DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes

We present DeepVesselNet, an architecture tailored to the challenges faced when extracting vessel trees and networks and corresponding features in 3-D angiographic volumes using deep learning. We discuss the problems of low execution speed and high memory requirements associated with full 3-D networ...

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Detalles Bibliográficos
Autores principales: Tetteh, Giles, Efremov, Velizar, Forkert, Nils D., Schneider, Matthias, Kirschke, Jan, Weber, Bruno, Zimmer, Claus, Piraud, Marie, Menze, Björn H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7753013/
https://www.ncbi.nlm.nih.gov/pubmed/33363452
http://dx.doi.org/10.3389/fnins.2020.592352

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7753013/
https://www.ncbi.nlm.nih.gov/pubmed/33363452
http://dx.doi.org/10.3389/fnins.2020.592352

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