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

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

Abstract 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...

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Autores principales: Antonio Garcia-Uceda, Raghavendra Selvan, Zaigham Saghir, Harm A. W. M. Tiddens, Marleen de Bruijne
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/04be7a8e66d846138c66cbc7a117dc5e
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