Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review

[Display omitted] oMachine learning has been widely applied to MRI to detect and diagnose gliomas.oNon-invasive detection of genetics has the potential to supersede biopsy procedures.oMachine learning has demonstrated strong performance and clinical utility.oPerformance metrics from 153 articles wer...

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Veröffentlicht in:	Journal of clinical neuroscience Jg. 89; S. 177 - 198
Hauptverfasser:	Buchlak, Quinlan D., Esmaili, Nazanin, Leveque, Jean-Christophe, Bennett, Christine, Farrokhi, Farrokh, Piccardi, Massimo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2021
Schlagworte:	Brain tumor classification Convolutional neural networks Deep learning FLAIR Glioblastoma Glioma Glioma grading Image processing Machine learning Multimodal neuroimaging Neurosurgery Radiomics T1-MR image T2-MR image T1-MR image Image processing Multimodal neuroimaging Glioblastoma Glioma grading Neurosurgery Radiomics Deep learning Brain tumor classification Glioma T2-MR image Machine learning FLAIR Convolutional neural networks
ISSN:	0967-5868, 1532-2653, 1532-2653
Online-Zugang:	Volltext
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