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maskNMF: A denoise-sparsen-detect approach for extracting neural signals from dense imaging data

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.09.14.557777Source: DataRank Database

maskNMF: A denoise-sparsen-detect approach for extracting neural signals from dense imaging data is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 2 times.

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Open Access2 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)OA: greenTopics (18)IDs (PubMed, OpenAlex)

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Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (12)

Ian Kinsella,Pengcheng Zhou ORCID,Melissa M. Wu ORCID,Daisong Pan ORCID,Jiang Lan Fan ORCID

Live enrichment

PubMed:37745388 OpenAlex:https://openalex.org/W4386759852

NINDS NIH HHS

Grant: U01 NS103489

NINDS NIH HHS

Grant: U19 NS104649

NINDS NIH HHS

Grant: U19 NS107613

NINDS NIH HHS

Grant: U19 NS123716

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/09/15/2023.09.14.557777.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.09.14.557777

repositoryhttps://doi.org/10.1101/2023.09.14.557777

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37745388

Fields of Study

Cell Image Analysis TechniquesAdvanced Fluorescence Microscopy TechniquesNeural dynamics and brain function

Keywords

Computer sciencePipeline (software)Artificial intelligenceArtificial neural networkCalcium imagingNon-negative matrix factorizationPattern recognition (psychology)PixelComputer visionMatrix decompositionPhysicsMaterials scienceBessel imagingdemixingopen-source software