Root canal preparation in endodontics poses significant challenges, particularly in curved canals of mandibular molars, where accurate preoperative assessment using CBCT imaging is crucial to avoid iatrogenic errors and improve treatment outcomes. This study aims to develop and evaluate the diagnostic accuracy of a deep learning model for analyzing root canal curvature angles in mandibular molars from CBCT scans, compared to human expert evaluations. The model will leverage advanced AI techniques to segment and measure curvatures objectively, addressing limitations in manual interpretation, potentially standardizing case difficulty assessments and aiding clinical decision-making.
Study Type
OBSERVATIONAL
Enrollment
207
Faculty of Dentistry, Cairo University
Cairo, Cairo Governorate, Egypt
Accuracy of analysis of root canal curvature angle
Curvature analysis classified according to its severity into 3 categories: "10 degrees or less"; as mild, "between 10 to 30 degrees"; as moderate and "30 degrees or more"; as severe curvature.
Time frame: June 2026 to September 2027
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