Automatic coronary artery segmentation is of great value in diagnosing coronary disease. In
this paper, we propose an automatic coronary artery segmentation method for coronary …

Abstract Purpose of Review Recently, machine learning (ML) has developed rapidly in the
field of medicine, playing an important role in disease diagnosis and treatment. Our aim of …

Automatic coronary artery (CA) segmentation on coronary-computed tomography
angiography (CCTA) images is critical for coronary-related disease diagnosis and pre …

Computer visual systems can rapidly obtain a large amount of data and automatically
process them with ease. These characteristics constitute advantages for the application of …

Cardiovascular disease is a severe threat to human health. The assessment of the degree of
cardiovascular stenosis is very important for the diagnosis of cardiovascular disease. The …

Purpose Computed tomography coronary angiography (CCTA) images provide optimal
visualization of coronary arteries to aid in diagnosing coronary heart disease (CHD). With …

Cerebral vessel segmentation is an important step in image analysis for brain function and
brain disease studies. To extract all the cerebrovascular patterns, including arteries and …

Precise and efficient diagnosis of coronary artery disease (CAD) greatly depend on the
automated segmentation of coronary arteries. However, due to the presence of noise in …

Every day is greater the number of images obtained to characterize the anatomy and
functions of the human body, because of this the automation of the medical image …

The processing and analysis of 3D Rotational Angiographic images (3DRA) of high spatial
resolution to facilitate intervention planning in interventional neuroradiology is a new and …