Characteristics Of Coronary Arteries Research Articles

Deep Recursive Bayesian Tracking for Fully Automatic Centerline Extraction of Coronary Arteries in CT Images.

Extraction of coronary arteries in coronary computed tomography (CT) angiography is a prerequisite for the quantification of coronary lesions. In this study, we propose a tracking method combining a deep convolutional neural network (DNN) and particle filtering method to identify the trajectories from the coronary ostium to each distal end from 3D CT images. The particle filter, as a non-linear approximator, is an appropriate tracking framework for such thin and elongated structures; however, the robust ‘vesselness’ measurement is essential for extracting coronary centerlines. Importantly, we employed the DNN to robustly measure the vesselness using patch images, and we integrated softmax values to the likelihood function in our particle filtering framework. Tangent patches represent cross-sections of coronary arteries of circular shapes. Thus, 2D tangent patches are assumed to include enough features of coronary arteries, and the use of 2D patches significantly reduces computational complexity. Because coronary vasculature has multiple bifurcations, we also modeled a method to detect branching sites by clustering the particle locations. The proposed method is compared with three commercial workstations and two conventional methods from the academic literature.

Progress in Kawasaki disease with coronary artery lesions

Kawasaki disease,which is an acute multisystem vasculitis of unknown cause,leads to pathognomonic feature of coronary artery lesion.Recent studies show that genetic polymorphism,neutrophils,monocytes,cytokines and other factors are involved in the development of coronary artery disease.Long-term use of anticoagulant drugs may reduce coronary artery damage. Key words: Mucocutaneous lymphnode syndrome; Coronary artery lesion