ArticleMagnetic resonance in medicine2021
Deep neural network for water/fat separation: Supervised training, unsupervised training, and no training.
Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The trial behind it
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Who cites it
14 citing papers in PubMed.
- Fat-water MRI separation using deep complex convolution network.Magma (New York, N.Y.) · 2025Article
- Estimation of fatty acid composition in mammary adipose tissue using deep neural network with unsupervised training.Magnetic resonance in medicine · 2025Article
- Real-time water/fat imaging at 0.55T with spiral out-in-out-in sampling.Magnetic resonance in medicine · 2024Article
- What Is Machine Learning, Artificial Neural Networks and Deep Learning?-Examples of Practical Applications in Medicine.Diagnostics (Basel, Switzerland) · 2023Review
- Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping.Magnetic resonance in medicine · 2023Article
- A low-rank deep image prior reconstruction for free-breathing ungated spiral functional CMR at 0.55 T and 1.5 T.Magma (New York, N.Y.) · 2023Article
- QSM Throughout the Body.Journal of magnetic resonance imaging : JMRI · 2023Review
- Uncertainty-aware physics-driven deep learning network for free-breathing liver fat and RMagnetic resonance in medicine · 2023Article
- LARO: Learned acquisition and reconstruction optimization to accelerate quantitative susceptibility mapping.NeuroImage · 2023Article
- GRASPNET: Fast spatiotemporal deep learning reconstruction of golden-angle radial data for free-breathing dynamic contrast-enhanced magnetic resonance imaging.NMR in biomedicine · 2023Article
- Artifact-free fat-water separation in Dixon MRI using deep learning.Journal of big data · 2023Article
- QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.Magnetic resonance in medicine · 2022Article
- Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation.Computational and mathematical methods in medicine · 2022Article
- Multi-muscle deep learning segmentation to automate the quantification of muscle fat infiltration in cervical spine conditions.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
purposeTo use a deep neural network (DNN) for solving the optimization problem of water/fat separation and to compare supervised and unsupervised training.
methodsThe current
resultsAll DNN methods generated consistent water/fat separation results that agreed well with
conclusionThe water/fat separation problem can be solved using unsupervised deep neural networks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.