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 …

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary
disease (COPD) and is associated with increased morbidity and mortality. Reference …

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 …

Segmenting portal vein (PV) and hepatic vein (HV) from magnetic resonance imaging (MRI)
scans is important for hepatic tumor surgery. Compared with single phase-based methods …

Lung vessel segmentation has been widely explored by the biomedical image processing
community; however, the differentiation of arterial from venous irrigation is still a challenge …

Objectives To evaluate interstitial lung disease associated with systemic sclerosis (SSc-ILD)
and its changes during treatment by using quantitative analysis (QA) compared to semi …

Objectives It has recently become possible to assess lung vascular and parenchymal
changes quantitatively in thoracic CT images using automated software tools. We …