The choice of features greatly influences the performance of a tissue classification system.
Despite this, many systems are built with standard, predefined filter banks that are not …

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 …

Precise segmentation of the lung airways is essential for a quantitative assessment of airway
diseases. However, because of the complexity of the airway structure and the different …

Objectives To develop and evaluate a fully automatic method to measure diameters of the
ascending and descending aorta on non-ECG-gated, non-contrast computed tomography …

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 …

Segmentation of the airway tree from chest computed tomography (CT) images is critical for
quantitative assessment of airway diseases including bronchiectasis and chronic obstructive …

Background: Newly developed quantitative chest computed tomography (CT) outcomes
designed specifically to assess structural abnormalities related to cystic fibrosis (CF) lung …

Background CT-derived bronchial parameters have been linked to chronic obstructive
pulmonary disease and asthma severity, but little is known about these parameters in …

Purpose Bronchiectasis and airway wall thickening are commonly assessed in computed
tomography (CT) by comparing the airway size with the size of the accompanying artery …

Purpose To estimate airway tapering in control subjects and to assess the usability of
tapering as a bronchiectasis biomarker in paediatric populations. Methods Airway tapering …