Machine Learning Models in the Detection of MB2 Canal Orifice in CBCT Images

Machine Learning Models in the Detection of MB2 Canal Orifice in CBCT Images

Objectives: The objective of the present study was to determine the accuracy of machine learning (ML) models in the detection of mesiobuccal (MB2) canals in axial cone-beam computed tomography (CBCT) sections. Methods: A total of 2500 CBCT scans from the oral radiology department of University Denta...

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Bibliographic Details
Main Authors: Shishir Shetty, Meliz Yuvali, Ilker Ozsahin, Saad Al-Bayatti, Sangeetha Narasimhan, Mohammed Alsaegh, Hiba Al-Daghestani, Raghavendra Shetty, Renita Castelino, Leena R David, Dilber Uzun Ozsahin
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:International Dental Journal
Subjects:
Artificial intelligence
Root canal
Cone-beam computed tomography
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S002065392500067X
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