Dumont Maxime, Prieto Juan Carlos, Brosset Serge, Cevidanes Lucia, Bianchi Jonas, Ruellas Antonio, Gurgel Marcela, Massaro Camila, Castillo Aron Aliaga Del, Ioshida Marcos, Yatabe Marilia, Benavides Erika, Rios Hector, Soki Fabiana, Neiva Gisele, Aristizabal Juan Fernando, Rey Diego, Alvarez Maria Antonia, Najarian Kayvan, Gryak Jonathan, Styner Martin, Fillion-Robin Jean-Christophe, Paniagua Beatriz, Soroushmehr Reza
University of Michigan, 1011 North University Ave., Ann Arbor, MI 48109, USA.
University of North Carolina, Chapel Hill, NC, USA.
Shape Med Imaging (2020). 2020 Oct;12474:145-153. doi: 10.1007/978-3-030-61056-2_12. Epub 2020 Oct 3.
This paper proposes machine learning approaches to support dentistry researchers in the context of integrating imaging modalities to analyze the morphology of tooth crowns and roots. One of the challenges to jointly analyze crowns and roots with precision is that two different image modalities are needed. Precision in dentistry is mainly driven by dental crown surfaces characteristics, but information on tooth root shape and position is of great value for successful root canal preparation, pulp regeneration, planning of orthodontic movement, restorative and implant dentistry. An innovative approach is to use image processing and machine learning to combine crown surfaces, obtained by intraoral scanners, with three dimensional volumetric images of the jaws and teeth root canals, obtained by cone beam computed tomography. In this paper, we propose a patient specific classification of dental root canal and crown shape analysis workflow that is widely applicable.
本文提出了机器学习方法，以支持牙科研究人员在整合成像模态以分析牙冠和牙根形态的背景下开展工作。精确联合分析牙冠和牙根面临的挑战之一是需要两种不同的图像模态。牙科中的精确性主要由牙冠表面特征驱动，但牙根形状和位置信息对于成功进行根管预备、牙髓再生、正畸移动规划、修复和种植牙科具有重要价值。一种创新方法是利用图像处理和机器学习，将口腔内扫描仪获取的牙冠表面与锥形束计算机断层扫描获取的颌骨和牙根三维容积图像相结合。在本文中，我们提出了一种广泛适用的针对患者的根管分类和牙冠形状分析工作流程。
