CT body composition analysis has been shown to play an important role in predicting health
and has the potential to improve patient outcomes if implemented clinically. Recent …

The global mortality rate is known to be the highest due to cardiovascular disease (CVD).
Thus, preventive, and early CVD risk identification in a non-invasive manner is vital as …

Purpose To develop an automated deep learning model for MRI‐based segmentation and
detection of intracranial arterial calcification. Methods A novel deep learning model under …

Methods A search was conducted in PubMed and Web of Science. The key words included
“artificial intelligence”,“machine learning”,“deep learning”, and “vascular calcification”. The …

The aim of this study was to determine if a convolutional neural network (CNN) can be
trained to automatically detect and localize cervical carotid artery calcifications (CACs) in …

Background Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients
with stroke of undetermined etiology. Its detection is challenging, especially among non …

Quantification of the histological staining images gives important insights in biomedical
research. In wet lab, it is common to have some stains off the target to become unwanted …

Objective We leveraged an artificial intelligence deep-learning convolutional neural network
(DL CNN) to detect calcified carotid artery atheromas (CCAAs) on cone beam computed …

Background and purpose: Anatomical labeling of the cerebral vasculature is a crucial topic
in determining the morphological nature and characterizing the vital variations of vessels …

Cardiovascular neurocristopathy is associated with abnormal migration and development of
neural crest cells, impacting the neural and the human cardiovascular system and leading to …