Year: 2025 | Month: November | Volume: 12 | Issue: 11 | Pages: 163-176
DOI: https://doi.org/10.52403/ijrr.20251118
A Comprehensive Review on Artificial Intelligence Assisted CBCT Analysis for 3D Alveolar Bone Morphometry and Periodontal Diagnosis
Priyadharshini K, Dr Rajapandian K, Dr Ravishankar PL, Dr PS Viola Esther, Dr Gayathri K
Department of Periodontics, SRM Kattankulathur Dental College and Hospital, Faculty of Medicine and Health Sciences, SRM Institute of Science and Technology (SRMIST) Kattankulathur, Chengalpattu-603203, Tamil Nadu, India.
Corresponding Author: Dr Rajapandian K
ABSTRACT
Periodontal disease is a chronic inflammation that damages the tooth-supporting structures, i.e., gingiva, cementum, periodontal ligament, and alveolar bone. It is the leading cause of tooth loss across the globe. Evaluation of alveolar bone structure is important in order to estimate the severity and stage classification of periodontal disease, thereby influencing treatment planning and prognosis. Traditional two-dimensional (2D) radiographs, in spite of their widespread use, are limited by structural superimposition and the inability to clearly represent complex three-dimensional (3D) bone disease. Cone-beam computed tomography (CBCT) is better than standard CT in imaging for producing more accurate three-dimensional images of alveolar bone with minimal doses of radiation. Diagnosis based upon CBCT imaging is very helpful in carrying out appropriate treatment of the disease. Advancements in artificial intelligence (AI) and deep learning (DL) technologies, along with the convolutional neural networks (CNNs) and U-Net design have empowered dental imaging to automatically identify, classify, and segment periodontal bone defects with more efficiency. Studies have established that AI-enhanced CBCT evaluation significantly improves diagnostic efficacy and speed and, in some cases, surpasses conventional interpretation. Future projects will focus on developing AI models for local defect detection, multimodal data fusion, and establishing explainable AI to enable individualized periodontal treatment. AI-CBCT is seen in the future to enhance periodontal diagnosis and assist with recovery for patients.
Keywords: Periodontal disease; Cone beam computed tomography (CBCT); Alveolar bone morphometry; Artificial intelligence (AI); Deep learning (DL); Convolutional neural networks (CNNs); Periodontal diagnosis.
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