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Development of multiscale 3D residual U-Net to segment edematous adipose tissue by leveraging annotations from non-edematous adipose tissue

PubMed(2023)10.1117/12.2669719Source: DataRank Database

Development of multiscale 3D residual U-Net to segment edematous adipose tissue by leveraging annotations from non-edematous adipose tissue is a research paper published in PubMed (2023). On theSindex it has a DataRank of 0. It has been cited 2 times.

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0DataRank · unranked

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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 (1 grants)OA: greenTopics (20)IDs (PubMed, PMC, 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 (3)

Omid Shafaat ORCID,Ronald M. Summers ORCID,Jianfei Liu ORCID

Live enrichment

PubMed:40256010 PMC:PMC12007116 OpenAlex:https://openalex.org/W4323309591

Intramural NIH HHS

Grant: Z01 CL040004

green

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/12007116

http://dx.doi.org/10.1117/12.2669719

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40256010

Fields of Study

Cardiovascular Disease and AdiposityThermoregulation and physiological responsesBody Composition Measurement Techniques

Keywords

Adipose tissueComputer scienceSegmentationAnasarcaArtificial intelligenceAnnotationResidualPattern recognition (psychology)MedicineAlgorithmSurgeryInternal medicineEdemaData AnnotationMulti-scale Feature Fusion3D Residual U-netAdipose Tissue Segmentation