Automatic airway segmentation from computed tomography using robust and efficient 3-D convolutional neural networks

This paper presents a fully automatic and end-to-end optimised airway segmentation method for thoracic computed tomography, based on the U-Net architecture. We use a simple and low-memory 3D U-Net as backbone, which allows the method to process large 3D image patches, often comprising full lungs, in...

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Detalles Bibliográficos
Autores principales: Garcia-Uceda, Antonio, Selvan, Raghavendra, Saghir, Zaigham, Tiddens, Harm A. W. M., de Bruijne, Marleen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346579/
https://www.ncbi.nlm.nih.gov/pubmed/34362949
http://dx.doi.org/10.1038/s41598-021-95364-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8346579/
https://www.ncbi.nlm.nih.gov/pubmed/34362949
http://dx.doi.org/10.1038/s41598-021-95364-1

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