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Adversarial Robust Training of Deep Learning MRI Reconstruction Models

The Journal of Machine Learning for Biomedical Imaging(2021)10.59275/j.melba.2021-df47Source: DataRank Database

Adversarial Robust Training of Deep Learning MRI Reconstruction Models is a research paper published in The Journal of Machine Learning for Biomedical Imaging (2021). On theSindex it has a DataRank of 0.292. It has been cited 6 times.

N/A

0.292DataRank · unranked

Scored on demand from live citation data

Open Access6 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (1 grants)Impact (FWCI 0.29)OA: closedTopics (27)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.292

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (4)

Kaiyang Cheng ORCID,Rutwik Shah ORCID,Valentina Pedoia ORCID,Francesco Calivá ORCID

Live enrichment

PubMed:20819859 OpenAlex:https://openalex.org/W3156072047

National Institutes of Health

Grant: 4R00AR070902-02

Multidimensional MRI-based Non-Euclidean Deep Learning to Study Osteoarthritis

FWCI

0.29

Citation Percentile

0.5%

Citation Trend

2021

2023

2025

closedLicense: CC BY

publisherhttp://melba-journal.org/pdf/2021:007.pdf

journalhttps://doi.org/10.59275/j.melba.2021-df47

https://dx.doi.org/10.48550/arxiv.2011.00070

http://arxiv.org/abs/2011.00070

Fields of Study

Advanced X-ray and CT ImagingMedical Imaging Techniques and ApplicationsAdversarial Robustness in Machine Learning0202 electrical engineering, electronic engineering, information engineering02 engineering and technology01 natural sciences0105 earth and related environmental sciences

Keywords

Computer scienceArtificial intelligenceIterative reconstructionDeep learningGeneralizationMachine learningWorkflowSet (abstract data type)Fidelity3D reconstructionCode (set theory)Pattern recognition (psychology)Computer visionMathematicsFOS: Computer and information sciencesComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionFOS: Electrical engineering, electronic engineering, information engineeringElectrical Engineering and Systems Science - Image and Video Processing

Sustainable Development Goals

SDG 0: Sustainable cities and communities