18 citations · 18 across the 1 of their papers we have counts for
5 papers
Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks
A. Garcia-Uceda, R. Selvan, Z. Saghir +2
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…
Crowdsourcing Airway Annotations in Chest Computed Tomography Images
Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo +2
Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine lea…
Automatic Airway Segmentation in chest CT using Convolutional Neural Networks
A. Garcia-Uceda Juarez, H. A. W. M. Tiddens, M. de Bruijne
Segmentation of the airway tree from chest computed tomography (CT) images is critical for quantitative assessment of airway diseases including bronchiectasis and chronic obstructi…
Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks
Filipe Marques, Florian Dubost, Mariette Kemner-van de Corput +2
Cystic fibrosis is a genetic disease which may appear in early life with structural abnormalities in lung tissues. We propose to detect these abnormalities using a texture classifi…
Early Experiences with Crowdsourcing Airway Annotations in Chest CT
Veronika Cheplygina, Adria Perez-Rovira, Wieying Kuo +2
Measuring airways in chest computed tomography (CT) images is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine le…