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Application of a virtual imaging framework for investigating a deep learning-based reconstruction method for 3D quantitative photoacoustic computed tomography

Photoacoustics(2025)10.1016/j.pacs.2025.100792Source: DataRank Database

Application of a virtual imaging framework for investigating a deep learning-based reconstruction method for 3D quantitative photoacoustic computed tomography is a research paper published in Photoacoustics (2025). On theSindex it has a DataRank of 0. It has been cited 1 time.

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Open Access1 citations

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Anatomy-Matched Multi-Variant Stochastic Optoacoustic Numerical Breast Phantoms and Simulated OAT Measurement Data · University of Illinois Urbana-Champaign

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (11 grants)Impact (FWCI 0.31)OA: goldTopics (15)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, PMC, OpenAlex)Annotations (1)

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Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

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Reusable (0/3)

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Authors (4)

Seonyeong Park ORCID,Umberto Villa ORCID,Mark A. Anastasio ORCID,Refik Mert Cam

Live enrichment

PubMed:41626289 PMC:PMC12858365 OpenAlex:https://openalex.org/W7117472420

National Science Foundation

Grant: 2138286

National Science Foundation

Grant: 2138307

National Science Foundation

Grant: 2138259

National Science Foundation

Grant: 2137603

National Science Foundation

Grant: 2138296

National Institutes of Health

Grant: EB034249

National Institutes of Health

Grant: EB034261

National Institutes of Health

Grant: EB031585

National Institutes of Health

Grant: EB031772

National Institutes of Health

Grant: MDE230007

NIBIB NIH HHS

Grant: P41 EB031772

FWCI

0.31

Citation Percentile

0.6%

Citation Trend

2026

goldLicense: cc-by-nc-nd

journalhttps://doi.org/10.1016/j.pacs.2025.100792

publisherhttps://doi.org/10.1016/j.pacs.2025.100792

publisherhttps://api.elsevier.com/content/article/PII:S2213597925001156?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2213597925001156?httpAccept=text/plain

repositoryhttps://pubmed.ncbi.nlm.nih.gov/41626289

Fields of Study

Photoacoustic and Ultrasonic ImagingThermography and Photoacoustic TechniquesInfrared Thermography in Medicine

Keywords

Imaging phantomPhotoacoustic imaging in biomedicinePhotoacoustic tomographyIterative reconstructionTestbedComputed tomographyModality (human–computer interaction)Noise (video)Breast ImagingNumerical Breast PhantomsQuantitative Photoacoustic Computed TomographyVirtual Imaging Studies

Anatomy-Matched Multi-Variant Stochastic Optoacoustic Numerical Breast Phantoms and Simulated OAT Measurement Data

10.13012/b2idb-8164905_v1University of Illinois Urbana-Champaign

Application of a virtual imaging framework for investigating a deep learning-based reconstruction method for 3D quantitative photoacoustic computed tomography

FAIR Checklist

Authors (4)

Funding (11 grants)

Impact

Open Access

Topics

Linked Datasets (1)

Annotations (Europe PMC)