2024/07/08 by Ignacio Garrido Botella, Ignacio Arranz Águeda, Botella, Ignacio Garrido +10
Arts and Humanities · Dentistry · Medicine · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Dental Radiography and Imaging #FOS: Computer and information sciences #FOS: Electrical engineering #Forensic Anthropology and Bioarchaeology Studies #Image and Video Processing (eess.IV) #Medical Imaging Techniques and Applications #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2407.05892
openalex publication_date 2024/07/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Accurate identification, localization, and segregation of teeth from Cone Beam Computed Tomography (CBCT) images are essential for analyzing dental pathologies. Modeling an individual tooth can be challenging and intricate to accomplish, especially when fillings and other restorations introduce artifacts. This paper proposes a method for automatically detecting, identifying, and extracting teeth from CBCT images. Our approach involves dividing the three-dimensional images into axial slices for image detection. Teeth are pinpointed and labeled using a single-stage object detector. Subsequently, bounding boxes are delineated and identified to create three-dimensional representations of each tooth. The proposed solution has been successfully integrated into the dental analysis tool Dentomo.