An overview of the applications of AI for detecting anatomical configurations in endodontics

• Published in: Annals of anatomy Vol. 260; p. 152671
• Main Authors: Fouad, Eman M., Abu-Seida, Ashraf, Alsheshtawi, Khaled A.
• Format: Journal Article
• Language: English
• Published: Germany Elsevier GmbH 01.06.2025
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Convolutional neural network; Deep learning; Dental Pulp Cavity - anatomy & histology; Dental Pulp Cavity - diagnostic imaging; Endodontics - methods; Humans; Pulp space anatomy; Pulp space segmentation; Tooth Root - anatomy & histology; Tooth Root - diagnostic imaging; Deep learning; Pulp space anatomy; Artificial intelligence; Convolutional neural network; Pulp space segmentation; Artificial neural networks
• ISSN: 0940-9602; 1618-0402; 1618-0402
• DOI: 10.1016/j.aanat.2025.152671

Artificial intelligence (AI), which uses algorithms to replicate human intellect, allows robots to learn from data and complete complex tasks on their own. Mini-narrative review. This mini-narrative review evaluates AI’s potential to improve the detection of anatomical features of root and canal systems, focusing on its benefits, challenges, and future applications. A comprehensive literature search was conducted using PubMed, Scopus, and Google Scholar to identify studies on AI applications in detecting anatomical features of root and root canal systems in endodontics. Inclusion criteria encompassed all relevant literature focused on anatomical feature detection, with no restrictions on time or language. Studies were excluded if they were unrelated to the topic or focused on pathological rather than anatomical feature detection. AI has significantly improved the detection of root and canal anatomy, including minor constrictions, working length, second mesio-buccal canals, and complex systems like C-shaped canals, with diagnostic accuracy comparable to or surpassing experienced practitioners. While challenges remain in technology, ethics, and regulation, AI enhances precision, efficiency, and patient outcomes. Addressing these hurdles will further advance its integration into endodontic practice and shape its future positively. [Display omitted]