A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

PURPOSE: Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neural networks (CNNs) are the state-of-the-art image segmentation technique, but require large annotated datasets for training. Annotation of 3D medical...

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Detalles Bibliográficos
Autores principales: Pérez-García, Fernando, Dorent, Reuben, Rizzi, Michele, Cardinale, Francesco, Frazzini, Valerio, Navarro, Vincent, Essert, Caroline, Ollivier, Irène, Vercauteren, Tom, Sparks, Rachel, Duncan, John S., Ourselin, Sébastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580910/
https://www.ncbi.nlm.nih.gov/pubmed/34120269
http://dx.doi.org/10.1007/s11548-021-02420-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580910/
https://www.ncbi.nlm.nih.gov/pubmed/34120269
http://dx.doi.org/10.1007/s11548-021-02420-2

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