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

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

BackgroundThe radiological differential diagnosis between tumor recurrence and radiation-induced necrosis (ie, pseudoprogression) is of paramount importance in the management of glioma patients. ObjectiveThis research aims to develop a deep learning methodology fo...

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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: JMIR Publications 2020-11-01
Series:JMIR Medical Informatics
Online Access:http://medinform.jmir.org/2020/11/e19805/

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http://medinform.jmir.org/2020/11/e19805/

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