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AI in Dentistry: Diagnosing TMD with MRIs
سلسلة مؤرشفة ("تلقيمة معطلة" status)
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المحتوى المقدم من Brian Carter. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Brian Carter أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
This research paper proposes an AI-driven diagnostic system for Temporomandibular Joint Disorders (TMD) using MRI images. The system employs a segmentation method to identify key anatomical structures like the temporal bone, temporomandibular joint (TMJ) disc, and condyle. Using these identified structures, the system utilizes a decision tree based on their geometrical relationship to classify a patient as having TMD or not. The paper details the system’s development, including data acquisition, preprocessing, model training, and inferencing. The system is evaluated through a k-fold cross-validation, and its performance is assessed based on various metrics like sensitivity, specificity, accuracy, and F1-score. The results suggest that the AI-driven TMD diagnostic system demonstrates significant potential in assisting radiologists with TMJ diagnosis, although further improvements and validation using larger and more diverse datasets are required to enhance its performance and generalizability.
Read more: https://arxiv.org/pdf/2402.03397
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