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AI in Dentistry: Diagnosing TMD with MRIs
Manage episode 444599857 series 3605861
Το περιεχόμενο παρέχεται από το Brian Carter. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Brian Carter ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.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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