Intensity harmonization techniques influence radiomics features and radiomics-based predictions in sarcoma patients.

Crombé, Amandine; Kind, Michèle; Fadli, David; Le Loarer, François; Italiano, Antoine; Buy, Xavier; Saut, Olivier

Crombé, Amandine; Kind, Michèle; Fadli, David; Le Loarer, François; Italiano, Antoine; Buy, Xavier; Saut, Olivier.

Affiliation

Crombé A; Department of Radiology, Institut Bergonie, 33000, Bordeaux, France. a.crombe@bordeaux.unicancer.fr.
Kind M; Modelisation in Oncology (MOnc) Team, INRIA Bordeaux-Sud-Ouest, CNRS UMR 5251, Université de Bordeaux, 33405, Talence, France. a.crombe@bordeaux.unicancer.fr.
Fadli D; University of Bordeaux, 33000, Bordeaux, France. a.crombe@bordeaux.unicancer.fr.
Le Loarer F; Department of Diagnostic and Interventional Radiology, Institut Bergonié, Comprehensive Cancer Center of Nouvelle-Aquitaine, 229 cours de l'Argonne, 33000, Bordeaux, France. a.crombe@bordeaux.unicancer.fr.
Italiano A; Department of Radiology, Institut Bergonie, 33000, Bordeaux, France.
Buy X; Department of Radiology, Institut Bergonie, 33000, Bordeaux, France.
Saut O; University of Bordeaux, 33000, Bordeaux, France.

Sci Rep ; 10(1): 15496, 2020 09 23.

Article in En | MEDLINE | ID: mdl-32968131

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Sarcoma / Soft Tissue Neoplasms / Image Interpretation, Computer-Assisted / Supervised Machine Learning Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limits: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Language: En Journal: Sci Rep Year: 2020 Document type: Article Affiliation country: Francia Country of publication: Reino Unido

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