Main coronary segmentation from the X-ray angiography images is important for the
computer-aided diagnosis and treatment of coronary disease. However, it confronts the …

Coronary artery segmentation is critical for coronary artery disease diagnosis but
challenging due to its tortuous course with numerous small branches and inter-subject …

Traffic flow prediction (TFP) has attracted increasing attention with the development of smart
city. In the past few years, neural network-based methods have shown impressive …

Coronary artery segmentation is a critical yet challenging step in coronary artery stenosis
diagnosis. Most existing studies ignore important contextual anatomical information and …

Although robust PCA has been increasingly adopted to extract vessels from X-ray coronary
angiography (XCA) images, challenging problems such as inefficient vessel-sparsity …

Blood vessel segmentation in medical imaging is one of the essential steps for vascular
disease diagnosis and interventional planning in a broad spectrum of clinical scenarios in …

Coronary Heart Disease (CHD) is a leading cause of death in the modern world. The
development of modern analytical tools for diagnostics and treatment of CHD is receiving …

With convolutional neural networks' remarkable performance in computer vision, more and
more studies are applying deep learning to vessel image segmentation tasks. This work …

The structural and functional analysis of coronary arteries in X-ray angiography (XRA)
images has great clinical importance for the intraoperative treatment of coronary artery …

Building an oil spill segmentation model is very challenging because of the limited available
information on oil spill accidents. Therefore, this paper proposes a custom data generator …