Automated Detection of Cervical Carotid Artery Calcifications in Cone Beam Computed Tomographic Images Using Deep Convolutional Neural Networks

Automated Detection of Cervical Carotid Artery Calcifications in Cone Beam Computed Tomographic Images Using Deep Convolutional Neural Networks

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 CBCT. A total of 56 CBCT studies (15,257 axial slices) were utilized to train, validate, and test the deep learning mode...

Full description

Bibliographic Details
Main Authors: Maryam Ajami, Pavani Tripathi, Haibin Ling, Mina Mahdian
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Diagnostics
Subjects:
carotid arteries
carotid stenosis
cone beam computed tomography
artificial intelligence
deep learning
Online Access:https://www.mdpi.com/2075-4418/12/10/2537

Internet

https://www.mdpi.com/2075-4418/12/10/2537

Similar Items