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Using a Generative Adversarial Network for CT Normalization and its Impact on Radiomic Features

arXiv (Cornell University)(2020)10.48550/arxiv.2001.08741Source: DataRank Database

Using a Generative Adversarial Network for CT Normalization and its Impact on Radiomic Features is a research paper published in arXiv (Cornell University) (2020). On theSindex it has a DataRank of 0.241. It has been cited 4 times.

N/A

0.241DataRank · unranked

Scored on demand from live citation data

Open Access4 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)OA: greenTopics (44)IDs (PubMed, OpenAlex)

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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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.241

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (3)

Yannan Lin ORCID,William Hsu ORCID,Leihao Wei

Live enrichment

PubMed:21097893 OpenAlex:https://openalex.org/W3001949958

National Science Foundation

Grant: 1722516

SCH: INT: Personalized Real-Time Learning of Optimal Diagnostic Tests using Multi-Modal Clinical Data

National Institutes of Health

Grant: 5R01CA210360-02

Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary Nodules

greenLicense: IEEE Copyright

repositoryhttps://arxiv.org/pdf/2001.08741

repositoryhttp://arxiv.org/abs/2001.08741

repositoryhttps://escholarship.org/uc/item/5ms7n1gd

repositoryhttps://doi.org/10.48550/arxiv.2001.08741

https://doi.org/10.1109/isbi45749.2020.9098724

Fields of Study

Radiomics and Machine Learning in Medical ImagingAI in cancer detectionAdvanced Image Processing TechniquesImage and Video Processing (eess.IV)Computer Vision and Pattern Recognition (cs.CV)Machine Learning (cs.LG)Machine Learning (stat.ML)FOS: Electrical engineering, electronic engineering, information engineeringFOS: Computer and information sciences03 medical and health sciences0302 clinical medicine

Keywords

Normalization (sociology)Artificial intelligenceGenerative adversarial networkComputer sciencePattern recognition (psychology)Similarity (geometry)Feature (linguistics)Image qualityProjection (relational algebra)Computer visionImage (mathematics)Nuclear medicineMedicineAlgorithmFOS: Computer and information sciencesComputer Science - Machine LearningComputer Vision and Pattern Recognition (cs.CV)cs.LGImage and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern RecognitionMachine Learning (stat.ML)Electrical Engineering and Systems Science - Image and Video Processingstat.MLMachine Learning (cs.LG)lung cancerdeep neural networksradiomicsStatistics - Machine LearningdenoisingFOS: Electrical engineering, electronic engineering, information engineeringeess.IVgenerative adversarial networkscs.CV