Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

A Radiological Clip Design Using Ultrasound Identification to Improve Localization

arXiv (Cornell University)(2023)10.48550/arxiv.2308.16319Source: DataRank Database

A Radiological Clip Design Using Ultrasound Identification to Improve Localization is a research paper published in arXiv (Cornell University) (2023). On theSindex it has a DataRank of 0.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access0 citations

Free full text

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)OA: greenTopics (28)IDs (PubMed, OpenAlex)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)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (6)

Zhengchang Kou ORCID,Miller, Rita J.,April Dickenson ORCID,Christine U. Lee ORCID,Michael L. Oelze ORCID

Live enrichment

PubMed:19276002 OpenAlex:https://openalex.org/W4386393888

National Institutes of Health

Grant: 1R01CA273700-01

Developing a quantitative ultrasound breast scanner for identifying early response of breast cancer to chemotherapy

National Institutes of Health

Grant: 1R21EB030743-01A1

Development of radiological clips having ultrasound identification

National Institutes of Health

Grant: 5R01CA251939-04

Use of Radiological Clips for Improving Quantitative Ultrasound Imaging

greenLicense: cc-by-nc-nd

repositoryhttps://arxiv.org/pdf/2308.16319

repositoryhttp://arxiv.org/abs/2308.16319

repositoryhttps://doi.org/10.48550/arxiv.2308.16319

https://doi.org/10.1109/tbme.2024.3388203

https://dx.doi.org/10.48550/arxiv.2308.16319

Fields of Study

Wireless Body Area NetworksSignal Processing (eess.SP)FOS: Electrical engineering, electronic engineering, information engineering

Keywords

Imaging phantomUltrasoundCLIPSUltrasonic sensorTransducerComputer scienceSIGNAL (programming language)Biomedical engineeringNuclear medicineComputer visionArtificial intelligenceRadiologyMedicineAcousticsPhysicsSignal Processing (eess.SP)Phantoms, ImagingTransducersFOS: Electrical engineering, electronic engineering, information engineeringHumansSignal Processing, Computer-AssistedEquipment DesignElectrical Engineering and Systems Science - Signal ProcessingArticleUltrasonography

Sustainable Development Goals

SDG 0: Good health and well-being