Digital Workflows in Orthodontics: Uses of Active Light Projection and Artificial Intelligence for Orthodontic Applications
Jason B. Cope
EDUCATION
- Texas A&M Univ. System - Baylor College of Dentistry
Dallas, Texas
PhD (Craniofacial Biology) - November 1999
Dallas, Texas
Certificate (Orthodontics) - August 1997
- Baylor College of Dentistry
Dallas, Texas
DDS - June 1995
- Southern Methodist Univ
Dallas, Texas
BA (Biology) - December 1990
- Airline High School
Bossier City, Louisiana
May 1987
ACADEMIC APPOINTMENTS
- Adjunct Associate Professor, Dept. of Orthodontics, Kung Hee University School of Dentistry, Seoul, Korea - 2015 to present.
- Adjunct Associate Professor, Dept. of Graduate Orthodontics, St. Louis University, St. Louis, Missouri - 2008 to present.
- Adjunct Assistant Professor, Dept. of Orthodontics, Texas A&M College of Dentistry, Dallas, Texas - September 2016 to August 2019.
- Clinical Assistant Professor, Dept. of Orthodontics, TAMHSC - Baylor College of Dentistry, Dallas, Texas - January to August 2016.
- Adjunct Assistant Professor, Dept. of Orthodontics, TAMSHSC - Baylor College of Dentistry, Dallas, Texas - July to December 2015.
- Adjunct Clinical Assistant Professor, Dept. of Orthodontics, TAMUSHSC - Baylor College of Dentistry, Dallas, Texas - 1997 to 2009.
- Adjunct Assistant Professor, Dept. of Oral & Maxillofacial Surgery and Pharmacology, TAMUSHSC - Baylor College of Dentistry, Dallas, Texas - 2005 to 2009.
Lecture Description
Traditional orthodontic mechanotherapy incorporates midtreatment records to assess tooth root positions and to make midcourse corrections. This is required with brackets and aligners and is primarily caused by the inaccuracy of ˇ°mentallyˇ± visualizing the radiographic root position to the appliance placed on the crowns in situ. Although the progression from 2D to 3D radiographic data has improved visualization of root positions, it still has not eliminated the necessity of mentally translating the unseen root position to the in situ appliance, often requiring midcourse corrections.
The incorporation of active light projection and artificial intelligence brings us a step closer to the goal of accurately prescribing tooth movement based on the exact known pretreatment tooth positions and the final predicted tooth positions. This presentation will demonstrate the use of the RayFace scanner and software that provides automated alignment of 3D face scans to intraoral scans and CBCT data with subsequent segmentation of the aligned data for use in tooth movement software with clinical examples.
