Quantitative analysis of thin-section CT of the chest has a growing role in the clinical
evaluation and management of diffuse lung diseases. This heterogeneous group includes …

Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient
information directly from images that are decoded into handcrafted features, comprising …

Abstract The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively
compares the performance of different algorithms to identify vessels in thoracic computed …

Accurate coronary artery segmentation is a fundamental step in various medical imaging
applications such as stenosis detection, 3D reconstruction and cardiac dynamics assessing …

Pulmonary vessel segmentation is the key application of AI in lung disease diagnosis and
surgical planning. Compared with manual labeling, automatic labeling of pulmonary vessels …

Lung cancer is a life-threatening disease with the highest morbidity and mortality rates of
any cancer worldwide. Clinical staging of lung cancer can significantly reduce the mortality …

Background and objective: The vessel segmentation in CT angiography (CTA) provides an
important basis for automatic diagnosis and hemodynamics analysis. Virtual unenhanced …

Lung vessel segmentation of computed tomography (CT) images is important in clinical
practise and challenging due to difficulties associated with minor size and blurred edges of …

Pulmonary vascular extraction from chest CT images plays an important role in the
diagnosis of lung disease. To improve the accuracy rate of pulmonary vascular …

Segmentation of pulmonary vessels in CT/CTA images can help physicians better determine
the patient's condition and treatment. However, due to the complexity of CT images, existing …