flow, peak velocity, and dimensions.
Aorta Deep Learning Magnetic Resonance Imaging Hemodynamics Humans Reproducibility of Results
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Deep learning-based target metabolite isolation and big data-driven measurement uncertainty estimation in proton magnetic resonance spectroscopy of the brain.

Magnetic resonance in medicine Mar 5, 2020
PURPOSE: The aim of this study was to develop a method for metabolite quantification with simultaneous measurement uncertainty estimation in deep learning-based proton magnetic resonance spectroscopy ( H-MRS).
Rats Magnetic Resonance Spectroscopy Deep Learning Big Data Proton Magnetic Resonance Spectroscopy Uncertainty Brain Reproducibility of Results Animals
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Deep learning-based MR fingerprinting ASL ReconStruction (DeepMARS).

Magnetic resonance in medicine Feb 4, 2020
PURPOSE: To develop a reproducible and fast method to reconstruct MR fingerprinting arterial spin labeling (MRF-ASL) perfusion maps using deep learning.
Magnetic Resonance Imaging Cerebrovascular Circulation Humans Spin Labels Deep Learning Moyamoya Disease
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Reconstruction of undersampled 3D non-Cartesian image-based navigators for coronary MRA using an unrolled deep learning model.

Magnetic resonance in medicine Feb 3, 2020
PURPOSE: To rapidly reconstruct undersampled 3D non-Cartesian image-based navigators (iNAVs) using an unrolled deep learning (DL) model, enabling nonrigid motion correction in coronary magnetic resonance angiography (CMRA).
Heart Imaging, Three-Dimensional Humans Magnetic Resonance Angiography Deep Learning Coronary Angiography
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Feasibility of a sub-3-minute imaging strategy for ungated quiescent interval slice-selective MRA of the extracranial carotid arteries using radial k-space sampling and deep learning-based image processing.

Magnetic resonance in medicine Jan 23, 2020
PURPOSE: To develop and test the feasibility of a sub-3-minute imaging strategy for non-contrast evaluation of the extracranial carotid arteries using ungated quiescent interval slice-selective (QISS) MRA, combining single-shot radial sampling with d...
Image Interpretation, Computer-Assisted Carotid Arteries Magnetic Resonance Angiography Deep Learning Humans Feasibility Studies
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Reconstruction of spectra from truncated free induction decays by deep learning in proton magnetic resonance spectroscopy.

Magnetic resonance in medicine Jan 8, 2020
PURPOSE: To explore the applicability of convolutional neural networks (CNNs) in the reconstruction of spectra from truncated FIDs (tFIDs) in H-MRS, which can be valuable in situations in which data sampling is highly limited, such as spectroscopic ...
Rats Magnetic Resonance Spectroscopy Animals Neural Networks, Computer Deep Learning Proton Magnetic Resonance Spectroscopy
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A Transfer-Learning Approach for Accelerated MRI Using Deep Neural Networks.

Magnetic resonance in medicine Jan 3, 2020
PURPOSE: Neural networks have received recent interest for reconstruction of undersampled MR acquisitions. Ideally, network performance should be optimized by drawing the training and testing data from the same domain. In practice, however, large dat...
Contrast Media Neural Networks, Computer Magnetic Resonance Imaging Brain Humans
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