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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Detalhes bibliográficos
Publicado no: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
Formato: Artigo
Idioma:Inglês
Publicado em: 2021
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Article
Acesso em linha: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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