Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation-Reference-Cited by-同舟云学术

Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation

Published:2023-09-04 Issue: Volume: Page:
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Cheong E.-Nae,Park Ji Eun^ORCID,Park Seo Young,Jung Seung Chai,Kim Ho Sung

Funder

Ministry of Health and Welfare

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-023-10164-7.pdf

Reference37 articles.

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3. Park CM (2019) Can artificial intelligence fix the reproducibility problem of radiomics? Radiology 292:374–375

4. Gillies RJ, Kinahan PE, Hricak H (2016) Radiomics: images are more than pictures, they are data. Radiology 278:563–577

5. Park JE, Park SY, Kim HJ, Kim HS (2019) Reproducibility and generalizability in radiomics modeling: possible strategies in radiologic and statistical perspectives. Korean J Radiol 20:1124–1137

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