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Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture

International Journal of Computer Assisted Radiology and Surgery(2025)10.1007/s11548-025-03323-2Source: DataRank Database

Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture is a research paper published in International Journal of Computer Assisted Radiology and Surgery (2025). On theSindex it has a DataRank of 0. It has been cited 2 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access2 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 1.41)OA: hybridTopics (50)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (7)

Jorge Cisneros ORCID,Girish B. Nair ORCID,Craig Stevens ORCID,Richard Castillo ORCID,Yevgeniy Vinogradskiy ORCID

Live enrichment

PubMed:39832070 PMC:PMC12055896 OpenAlex:https://openalex.org/W4406628739

NIH National Cancer Institute

Grant: R01CA236857

NHLBI NIH HHS

Grant: R01 HL169869

NCI NIH HHS

Grant: UH3 CA247605

National Institutes of Health

Grant: 3R01CA236857-05S1

Development of a Novel Lung Function Imaging Modality for comprehensive management of lung cancer

FWCI

1.41

Citation Percentile

0.8%

Citation Trend

2026

hybridLicense: cc-by

journalhttps://link.springer.com/content/pdf/10.1007/s11548-025-03323-2.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/s11548-025-03323-2.pdf

publisherhttps://link.springer.com/article/10.1007/s11548-025-03323-2/fulltext.html

journalhttps://doi.org/10.1007/s11548-025-03323-2

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39832070

Fields of Study

Effects of Radiation ExposureLung Cancer Diagnosis and TreatmentUltrasound in Clinical Applications0202 electrical engineering, electronic engineering, information engineering02 engineering and technologyHumansPerfusion ImagingSupervised Machine LearningDeep LearningTomography, X-Ray ComputedMaleLungFemaleFour-Dimensional Computed TomographyMiddle Aged

MeSH Terms

Supervised Machine LearningDeep LearningFemaleHumansLungMaleMiddle AgedTomography, X-Ray ComputedPerfusion ImagingFour-Dimensional Computed Tomography

Keywords

Artificial intelligenceComputer scienceFeature (linguistics)Deep learningMedical imagingPerfusion scanningMachine learningMedicinePattern recognition (psychology)PerfusionRadiologycomputed tomographyPulmonary PerfusionSelf-supervised LearningVision TransformerMalePerfusion ImagingHumansOriginal ArticleFemaleSupervised Machine LearningFour-Dimensional Computed TomographyMiddle AgedTomography, X-Ray ComputedLung

Sustainable Development Goals

SDG 0: Good health and well-being

Perfusion estimation from dynamic non-contrast computed tomography using self-supervised learning and a physics-inspired U-net transformer architecture

FAIR Checklist

Authors (7)

Funding (4 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)