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Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-Empowered Learning

Lecture notes in computer science(2023)10.1007/978-3-031-43987-2_48Source: DataRank Database

Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-Empowered Learning is a research paper published in Lecture notes in computer science (2023). On theSindex it has a DataRank of 0. It has been cited 6 times.

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Open Access6 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)OA: greenTopics (12)IDs (PubMed, PMC)

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Open Access

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Authors (14)

Yanwei Li ORCID,Peize Li ORCID,Jiacheng Wang ORCID,Lucas W. Remedios,Saydolimkhon Agzamkhodjaev

Live enrichment

PubMed:38529367 PMC:PMC10961594

NIDDK NIH HHS

Grant: R01 DK056942

NIDDK NIH HHS

Grant: R01 DK135597

National Institutes of Health

Grant: 1R01DK135597-01

AI-empowered 3D Computer Vision and Image-Omics Integration for Digital Kidney Histopathology

National Institutes of Health

Grant: 5R01DK056942-07

Resolution of Glomerulosclerosis

greenLicense: Springer Nature TDM

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC10961594/pdf/nihms-1934700.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/978-3-031-43987-2_48

https://doi.org/10.1007/978-3-031-43987-2_48

https://dx.doi.org/10.48550/arxiv.2306.00047

https://pubmed.ncbi.nlm.nih.gov/38529367

Fields of Study

0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

PathologyRegistrationImage AnnotationNoisy Label LearningFOS: 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