Merging and Annotating Teeth and Roots from Automated Segmentation of Multimodal Images

• Published in: Multimodal Learning for Clinical Decision Support Vol. 13050; pp. 81 - 92
• Main Authors: Deleat-Besson, Romain, Le, Celia, Zhang, Winston, Turkestani, Najla Al, Cevidanes, Lucia, Bianchi, Jonas, Ruellas, Antonio, Gurgel, Marcela, Massaro, Camila, Del Castillo, Aron Aliaga, Ioshida, Marcos, Yatabe, Marilia, Benavides, Erika, Rios, Hector, Soki, Fabiana, Neiva, Gisele, Najarian, Kayvan, Gryak, Jonathan, Styner, Martin, Aristizabal, Juan Fernando, Rey, Diego, Alvarez, Maria Antonia, Bert, Loris, Soroushmehr, Reza, Prieto, Juan
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2021; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Deep learning; Dental crown segmentation; Dentistry; Merging; Root canal segmentation; Universal label

This paper aims to combine two different imaging techniques to create an accurate 3D model representation of root canals and dental crowns. We combine Cone-Beam Computed Tomography (CBCT) (root canals) and Intra Oral Scans (IOS) (dental crowns). The Root Canal Segmentation algorithm relies on a U-Ne...