13 citations · 18 across the 4 of their papers we have counts for
4 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…
A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs
Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir +1
We present an end-to-end deep learning segmentation method by combining a 3D UNet architecture with a graph neural network (GNN) model. In this approach, the convolutional layers a…
Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation
Shuai Chen, Gerda Bortsova, Antonio Garcia-Uceda Juarez +2
We propose a novel semi-supervised image segmentation method that simultaneously optimizes a supervised segmentation and an unsupervised reconstruction objectives. The reconstructi…
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…