创建并测试一种用于检测正畸患者牙齿问题的新型计算机视觉系统。
Creating and Testing a New Computer Vision System for Detecting Dental Problems in Orthodontic Patients.
作者信息
Chattopadhyay Jnananjan, Deb Anamika, Sharma Kanchan, Nawaid Khwaja Ahmad, Gandhi Rachana, Joshi Poonam, Makkad Ramanpal Singh
机构信息
Department of Dentistry, Murshidabad Medical College, Berhampore, Murshidabad, West Bengal, India.
Department of Oral and Maxillofacial Pathology and Microbiology and Forensic Odontology, Bhabha College of Dental Sciences, Bhopal, Madhya Pradesh, India.
出版信息
J Pharm Bioallied Sci. 2024 Feb;16(Suppl 1):S466-S468. doi: 10.4103/jpbs.jpbs_752_23. Epub 2023 Nov 7.
AIM
The research project focuses on the creation and assessment of an innovative computer vision system designed to identify dental irregularities in individuals undergoing orthodontic treatment.
MATERIALS AND METHODS
To establish the computer vision system, a comprehensive dataset of dental images was collected, encompassing various orthodontic cases. The system's algorithm was trained to recognize patterns indicative of common dental anomalies, such as malocclusions, spacing issues, and misalignments. Rigorous testing and refinement of the algorithm were conducted to enhance its accuracy and reliability.
RESULTS
The validation of the system was carried out using the dental records and images of the 40 patients. The computer vision system's performance was evaluated against assessments made by experienced orthodontists. The results demonstrated a commendable level of concurrence between the system's automated detections and the orthodontists' evaluations, suggesting its potential as a valuable diagnostic tool.
CONCLUSION
In conclusion, the development and validation of this novel computer vision system exhibit promising outcomes in its ability to automatically detect dental anomalies in orthodontic patients.
目的
该研究项目专注于创建和评估一个创新的计算机视觉系统，旨在识别接受正畸治疗的个体的牙齿不规则情况。
材料与方法
为建立计算机视觉系统，收集了包含各种正畸病例的全面牙齿图像数据集。对该系统的算法进行训练，以识别指示常见牙齿异常的模式，如错牙合、间隙问题和牙齿排列不齐。对算法进行了严格测试和优化，以提高其准确性和可靠性。
结果
使用40名患者的牙科记录和图像对该系统进行了验证。根据经验丰富的正畸医生的评估对计算机视觉系统的性能进行了评估。结果表明，该系统的自动检测结果与正畸医生的评估之间具有值得称赞的一致性水平，表明其作为一种有价值的诊断工具的潜力。
结论
总之，这种新型计算机视觉系统的开发和验证在自动检测正畸患者牙齿异常方面展现出了有前景的成果。
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