On the public citation graph

Oxygen extraction fraction mapping at 3 Tesla using an artificial neural network: A feasibility study

0 signed · 71 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1001/archneurol.2011.2910openalex-snapshot

Addressing Diffuse Glioma as a Systemic Brain Disease With Single-Cell Analysis

inferredcites →https://doi.org/10.1002/jmri.22423openalex-snapshot

Susceptibility‐related MR signal dephasing under nonstatic conditions: Experimental verification and consequences for qBOLD measurements

inferredcites →https://doi.org/10.1002/jmri.24390openalex-snapshot

Machine learning in preoperative glioma MRI: Survival associations by perfusion‐based support vector machine outperforms traditional MRI

inferredcites →https://doi.org/10.1002/mrm.10148openalex-snapshot

Cerebral oxygen extraction fraction and cerebral venous blood volume measurements using MRI: Effects of magnetic field variation

inferredcites →https://doi.org/10.1002/mrm.1072openalex-snapshot

Water proton MR properties of human blood at 1.5 Tesla: Magnetic susceptibility, T 1 , T 2 , T , and non‐Lorentzian signal behavior

inferredcites →https://doi.org/10.1002/mrm.1910320610openalex-snapshot

Theory of NMR signal behavior in magnetically inhomogeneous tissues: The static dephasing regime

inferredcites →https://doi.org/10.1002/mrm.1910350619openalex-snapshot

Fast 3D large‐angle spin‐echo imaging (3D FLASE)

inferredcites →https://doi.org/10.1002/mrm.1910390312openalex-snapshot

Quantitation of intrinsic magnetic susceptibility‐related effects in a tissue matrix. Phantom study

inferredcites →https://doi.org/10.1002/mrm.21108openalex-snapshot

Quantitative BOLD: Mapping of human cerebral deoxygenated blood volume and oxygen extraction fraction: Default state

inferredcites →https://doi.org/10.1002/mrm.21283openalex-snapshot

Obtaining blood oxygenation levels from MR signal behavior in the presence of single venous vessels

inferredcites →https://doi.org/10.1002/mrm.22274openalex-snapshot

Validation of quantitative estimation of tissue oxygen extraction fraction and deoxygenated blood volume fraction in phantom and in vivo experiments by using MRI

inferredcites →https://doi.org/10.1002/mrm.22495openalex-snapshot

Support vector machines in DSC‐based glioma imaging: Suggestions for optimal characterization

inferredcites →https://doi.org/10.1007/978-3-319-10581-9_9openalex-snapshot

Deep Learning for Cerebellar Ataxia Classification and Functional Score Regression

inferredcites →https://doi.org/10.1007/978-3-319-46723-8_25openalex-snapshot

3D Deep Learning for Multi-modal Imaging-Guided Survival Time Prediction of Brain Tumor Patients

inferredcites →https://doi.org/10.1007/978-3-662-09334-4openalex-snapshot

Physiologie des Menschen

inferredcites →https://doi.org/10.1007/s00259-003-1430-8openalex-snapshot

Database of normal human cerebral blood flow, cerebral blood volume, cerebral oxygen extraction fraction and cerebral metabolic rate of oxygen measured by positron emission tomography with 15 O-labelled carbon dioxide or water, carbon monoxide and oxygen: a multicentre study in Japan

inferredcites →https://doi.org/10.1016/0893-6080(89)90003-8openalex-snapshot

On the approximate realization of continuous mappings by neural networks

inferredcites →https://doi.org/10.1016/0893-6080(90)90004-5openalex-snapshot

Connectionist nonparametric regression: Multilayer feedforward networks can learn arbitrary mappings

inferredcites →https://doi.org/10.1016/0893-6080(91)90009-topenalex-snapshot

Approximation capabilities of multilayer feedforward networks

inferredcites →https://doi.org/10.1016/0893-6080(91)90033-2openalex-snapshot

Creating artificial neural networks that generalize

inferredcites →https://doi.org/10.1016/j.imavis.2010.03.007openalex-snapshot

Online pattern recognition and machine learning techniques for computer-vision: Theory and applications

inferredcites →https://doi.org/10.1016/j.neuroscience.2008.08.016openalex-snapshot

Improvement of brain tissue oxygenation by inhalation of carbogen

inferredcites →https://doi.org/10.1016/j.zemedi.2008.07.005openalex-snapshot

Quantification of modulated blood oxygenation levels in single cerebral veins by investigating their MR signal decay

inferredcites →https://doi.org/10.1016/j.zemedi.2014.03.009openalex-snapshot

Non-invasive multiparametric qBOLD approach for robust mapping of the oxygen extraction fraction

inferredcites →https://doi.org/10.1016/j.zemedi.2015.10.002openalex-snapshot

Foundations of MRI phase imaging and processing for Quantitative Susceptibility Mapping (QSM)

inferredcites →https://doi.org/10.1038/nrn1387openalex-snapshot

Neurovascular regulation in the normal brain and in Alzheimer's disease

inferredcites →https://doi.org/10.1063/1.1143696openalex-snapshot

Fast curve fitting using neural networks

inferredcites →https://doi.org/10.1073/pnas.87.24.9868openalex-snapshot

Brain magnetic resonance imaging with contrast dependent on blood oxygenation.

inferredcites →https://doi.org/10.1088/0031-9155/42/3/008openalex-snapshot

Computerized classification of malignant and benign microcalcifications on mammograms: texture analysis using an artificial neural network

inferredcites →https://doi.org/10.1093/brain/awf047openalex-snapshot

Variability of cerebral blood volume and oxygen extraction: stages of cerebral haemodynamic impairment revisited

inferredcites →https://doi.org/10.1097/00004647-200008000-00008openalex-snapshot

Quantitative Measurements of Cerebral Blood Oxygen Saturation Using Magnetic Resonance Imaging

inferredcites →https://doi.org/10.1109/21.370200openalex-snapshot

Comments on "Noise injection into inputs in back propagation learning"

inferredcites →https://doi.org/10.1109/72.870040openalex-snapshot

The annealing robust backpropagation (ARBP) learning algorithm

inferredcites →https://doi.org/10.1109/tit.1963.1057854openalex-snapshot

Pattern recognition and machine learning

inferredcites →https://doi.org/10.1109/tnn.2002.804227openalex-snapshot

Robust support vector regression networks for function approximation with outliers

inferredcites →https://doi.org/10.1118/1.3213517openalex-snapshot

Noise injection for training artificial neural networks: A comparison with weight decay and early stopping

inferredcites →https://doi.org/10.1161/01.res.37.6.707openalex-snapshot

In vivo determination of cerebral blood volume with radioactive oxygen-15 in the monkey.

inferredcites →https://doi.org/10.1161/01.str.16.3.361openalex-snapshot

Positron emission tomography and its application to the study of cerebrovascular disease in man.

inferredcites →https://doi.org/10.1161/01.str.17.6.1220openalex-snapshot

Reduction in regional cerebral metabolic rate of oxygen during human aging.

inferredcites →https://doi.org/10.1162/neco.1995.7.1.108openalex-snapshot

Training with Noise is Equivalent to Tikhonov Regularization

inferredcites →https://doi.org/10.1162/neco.1996.8.3.643openalex-snapshot

The Effects of Adding Noise During Backpropagation Training on a Generalization Performance

inferredcites →https://doi.org/10.1162/neco.1997.9.5.1093openalex-snapshot

Noise Injection: Theoretical Prospects

inferredcites →https://doi.org/10.1163/156856896x00079openalex-snapshot

Machine learning paradigms for pattern recognition and image understanding

inferredcites →https://doi.org/10.2967/jnumed.108.050559openalex-snapshot

Correlative Imaging of Hypoxia and Angiogenesis in Oncology

inferredcites →https://doi.org/10.3109/09273970903234032openalex-snapshot

Pattern Recognition of Vertical Strabismus Using an Artificial Neural Network (StrabNet©)

inferredcites →https://doi.org/10.3233/bme-151459openalex-snapshot

Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network

inferredcites →https://doi.org/10.3390/cancers6010226openalex-snapshot

Glioblastoma Multiforme: A Look Inside Its Heterogeneous Nature

inferredcites →https://doi.org/10.4103/2153-3539.189703openalex-snapshot

Antibody-supervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples

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.4190247openalex-extracted

The Clinical Applications of Oxygen Extraction Fraction (OEF) Metrics: A Systematic Review

inferred← citeshttps://doi.org/10.1002/mrm.27804openalex-snapshot

Comparison of gradient echo and gradient echo sampling of spin echo sequence for the quantification of the oxygen extraction fraction from a combined quantitative susceptibility mapping and quantitative BOLD (QSM+qBOLD) approach

inferred← citeshttps://doi.org/10.1002/mrm.27882openalex-snapshot

Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD

inferred← citeshttps://doi.org/10.1002/mrm.28117openalex-snapshot

DeepCEST 3T: Robust MRI parameter determination and uncertainty quantification with neural networks—application to CEST imaging of the human brain at 3T

inferred← citeshttps://doi.org/10.1002/mrm.28344openalex-snapshot

Deep learning using a biophysical model for robust and accelerated reconstruction of quantitative, artifact‐free and denoised images

inferred← citeshttps://doi.org/10.1002/mrm.28407openalex-snapshot

Artificial neural network for multi‐echo gradient echo–based myelin water fraction estimation

inferred← citeshttps://doi.org/10.1002/mrm.29063openalex-snapshot

Optimization of spin‐lock times in T1ρ mapping of knee cartilage: Cramér‐Rao bounds versus matched sampling‐fitting

inferred← citeshttps://doi.org/10.1002/mrm.29272openalex-snapshot

Cerebral oxygen extraction fraction MRI : Techniques and applications

inferred← citeshttps://doi.org/10.1002/mrm.30165openalex-snapshot

Quantitative BOLD ( qBOLD ) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review

inferred← citeshttps://doi.org/10.1002/mrm.30555openalex-snapshot

Model‐based self‐supervised learning for quantitative assessment of myocardial oxygen extraction fraction and myocardial blood volume

inferred← citeshttps://doi.org/10.1002/mrm.70550openalex-snapshot

Free‐Breathing Hepatic Oxygen Extraction Fraction ( OEF ) Mapping Using Radial GESSE

inferred← citeshttps://doi.org/10.1002/nbm.3833openalex-snapshot

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T

inferred← citeshttps://doi.org/10.1002/nbm.4883openalex-snapshot

Deep learning‐based Accelerated and Noise‐Suppressed Estimation (DANSE) of quantitative Gradient‐Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties

inferred← citeshttps://doi.org/10.1002/nbm.70387openalex-snapshot

Noncontrast MRI Assessment of Oxygen Metabolism in Human Calf Muscles Using VSASL and ANN‐Based GESSE

inferred← citeshttps://doi.org/10.1016/j.neuroimage.2017.12.049openalex-snapshot

Multiparametric measurement of cerebral physiology using calibrated fMRI

inferred← citeshttps://doi.org/10.1016/j.neuroimage.2019.116106openalex-snapshot

Model-based Bayesian inference of brain oxygenation using quantitative BOLD

inferred← citeshttps://doi.org/10.1155/2022/4554271openalex-snapshot

Review of the Research Progress of Human Brain Oxygen Extraction Fraction by Magnetic Resonance Imaging

inferred← citeshttps://doi.org/10.13104/imri.2019.23.2.81openalex-snapshot

Deep Learning in MR Image Processing

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/10.3389/fneur.2025.1534844openalex-snapshot

Correlation of breathing task derived cerebrovascular reactivity with baseline CBF, OEF and CMRO2

inferred← citeshttps://doi.org/10.3390/bioengineering12010008openalex-snapshot

HDNLS: Hybrid Deep-Learning and Non-Linear Least Squares-Based Method for Fast Multi-Component T1ρ Mapping in the Knee Joint

inferred← citeshttps://doi.org/10.48550/arxiv.1908.10995openalex-snapshot

Real-time interactive magnetic resonance (MR) temperature imaging in both aqueous and adipose tissues using cascaded deep neural networks for MR-guided focused ultrasound surgery (MRgFUS)

inferred← citeshttps://doi.org/10.48550/arxiv.1912.07087openalex-snapshot

Deep learning using a biophysical model for Robust and Accelerated Reconstruction (RoAR) of quantitative and artifact-free R2* images

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.