Glioblastoma Surgery Imaging–Reporting and Data System: Validation and Performance of the Automated Segmentation Task

Glioblastoma Surgery Imaging–Reporting and Data System: Validation and Performance of the Automated Segmentation Task

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeo...

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Bibliographic Details
Main Authors: David Bouget, Roelant S. Eijgelaar, André Pedersen, Ivar Kommers, Hilko Ardon, Frederik Barkhof, Lorenzo Bello, Mitchel S. Berger, Marco Conti Nibali, Julia Furtner, Even Hovig Fyllingen, Shawn Hervey-Jumper, Albert J. S. Idema, Barbara Kiesel, Alfred Kloet, Emmanuel Mandonnet, Domenique M. J. Müller, Pierre A. Robe, Marco Rossi, Lisa M. Sagberg, Tommaso Sciortino, Wimar A. Van den Brink, Michiel Wagemakers, Georg Widhalm, Marnix G. Witte, Aeilko H. Zwinderman, Ingerid Reinertsen, Philip C. De Witt Hamer, Ole Solheim
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Cancers
Subjects:
glioblastoma
deep learning
3D segmentation
computer-assisted image processing
magnetic resonance imaging
neuroimaging
Online Access:https://www.mdpi.com/2072-6694/13/18/4674

Internet

https://www.mdpi.com/2072-6694/13/18/4674

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