Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

Journal: Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]

Published Date: Oct 1, 2020

Abstract

BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors.

Authors

Martin Kocher
Maximilian I Ruge

Department of Stereotaxy and Functional Neurosurgery, Center for Neurosurgery, Faculty of Medicine and University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Norbert Galldiks

Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Wilhelm-Johnen-Straße, 52428, Juelich, Germany.
Philipp Lohmann

Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Juelich, Juelich, Germany.

Keywords

Brain Neoplasms Computational Biology Deep Learning Diagnosis, Differential DNA Methylation DNA Modification Methylases DNA Repair Enzymes Glioblastoma Glioma Humans Image Processing, Computer-Assisted Imaging Genomics Isocitrate Dehydrogenase Magnetic Resonance Imaging Neoplasm Grading Neoplasm Proteins Neoplasm Recurrence, Local Neuroimaging Positron-Emission Tomography Progression-Free Survival Promoter Regions, Genetic Radiation Oncology Radiosurgery Radiotherapy Planning, Computer-Assisted Sensitivity and Specificity Tumor Suppressor Proteins

External Resources

View on PubMed Access via DOI PubMed (32394100)

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

Abstract

Authors

Keywords

External Resources

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