Over the last decade, deep learning (DL) has contributed to a paradigm shift in computer
vision and image recognition creating widespread opportunities of using artificial …

The results of the randomised controlled trials investigating the bronchoscopic lung volume
reduction treatment using endobronchial valves (EBV) are promising, and have led to their …

Recent studies show that pulmonary vascular diseases may specifically affect arteries or
veins through different physiologic mechanisms. To detect changes in the two vascular …

Training convolutional neural networks (CNNs) for segmentation of pulmonary airway,
artery, and vein is challenging due to sparse supervisory signals caused by the severe class …

We present a novel integrative computerized solution to automatically identify and
differentiate pulmonary arteries and veins depicted on chest computed tomography (CT) …

We present a novel computer algorithm to automatically detect and segment pulmonary
embolisms (PEs) on computed tomography pulmonary angiography (CTPA). This algorithm …

Abstract Graph Convolutional Networks (GCNs) are a novel and powerful method for
dealing with non-Euclidean data, while Convolutional Neural Networks (CNNs) can learn …

Multiple thoracic imaging modalities have been developed to link structure to function in the
diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders …

Background The in vivo relationship between peel pulmonary vessels, small pulmonary
vessels, and pulmonary hypertension (PH) is not fully understood. Purpose To quantitatively …

We propose MisMatch, a novel consistency-driven semi-supervised segmentation
framework which produces predictions that are invariant to learnt feature perturbations …