Deep learning for the fully automated segmentation of the inner ear on MRI

Deep learning for the fully automated segmentation of the inner ear on MRI

Abstract Segmentation of anatomical structures is valuable in a variety of tasks, including 3D visualization, surgical planning, and quantitative image analysis. Manual segmentation is time-consuming and deals with intra and inter-observer variability. To develop a deep-learning approach for the ful...

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Bibliographic Details
Main Authors: Akshayaa Vaidyanathan, Marly F. J. A. van der Lubbe, Ralph T. H. Leijenaar, Marc van Hoof, Fadila Zerka, Benjamin Miraglio, Sergey Primakov, Alida A. Postma, Tjasse D. Bruintjes, Monique A. L. Bilderbeek, Hammer Sebastiaan, Patrick F. M. Dammeijer, Vincent van Rompaey, Henry C. Woodruff, Wim Vos, Seán Walsh, Raymond van de Berg, Philippe Lambin
Format: Article
Language:English
Published: Nature Portfolio 2021-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-82289-y

Internet

https://doi.org/10.1038/s41598-021-82289-y

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