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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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007642/
https://www.ncbi.nlm.nih.gov/pubmed/32033580
http://dx.doi.org/10.1186/s12883-020-1613-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007642/
https://www.ncbi.nlm.nih.gov/pubmed/32033580
http://dx.doi.org/10.1186/s12883-020-1613-y

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