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Developing a three-dimensional statistical shape model of normal dentition using an automated algorithm and normal
Hwee-Ho Kim1, Sieun Choi2, Young-Il Chang1
1Department of Orthodontics, School of Dentistry, Seoul National University, 101 Daehakro, Jongro-Gu, Seoul, 03080, Republic of Korea.
Clinical Oral Investigations
|December 9, 2022
Summary
A new 3D statistical shape model (SSM) of normal dentition was developed. This 3D SSM provides objective visual data for efficient orthodontic treatment planning and serves as a versatile dental template.
Area of Science:
- Biomedical Engineering
- Dental Morphology
- Statistical Shape Analysis
Background:
- Statistical Shape Models (SSMs) analyze geometric properties of shapes using automated algorithms.
- Developing an objective, average model of normal dentition is crucial for dental applications.
Purpose of the Study:
- To create a three-dimensional (3D) statistical shape model (SSM) of normal human dentition.
- To establish virtual templates for enhancing the efficiency of orthodontic treatments.
Main Methods:
- Acquired 3D models from dental casts of individuals with normal dentition.
- Generated individual tooth and dental arch SSMs using iterative closest point (ICP) registration.
- Aligned individual tooth SSMs to the dental arch SSM to create an average normal dentition model.
Main Results:
- The developed 3D SSM accurately represented the morphological features of normal dentition.
- Measured arch dimensions from the SSM aligned with previously reported values for normal dentition.
Conclusions:
- The 3D SSM of normal dentition offers a visual, objective tool to improve diagnostic efficiency in orthodontics.
- This SSM serves as a valuable 3D template for virtual setups, bracket fabrication, and aligner treatments in dentistry.
