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Spatially regularized low-rank tensor approximation for accurate and fast tractography

NeuroImage(2023)10.1016/j.neuroimage.2023.120004Source: DataRank Database

Spatially regularized low-rank tensor approximation for accurate and fast tractography is a research paper published in NeuroImage (2023). On theSindex it has a DataRank of 0. It has been cited 8 times.

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Open Access8 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (7 grants)OA: goldTopics (27)IDs (PubMed)

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Authors (3)

Samuel Groeschel ORCID,Thomas Schultz ORCID,Johannes Gruen

Live enrichment

PubMed:36898487

Deutsche Forschungsgemeinschaft

Grant: 422414649

Deutsche Forschungsgemeinschaft

Grant: 1U54MH091657

NIMH NIH HHS

Grant: U54 MH091657

Deutsche Forschungsgemeinschaft

Grant: unidentified

unidentified

McDonnell Center for Systems Neuroscience

National Institutes of Health

NIH Blueprint for Neuroscience Research

goldLicense: cc-by

publisherhttps://doi.org/10.1016/j.neuroimage.2023.120004

publisherhttps://api.elsevier.com/content/article/PII:S1053811923001507?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S1053811923001507?httpAccept=text/plain

repositoryhttps://doaj.org/article/7780b939c1494ef4936db0198dcf80e7

https://pubmed.ncbi.nlm.nih.gov/36898487

Fields of Study

HumansDiffusion Tensor ImagingImage Processing, Computer-AssistedDiffusion Magnetic Resonance ImagingBrainAlgorithmsWhite Matter

MeSH Terms

BrainHumansDiffusion Magnetic Resonance ImagingAlgorithmsImage Processing, Computer-AssistedDiffusion Tensor ImagingWhite Matter

Keywords

Diffusion MriTractographyUnscented Kalman filterJoint Tensor ApproximationDiffusion Tensor ImagingDiffusion Magnetic Resonance ImagingImage Processing, Computer-AssistedHumansBrainNeurosciences. Biological psychiatry. NeuropsychiatryWhite MatterAlgorithmsRC321-571