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Robust water–fat separation for multi‐echo gradient‐recalled echo sequence using convolutional neural network
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/jmri.22111openalex-snapshot
Phase and amplitude correction for multi‐echo water–fat separation with bipolar acquisitions
inferredcites →https://doi.org/10.1002/jmri.22580openalex-snapshot
Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy
inferredcites →https://doi.org/10.1002/mp.12600openalex-snapshot
A parallel MR imaging method using multilayer perceptron
inferredcites →https://doi.org/10.1002/mrm.10055openalex-snapshot
Elimination of Nyquist ghosting caused by read‐out to phase‐encode gradient cross‐terms in EPI
inferredcites →https://doi.org/10.1002/mrm.1910030310openalex-snapshot
High‐resolution human in vivo spectroscopic imaging using echo‐ time encoding technique
inferredcites →https://doi.org/10.1002/mrm.1910200209openalex-snapshot
Temporal and spatial analysis of fields generated by eddy currents in superconducting magnets: Optimization of corrections and quantitative characterization of magnet/gradient systems
inferredcites →https://doi.org/10.1002/mrm.1910250116openalex-snapshot
Analysis of the temporal and spatial dependence of the Eddy current fields in a 40‐cm bore magnet
inferredcites →https://doi.org/10.1002/mrm.1910360126openalex-snapshot
Artifact reduction in EPI with phase‐encoded reference scan
inferredcites →https://doi.org/10.1002/mrm.20097openalex-snapshot
Removal of EPI Nyquist ghost artifacts with two‐dimensional phase correction
inferredcites →https://doi.org/10.1002/mrm.20624openalex-snapshot
Iterative decomposition of water and fat with echo asymmetry and least‐squares estimation (IDEAL): Application with fast spin‐echo imaging
inferredcites →https://doi.org/10.1002/mrm.20654openalex-snapshot
Field map estimation with a region growing scheme for iterative 3‐point water‐fat decomposition
inferredcites →https://doi.org/10.1002/mrm.21583openalex-snapshot
Water–fat separation with bipolar multiecho sequences
inferredcites →https://doi.org/10.1002/mrm.21737openalex-snapshot
Multiecho water‐fat separation and simultaneous R estimation with multifrequency fat spectrum modeling
inferredcites →https://doi.org/10.1002/mrm.22177openalex-snapshot
Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm
inferredcites →https://doi.org/10.1002/mrm.23044openalex-snapshot
Addressing phase errors in fat‐water imaging using a mixed magnitude/complex fitting method
inferredcites →https://doi.org/10.1002/mrm.24369openalex-snapshot
ISMRM workshop on fat–water separation: Insights, applications and progress in MRI
inferredcites →https://doi.org/10.1002/mrm.24657openalex-snapshot
Fat quantification using multiecho sequences with bipolar gradients: Investigation of accuracy and noise performance
inferredcites →https://doi.org/10.1007/978-3-319-47118-1_16openalex-snapshot
Identification of Water and Fat Images in Dixon MRI Using Aggregated Patch-Based Convolutional Neural Networks
inferredcites →https://doi.org/10.1038/nature25988openalex-snapshot
Image reconstruction by domain-transform manifold learning
inferredcites →https://doi.org/10.1145/3022670.2976746openalex-snapshot
TensorFlow: learning functions at scale
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1148/radiology.153.1.6089263openalex-snapshot
Simple proton spectroscopic imaging.
inferredcites →https://doi.org/10.1162/neco_a_00052openalex-snapshot
Deep, Big, Simple Neural Nets for Handwritten Digit Recognition
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1511.05440openalex-snapshot
Deep multi-scale video prediction beyond mean square error
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4740619openalex-extracted
Deep Complex Convolutional Network in Ad-Hoc Reconstruction of Fat and Water Maps Using Multi-Echo GRE in Magnetic Resonance Imaging
inferred← citeshttps://doi.org/10.1002/jmri.28300openalex-snapshot
Deep Learning Staging of Liver Iron Content From Multiecho MR Images
inferred← citeshttps://doi.org/10.1002/mp.70101openalex-snapshot
A robust MRI water‐fat separation algorithm based on field map and fat fraction map smoothness
inferred← citeshttps://doi.org/10.1002/mrm.28586openalex-snapshot
Robust water–fat separation based on deep learning model exploring multi‐echo nature of mGRE
inferred← citeshttps://doi.org/10.1002/mrm.29172openalex-snapshot
Ultrafast water–fat separation using deep learning–based single‐shot MRI
inferred← citeshttps://doi.org/10.1002/mrm.29525openalex-snapshot
Uncertainty‐aware physics‐driven deep learning network for free‐breathing liver fat and R2* quantification using self‐gated stack‐of‐radial MRI
inferred← citeshttps://doi.org/10.1002/mrm.29774openalex-snapshot
Reducing the ambiguity of field inhomogeneity and chemical shift effect for fat–water separation by field factor
inferred← citeshttps://doi.org/10.1002/mrm.29860openalex-snapshot
Comparative review of algorithms and methods for chemical‐shift‐encoded quantitative fat‐water imaging
inferred← citeshttps://doi.org/10.1002/nbm.70216openalex-snapshot
HighRes‐Net: Physics‐Informed Deep Learning Framework for High‐Resolution Fat–Water Imaging
inferred← citeshttps://doi.org/10.1007/s00330-023-09576-2openalex-snapshot
Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes
inferred← citeshttps://doi.org/10.1007/s00330-024-11164-xopenalex-snapshot
Unbiased and reproducible liver MRI-PDFF estimation using a scan protocol-informed deep learning method
inferred← citeshttps://doi.org/10.1007/s10334-025-01268-wopenalex-snapshot
Fat–water MRI separation using deep complex convolution network
inferred← citeshttps://doi.org/10.1016/j.media.2025.103811openalex-snapshot
Non-iterative and uncertainty-aware MRI-based liver fat estimation using an unsupervised deep learning method
inferred← citeshttps://doi.org/10.1016/j.mrl.2026.200272openalex-snapshot
Physics-embedded CycleGAN for robust metabolite mapping in short-readout deuterium metabolic imaging
inferred← citeshttps://doi.org/10.1088/1361-6560/ae0efaopenalex-snapshot
Fast water/fat T 2 and PDFF mapping via multiple overlapping-echo detachment acquisition and deep learning reconstruction
inferred← citeshttps://doi.org/10.1109/isbi48211.2021.9433938openalex-snapshot
Deep Learning-Based Parameter Mapping With Uncertainty Estimation For Fat Quantification Using Accelerated Free-Breathing Radial MRI
inferred← citeshttps://doi.org/10.1109/tmi.2020.3018508openalex-snapshot
Deep Reinforcement Learning Designed Shinnar-Le Roux RF Pulse Using Root-Flipping: DeepRFSLR
inferred← citeshttps://doi.org/10.1145/3444884.3444891openalex-snapshot
Improved Robustness in Water-Fat Separation in MRI using Conditional Adversarial Networks
inferred← citeshttps://doi.org/10.1155/2019/3439468openalex-snapshot
Full-Range Liver Fat Fraction Estimation in Magnitude MRI Using a Signal Shape Descriptor
inferred← citeshttps://doi.org/10.1186/s40537-022-00677-1openalex-snapshot
Artifact-free fat-water separation in Dixon MRI using deep learning
inferred← citeshttps://doi.org/10.2463/mrms.rev.2021-0040openalex-snapshot
Deep Learning and Its Application to Function Approximation for MR in Medicine: An Overview
inferred← citeshttps://doi.org/10.3390/bioengineering9100579openalex-snapshot
Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging
inferred← citeshttps://doi.org/10.3390/electronics11182829openalex-snapshot
Fat-Corrected Pancreatic R2* Relaxometry from Multi-Echo Gradient-Recalled Echo Sequence Using Convolutional Neural Network
inferred← citeshttps://doi.org/10.6084/m9.figshare.26560955openalex-snapshot
Additional file 1 of Artifact-free fat-water separation in Dixon MRI using deep learning
inferred← citeshttps://doi.org/10.6084/m9.figshare.26560958openalex-snapshot
Additional file 2 of Artifact-free fat-water separation in Dixon MRI using deep learning
inferred← citeshttps://doi.org/10.6084/m9.figshare.26560961openalex-snapshot
Additional file 3 of Artifact-free fat-water separation in Dixon MRI using deep learning
inferred← citeshttps://doi.org/10.6084/m9.figshare.26560964openalex-snapshot
Additional file 4 of Artifact-free fat-water separation in Dixon MRI using deep learning
inferred← citeshttps://doi.org/10.6084/m9.figshare.26560967openalex-snapshot
Additional file 5 of Artifact-free fat-water separation in Dixon MRI using deep learning
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