Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning

Yannick Suter, Urspeter Knecht, Roland Wiest, Ekkehard Hewer, Philippe Schucht, Mauricio Reyes 0001. Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning. In Seyed Mostafa Kia, Hassan Mohy-ud-Din, Ahmed Abdulkadir, Cher Bass, Mohamad Habes, Jane Maryam Rondina, Chantal M. W. Tax, Hongzhi Wang 0002, Thomas Wolfers, Saima Rathore, Madhura Ingalhalikar, editors, Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology - Third International Workshop, MLCN 2020, and Second International Workshop, RNO-AI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings. Volume 12449 of Lecture Notes in Computer Science, pages 129-138, Springer, 2020. [doi]

Abstract

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