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AI in Dentistry: Diagnosing TMD with MRIs
Manage episode 444599857 series 3605861
Sisällön tarjoaa Brian Carter. Brian Carter tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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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