Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning

Fully automated brain resection cavity delineation for radiation target volume definition in glioblastoma patients using deep learning

Abstract Background Automated brain tumor segmentation methods are computational algorithms that yield tumor delineation from, in this case, multimodal magnetic resonance imaging (MRI). We present an automated segmentation method and its results for resection cavity (RC) in glioblastoma multiforme (...

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Bibliographic Details
Main Authors: Ekin Ermiş, Alain Jungo, Robert Poel, Marcela Blatti-Moreno, Raphael Meier, Urspeter Knecht, Daniel M. Aebersold, Michael K. Fix, Peter Manser, Mauricio Reyes, Evelyn Herrmann
Format: Article
Language:English
Published: BMC 2020-05-01
Series:Radiation Oncology
Subjects:
Glioblastoma
Automatic segmentation
Deep learning
Target definition
MRI
Online Access:http://link.springer.com/article/10.1186/s13014-020-01553-z

Internet

http://link.springer.com/article/10.1186/s13014-020-01553-z

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