Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation

BACKGROUND: The radiological differential diagnosis between tumor recurrence and radiation-induced necrosis (ie, pseudoprogression) is of paramount importance in the management of glioma patients. OBJECTIVE: This research aims to develop a deep learning methodology for automated differentiation of t...

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Detalles Bibliográficos
Autores principales: Gao, Yang, Xiao, Xiong, Han, Bangcheng, Li, Guilin, Ning, Xiaolin, Wang, Defeng, Cai, Weidong, Kikinis, Ron, Berkovsky, Shlomo, Di Ieva, Antonio, Zhang, Liwei, Ji, Nan, Liu, Sidong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708085/
https://www.ncbi.nlm.nih.gov/pubmed/33200991
http://dx.doi.org/10.2196/19805

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708085/
https://www.ncbi.nlm.nih.gov/pubmed/33200991
http://dx.doi.org/10.2196/19805

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