Cargando…
Application of radiomics feature captured from MRI for prediction of recurrence for glioma patients
Purpose: This study aimed to develop and validate a recurrence prediction of glioma patients through a radiomics feature training and validation model. Patients and methods: In this study, the prediction model was developed in a training cohort that consisted of 88 patients from January 2014 to July...
Autores principales: | Liu, Canyu, Li, Yujiao, Xia, Xiang, Wang, Jiazhou, Hu, Chaosu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8824898/ https://www.ncbi.nlm.nih.gov/pubmed/35154462 http://dx.doi.org/10.7150/jca.65366 |
Ejemplares similares
-
MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
por: Ming, Xue, et al.
Publicado: (2019) -
Differentiation of Recurrence from Radiation Necrosis in Gliomas Based on the Radiomics of Combinational Features and Multimodality MRI Images
por: Zhang, Quan, et al.
Publicado: (2019) -
Application of Enhanced T1WI of MRI Radiomics in Glioma Grading
por: Zhou, Hongzhang, et al.
Publicado: (2022) -
Radiomics and Qualitative Features From Multiparametric MRI Predict Molecular Subtypes in Patients With Lower-Grade Glioma
por: Sun, Chen, et al.
Publicado: (2022) -
High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management
por: Li, Jing, et al.
Publicado: (2020)