The computational detection of pulmonary lobes from CT images is a challenging
segmentation problem with important respiratory health care applications, including surgical …

We aim at improving quantitative measures of emphysema in computed tomography (CT)
images of the lungs. Current standard measures, such as the relative area of emphysema …

As one of the most prevalent chronic disorders, airway disease is a major cause of morbidity
and mortality worldwide. In order to understand its underlying mechanisms and to enable …

This paper describes a framework for establishing a reference airway tree segmentation,
which was used to quantitatively evaluate 15 different airway tree extraction algorithms in a …

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 …

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 …

Graph refinement, or the task of obtaining subgraphs of interest from over-complete graphs,
can have many varied applications. In this work, we extract trees or collection of sub-trees …

This paper introduces a graph construction method for multi-dimensional and multi-surface
segmentation problems. Such problems can be solved by searching for the optimal …

We present extraction of tree structures, such as airways, from image data as a graph
refinement task. To this end, we propose a graph auto-encoder model that uses an encoder …

We present a fast and robust atlas-based algorithm for labeling airway trees, using geodesic
distances in a geometric tree-space. Possible branch label configurations for an unlabeled …