Cargando…
Predicting pediatric optic pathway glioma progression using advanced magnetic resonance image analysis and machine learning
BACKGROUND: Optic pathway gliomas (OPGs) are low-grade tumors of the white matter of the visual system with a highly variable clinical course. The aim of the study was to generate a magnetic resonance imaging (MRI)-based predictive model of OPG tumor progression using advanced image analysis and mac...
Autores principales: | Pisapia, Jared M, Akbari, Hamed, Rozycki, Martin, Thawani, Jayesh P, Storm, Phillip B, Avery, Robert A, Vossough, Arastoo, Fisher, Michael J, Heuer, Gregory G, Davatzikos, Christos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7455885/ https://www.ncbi.nlm.nih.gov/pubmed/32885166 http://dx.doi.org/10.1093/noajnl/vdaa090 |
Ejemplares similares
-
Unsupervised machine learning using K-means identifies radiomic subgroups of pediatric low-grade gliomas that correlate with key molecular markers
por: Haldar, Debanjan, et al.
Publicado: (2022) -
Management of Giant Cervical Teratoma with Intracranial Extension Diagnosed in Utero
por: Thawani, Jayesh P., et al.
Publicado: (2016) -
Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features
por: Bakas, Spyridon, et al.
Publicado: (2017) -
Radiomics and radiogenomics in pediatric neuro-oncology: A review
por: Madhogarhia, Rachel, et al.
Publicado: (2022) -
IMG-06. RADIOMIC-BASED RISK STRATIFICATION OF PEDIATRIC LOW-GRADE GLIOMA REVEALS DIFFERENTIALLY EXPRESSED MOLECULAR PROCESSES CONTRIBUTING TO VARIABLE PATIENT PROGNOSIS
por: Kazerooni, Anahita Fathi, et al.
Publicado: (2023)