Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist's reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images.

Background: The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1 CE) and fluid attenuated inv...

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Bibliographic Details

Published in:	BMC Neurology Vol. 20; no. 1; pp. 1 - 11
Main Authors:	Zhao, Sha-Sha, Feng, Xiu-Long, Hu, Yu-Chuan, Han, Yu, Tian, Qiang, Sun, Ying-Zhi, Zhang, Jie, Ge, Xiang-Wei, Cheng, Si-Chao, Li, Xiu-Li, Mao, Li, Shen, Shu-Ning, Yan, Lin-Feng, Cui, Guang-Bin, Wang, Wen
Format:	Journal Article
Published:	BioMed Central 2/7/2020
Online Access:	View this record in EBSCOhost