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Associations between radiologist-defined semantic and automatically computed radiomic features in no...

Associations between radiologist-defined semantic and automatically computed radiomic features in no...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d55a79bca4be44c7ac340a26b1dcd18b

Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer

About this item

Full title

Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2017-06, Vol.7 (1), p.3519-11, Article 3519

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Tumor phenotypes captured in computed tomography (CT) images can be described qualitatively and quantitatively using radiologist-defined “semantic” and computer-derived “radiomic” features, respectively. While both types of features have shown to be promising predictors of prognosis, the association between these groups of features remains unclear....

Alternative Titles

Full title

Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_d55a79bca4be44c7ac340a26b1dcd18b

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_d55a79bca4be44c7ac340a26b1dcd18b

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-017-02425-5

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