3D Segmentation of Perivascular Spaces on T1-Weighted 3 Tesla MR Images With a Convolutional Autoencoder and a U-Shaped Neural Network

We implemented a deep learning (DL) algorithm for the 3-dimensional segmentation of perivascular spaces (PVSs) in deep white matter (DWM) and basal ganglia (BG). This algorithm is based on an autoencoder and a U-shaped network (U-net), and was trained and tested using T1-weighted magnetic resonance...

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Detalles Bibliográficos
Autores principales: Boutinaud, Philippe, Tsuchida, Ami, Laurent, Alexandre, Adonias, Filipa, Hanifehlou, Zahra, Nozais, Victor, Verrecchia, Violaine, Lampe, Leonie, Zhang, Junyi, Zhu, Yi-Cheng, Tzourio, Christophe, Mazoyer, Bernard, Joliot, Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273917/
https://www.ncbi.nlm.nih.gov/pubmed/34262443
http://dx.doi.org/10.3389/fninf.2021.641600

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273917/
https://www.ncbi.nlm.nih.gov/pubmed/34262443
http://dx.doi.org/10.3389/fninf.2021.641600

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