Radiomics-Based Machine Learning Technology Enables Better Differentiation Between Glioblastoma and Anaplastic Oligodendroglioma

Radiomics-Based Machine Learning Technology Enables Better Differentiation Between Glioblastoma and Anaplastic Oligodendroglioma

Purpose: The aim of this study was to test whether radiomics-based machine learning can enable the better differentiation between glioblastoma (GBM) and anaplastic oligodendroglioma (AO).Methods: This retrospective study involved 126 patients histologically diagnosed as GBM (n = 76) or AO (n = 50) i...

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Bibliographic Details
Main Authors: Yimeng Fan, Chaoyue Chen, Fumin Zhao, Zerong Tian, Jian Wang, Xuelei Ma, Jianguo Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-11-01
Series:Frontiers in Oncology
Subjects:
machine learning
magnetic resonance imaging
glioblastoma
anaplastic oligodendroglioma
texture analysis
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2019.01164/full

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https://www.frontiersin.org/article/10.3389/fonc.2019.01164/full

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