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Investigating the Domain Adaptability of General-Purpose Foundation Models for Left Atrium Segmentation from MR Images

Lecture notes in computer science(2025)10.1007/978-3-031-94562-5_25Source: DataRank Database

Investigating the Domain Adaptability of General-Purpose Foundation Models for Left Atrium Segmentation from MR Images is a research paper published in Lecture notes in computer science (2025). On theSindex it has a DataRank of 0.

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (1 grants)Impact (FWCI 0.00)OA: greenTopics (25)IDs (PubMed, PMC, OpenAlex)Annotations (1)

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Accessible (1/2)

Open Access

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Reusable (0/3)

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Authors (4)

Bidur Khanal ORCID,Richard Simon ORCID,Cristian A. Linte ORCID,Bipasha Kundu

Live enrichment

PubMed:41883586 PMC:PMC13012294 OpenAlex:https://openalex.org/W4411495431

NIGMS NIH HHS

Grant: R35 GM128877

FWCI

0.00

Citation Percentile

0.1%

greenLicense: https://www.springernature.com/gp/researchers/text-and-data-mining

repositoryhttps://pmc.ncbi.nlm.nih.gov/articles/PMC13012294/

publisherhttps://link.springer.com/content/pdf/10.1007/978-3-031-94562-5_25

book serieshttps://doi.org/10.1007/978-3-031-94562-5_25

repositoryhttps://pubmed.ncbi.nlm.nih.gov/41883586

Fields of Study

Medical Image Segmentation TechniquesRadiomics and Machine Learning in Medical ImagingAdvanced Neural Network Applications

Keywords

AdaptabilityComputer scienceSegmentationDomain (mathematical analysis)Foundation (evidence)Artificial intelligenceLeft atriumComputer visionImage segmentationDomain adaptationComputer graphics (images)MedicineMathematicsGeographyManagementAtrial fibrillationSAMLeft Atrium SegmentationFoundation ModelVision Transformer ModelDinov2Medsam-V1

Investigating the Domain Adaptability of General-Purpose Foundation Models for Left Atrium Segmentation from MR Images

FAIR Checklist

Authors (4)

Funding (1 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)