Optimization of deep learning methods for visualization of tumor heterogeneity and brain tumor grading through digital pathology

BACKGROUND: Variations in prognosis and treatment options for gliomas are dependent on tumor grading. When tissue is available for analysis, grade is established based on histological criteria. However, histopathological diagnosis is not always reliable or straight-forward due to tumor heterogeneity...

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Detalles Bibliográficos
Autores principales: Truong, An Hoai, Sharmanska, Viktoriia, Limbӓck-Stanic, Clara, Grech-Sollars, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Basic and Translational Investigations
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648592/
https://www.ncbi.nlm.nih.gov/pubmed/33196039
http://dx.doi.org/10.1093/noajnl/vdaa110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648592/
https://www.ncbi.nlm.nih.gov/pubmed/33196039
http://dx.doi.org/10.1093/noajnl/vdaa110

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