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@article{174133,
        author = {Trushank Ravindra Baria and Jenil Rashesh Naik and Venugopalan P.V. and Piyush Suthar and Prof. Dimpal Khambhati},
        title = {OdontalCam: A Smart Intraoral Imaging System for Automated Cavity Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2798-2802},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174133},
        abstract = {Traditional intraoral cameras in dentistry primarily serve as observational tools, heavily relying on the clinician's expertise for accurate diagnosis. This dependence can lead to diagnostic inconsistencies, as visual assessments are inherently subjective. Moreover, the operation of these devices often necessitates additional personnel to capture images, thereby increasing operational complexity and resource utilization. In response to these challenges, we have developed OdontalCam, an innovative intraoral camera system enhanced with machine learning capabilities for automated dental cavity detection. OdontalCam is designed to streamline the diagnostic process by autonomously identifying and capturing images of carious lesions, thus minimizing the need for manual intervention and reducing the potential for human error. The system employs a sophisticated machine learning algorithm trained on a diverse dataset of dental images, enabling it to detect cavities with a confidence level exceeding 60%. Detections below this threshold are disregarded to maintain diagnostic accuracy, effectively implementing a true-false evaluation method. This approach ensures that only high-confidence detections are considered, thereby reducing the incidence of false positives. Extensive testing and validation have demonstrated that OdontalCam achieves a cavity detection accuracy of approximately 80%. This significant improvement over traditional methods underscores the potential of integrating advanced technologies into routine dental practice. By enhancing diagnostic precision and operational efficiency, OdontalCam represents a substantial advancement in dental healthcare, promising improved patient outcomes and optimized clinical workflows.},
        keywords = {Automated Imaging, Cavity Detection, Dental Diagnostics, Intraoral Camera, Machine Learning, OdontalCam.},
        month = {March},
        }