Cargando…
Publisher Correction: A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics
Autores principales: | Yan, Jiun-Lin, Li, Chao, van der Hoorn, Anouk, Boonzaier, Natalie R., Matys, Tomasz, Price, Stephen J. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419500/ https://www.ncbi.nlm.nih.gov/pubmed/32782416 http://dx.doi.org/10.1038/s41598-020-70346-x |
Ejemplares similares
-
A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics
por: Yan, Jiun-Lin, et al.
Publicado: (2020) -
Multimodal MRI characteristics of the glioblastoma infiltration beyond contrast enhancement
por: Yan, Jiun-Lin, et al.
Publicado: (2019) -
Multi-parametric and multi-regional histogram analysis of MRI: modality integration reveals imaging phenotypes of glioblastoma
por: Li, Chao, et al.
Publicado: (2019) -
MRI radiomic features of peritumoral edema may predict the recurrence sites of glioblastoma multiforme
por: Long, Hao, et al.
Publicado: (2023) -
Low perfusion compartments in glioblastoma quantified by advanced magnetic resonance imaging and correlated with patient survival
por: Li, Chao, et al.
Publicado: (2019)