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Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time
Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time
Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonan...
Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping
Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping
Quantitative susceptibility mapping (QSM) provides an estimate of the magnetic susceptibility of tissue using magnetic res...
Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R1·R2* and myelin water fraction in white matter
Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R1·R2* and myelin water fraction in white matter
To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF ...
Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI
Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI
To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and e...
Reply to Comment on ‘Nanodiamond incorporated human liver mimicking phantoms: prospective calibration medium of magnetic resonance imaging’
Reply to Comment on ‘Nanodiamond incorporated human liver mimicking phantoms: prospective calibration medium of magnetic resonance imaging’
Department of Metrology and Optoelectronics, Faculty of Electronics, Telecommunications and Informatics, Gdańsk University...
Late/delayed gadolinium enhancement in MRI after intravenous administration of extracellular gadolinium-based contrast agents: is it worth waiting?
Late/delayed gadolinium enhancement in MRI after intravenous administration of extracellular gadolinium-based contrast agents: is it worth waiting?
The acquisition of images minutes or even hours after intravenous extracellular gadolinium-based contrast agents (GBCA) ad...
Stop moving: MR motion correction as an opportunity for artificial intelligence
Stop moving: MR motion correction as an opportunity for artificial intelligence
Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can seriously deteriorate the image q...
Improved reconstruction for highly accelerated propeller diffusion 1.5 T clinical MRI
Improved reconstruction for highly accelerated propeller diffusion 1.5 T clinical MRI
Propeller fast-spin-echo diffusion magnetic resonance imaging (FSE-dMRI) is essential for the diagnosis of Cholesteatoma. ...
Multi-target field control for matrix gradient coils
Multi-target field control for matrix gradient coils
Conventional single-target field control for matrix gradient coils will add control complexity in MRI spatial encoding, su...
Impact of truncating diffusion MRI scans on diffusional kurtosis imaging
Impact of truncating diffusion MRI scans on diffusional kurtosis imaging
Diffusional kurtosis imaging (DKI) extends diffusion tensor imaging (DTI), characterizing non-Gaussian diffusion effects b...
Diffusion weighted imaging combining respiratory triggering and navigator echo tracking in the upper abdomen
Diffusion weighted imaging combining respiratory triggering and navigator echo tracking in the upper abdomen
To evaluate a new motion correction method, named RT + NV Track, for upper abdominal DWI that combines the res...
Fast online spectral-spatial pulse design for subject-specific fat saturation in cervical spine and foot imaging at 1.5 T
Fast online spectral-spatial pulse design for subject-specific fat saturation in cervical spine and foot imaging at 1.5 T
To compensate subject-specific field inhomogeneities and enhance fat pre-saturation with a fast online individual spectral...
High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising
High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising
To develop and evaluate a technique combining eddy current-nulled convex optimized diffusion encoding (ENCODE) with random...
Linearity and bias of proton density fat fraction across the full dynamic range of 0–100%: a multiplatform, multivendor phantom study using 1.5T and 3T MRI at two sites
Linearity and bias of proton density fat fraction across the full dynamic range of 0–100%: a multiplatform, multivendor phantom study using 1.5T and 3T MRI at two sites
Performance assessments of quantitative determinations of proton density fat fraction (PDFF) have largely focused on the r...
Cross2SynNet: cross-device–cross-modal synthesis of routine brain MRI sequences from CT with brain lesion
Cross2SynNet: cross-device–cross-modal synthesis of routine brain MRI sequences from CT with brain lesion
CT and MR are often needed to determine the location and extent of brain lesions collectively to improve diagnosis. Howeve...
Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs
Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs
Increased subcutaneous and visceral adipose tissue (SAT/VAT) volume is associated with risk for cardiometabolic diseases. ...
Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis
Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis
Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischemic brain injury can provide assistance in the prognosis of...
Nonuniform sliding-window reconstruction for accelerated dual contrast agent quantification with MR fingerprinting
Nonuniform sliding-window reconstruction for accelerated dual contrast agent quantification with MR fingerprinting
MR fingerprinting (MRF) can enable preclinical studies of cell tracking by quantifying multiple contrast agents simultaneo...
The possible influence of third-order shim coils on gradient–magnet interactions: an inter-field and inter-site study
The possible influence of third-order shim coils on gradient–magnet interactions: an inter-field and inter-site study
To assess the possible influence of third-order shim coils on the behavior of the gradient field and in gradient–mag...
STEAM-SASHA: a novel approach for blood- and fat-suppressed native T1 measurement in the right ventricular myocardium
STEAM-SASHA: a novel approach for blood- and fat-suppressed native T1 measurement in the right ventricular myocardium
The excellent blood and fat suppression of stimulated echo acquisition mode (STEAM) can be combined with saturation recove...
Detection of hypoplastic left heart syndrome anatomy from cardiovascular magnetic resonance images using machine learning
Detection of hypoplastic left heart syndrome anatomy from cardiovascular magnetic resonance images using machine learning
The prospect of being able to gain relevant information from cardiovascular magnetic resonance (CMR) image analysis automa...
Quantification of neurovascular compliance with retrospectively gated phase-contrast MRI
Quantification of neurovascular compliance with retrospectively gated phase-contrast MRI
Neurovascular compliance (NVC) is the change in the brain’s arterial tree blood volume, ΔV, divided by the chan...
Field camera input to virtual phantom (ViP) scanner acquisitions for quality assurance of derived MRI quantities: first implementation and proof-of-principle
Field camera input to virtual phantom (ViP) scanner acquisitions for quality assurance of derived MRI quantities: first implementation and proof-of-principle
Quality assurance (QA) of measurements derived from MRI can require complicated test phantoms. This work introduces a new ...
Correction to: Book of Abstracts ESMRMB 2023 Online 39th Annual Scientific Meeting 4–7 October 2023
Correction to: Book of Abstracts ESMRMB 2023 Online 39th Annual Scientific Meeting 4–7 October 2023
Correction to: Magn Reson Mater Phy (2023) 36:S1–S328 https://doi.org/10.1007/s10334-...
A short-TR single-echo spin-echo breath-hold method for assessing liver T2
A short-TR single-echo spin-echo breath-hold method for assessing liver T2
Conventional single-echo spin-echo T2 mapping used for liver iron quantification is too long for breath-holding. This stud...
FastPtx: a versatile toolbox for rapid, joint design of pTx RF and gradient pulses using Pytorch’s autodifferentiation
FastPtx: a versatile toolbox for rapid, joint design of pTx RF and gradient pulses using Pytorch’s autodifferentiation
With modern optimization methods, free optimization of parallel transmit pulses together with their gradient waveforms can...
Liver T1 and T2 mapping in a large cohort of healthy subjects: normal ranges and correlation with age and sex
Liver T1 and T2 mapping in a large cohort of healthy subjects: normal ranges and correlation with age and sex
We established normal ranges for native T1 and T2 values in the human liver using a 1.5 T whole-body imager (Gene...
Automatic segmentation of the interscapular brown adipose tissue in rats based on deep learning using the dynamic magnetic resonance fat fraction images
Automatic segmentation of the interscapular brown adipose tissue in rats based on deep learning using the dynamic magnetic resonance fat fraction images
The study aims to propose an accurate labelling method of interscapular BAT (iBAT) in rats using dynamic MR fat fraction (...
Improvement of image quality in diffusion-weighted imaging with model-based deep learning reconstruction for evaluations of the head and neck
Improvement of image quality in diffusion-weighted imaging with model-based deep learning reconstruction for evaluations of the head and neck
To investigate the utility of deep learning (DL)-based image reconstruction using a model-based approach in head and neck ...
Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI
Learning to deep learning: statistics and a paradigm test in selecting a UNet architecture to enhance MRI
This study aims to assess the statistical significance of training parameters in 240 dense UNets (DUNets) used for enhanci...
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