An artificial intelligence framework for automatic segmentation and volumetry of vestibular schwannomas from contrast-enhanced T1-weighted and high-resolution T2-Weighted MRI

OBJECTIVE: Automatic segmentation of vestibular schwannomas (VS) from magnetic resonance imaging (MRI) could significantly improve clinical workflow and assist patient management. Accurate tumour segmentation and volumetric measurements provide the best indicator to detect subtle VS growth but curre...

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Bibliographic Details
Published in:J Neurosurg
Main Authors: Shapey, Jonathan, Wang, Guotai, Dorent, Reuben, Dimitriadis, Alexis, Li, Wenqi, Paddick, Ian, Kitchen, Neil, Bisdas, Sotirios, Saeed, Shakeel R, Ourselin, Sebastien, Bradford, Robert, Vercauteren, Tom
Format: Artigo
Language:Inglês
Published: 2021
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Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC7617042/
https://ncbi.nlm.nih.gov/pubmed/31812137
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3171/2019.9.JNS191949
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