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...

Descripción completa

Detalles Bibliográficos
Autores principales: Ajami, Maryam, Tripathi, Pavani, Ling, Haibin, Mahdian, Mina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600983/
https://www.ncbi.nlm.nih.gov/pubmed/36292226
http://dx.doi.org/10.3390/diagnostics12102537

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600983/
https://www.ncbi.nlm.nih.gov/pubmed/36292226
http://dx.doi.org/10.3390/diagnostics12102537

Ejemplares similares