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Conditional generative adversarial network (cGAN) for synthesis of digital histologic images from hyperspectral images

PubMed(2023)10.1117/12.2653715Source: DataRank Database

Conditional generative adversarial network (cGAN) for synthesis of digital histologic images from hyperspectral images is a research paper published in PubMed (2023). On theSindex it has a DataRank of 0. It has been cited 3 times.

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0DataRank · unranked

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Open Access3 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 (20)IDs (PubMed, OpenAlex)

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (4)

Jeremy C. Sherey,Doreen N. Palsgrove ORCID,Baowei Fei ORCID,Ling Ma ORCID

Live enrichment

PubMed:38495871 OpenAlex:https://openalex.org/W4362693635

NCI NIH HHS

Grant: R01 CA156775

NCI NIH HHS

Grant: R01 CA204254

NHLBI NIH HHS

Grant: R01 HL140325

NCI NIH HHS

Grant: R21 CA231911

green

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10942653/pdf/nihms-1973768.pdf

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/10942653

https://doi.org/10.1117/12.2653715

repositoryhttps://pubmed.ncbi.nlm.nih.gov/38495871

Fields of Study

AI in cancer detectionCell Image Analysis TechniquesImage Processing Techniques and Applications

Keywords

Hyperspectral imagingArtificial intelligenceRGB color modelGround truthComputer scienceComputer visionGenerative adversarial networkPattern recognition (psychology)MagnificationVisualizationImage (mathematics)Hyperspectral imaging (HSI)computationalconditional generative adversarial network (cGAN)digital pathologyhistologic imagenatural-color visualization