Towards Segmentation and Spatial Alignment of the Human Embryonic Brain Using Deep Learning for Atlas-Based Registration

We propose an unsupervised deep learning method for atlas-based registration to achieve segmentation and spatial alignment of the embryonic brain in a single framework. Our approach consists of two sequential networks with a specifically designed loss function to address the challenges in 3D first t...

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Detalles Bibliográficos
Autores principales: Bastiaansen, Wietske A. P., Rousian, Melek, Steegers-Theunissen, Régine P. M., Niessen, Wiro J., Koning, Anton, Klein, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279927/
http://dx.doi.org/10.1007/978-3-030-50120-4_4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279927/
http://dx.doi.org/10.1007/978-3-030-50120-4_4

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