Fast meningioma segmentation in T1-weighted magnetic resonance imaging volumes using a lightweight 3D deep learning architecture

Automatic and consistent meningioma segmentation in T1-weighted magnetic resonance (MR) imaging volumes and corresponding volumetric assessment is of use for diagnosis, treatment planning, and tumor growth evaluation. We optimized the segmentation and processing speed performances using a large numb...

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Bibliographic Details

Published in:	Journal of medical imaging (Bellingham, Wash.) Vol. 8; no. 2; p. 024002
Main Authors:	Bouget, David, Pedersen, André, Hosainey, Sayied Abdol Mohieb, Vanel, Johanna, Solheim, Ole, Reinertsen, Ingerid
Format:	Journal Article
Language:	English
Published:	United States 01.03.2021
Subjects:	clinical diagnosis meningioma deep learning magnetic resonance imaging three-dimensional segmentation
ISSN:	2329-4302
Online Access:	Get more information
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