Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques

Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques

Abstract Background This study aims to identify robust radiomic features for Magnetic Resonance Imaging (MRI), assess feature selection and machine learning methods for overall survival classification of Glioblastoma multiforme patients, and to robustify models trained on single-center data when app...

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Bibliographic Details
Main Authors: Yannick Suter, Urspeter Knecht, Mariana Alão, Waldo Valenzuela, Ekkehard Hewer, Philippe Schucht, Roland Wiest, Mauricio Reyes
Format: Article
Language:English
Published: BMC 2020-08-01
Series:Cancer Imaging
Subjects:
Glioblastoma multiforme
MRI radiomics
Overall survival classification
Multi-center
Robustness
Online Access:http://link.springer.com/article/10.1186/s40644-020-00329-8

Internet

http://link.springer.com/article/10.1186/s40644-020-00329-8

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