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Tooth Anatomy

Tooth Anatomy

The human tooth enables us to eat a variety of foods, speak clearly, and even aid in shaping our faces. Teeth are composed of various elements that work together. Here's a detailed look at the anatomy of a human tooth.
The Crown, Neck, and Root
The visible part of the tooth is referred to as the crown. It's covered by enamel, the hardest substance in the human body. The crown is uniquely shaped for each type of tooth, allowing for different functions such as cutting, tearing, or grinding food.

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Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images

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Published on: February 23, 2024

Automated digital dental articulation.

James J Xia¹, Yu-Bing Chang, Jaime Gateno

¹The Methodist Hospital Research Institute, Houston, Texas, USA. JXia@tmhs.org

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|October 1, 2010

Summary

This study introduces an automated method for accurately articulating digital dental models to maximum intercuspation (MI). The novel approach significantly improves efficiency and precision in digital dentistry workflows.

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Area of Science:

Digital dentistry
Biomedical engineering
Computer-aided design (CAD)

Background:

Articulating digital dental models is crucial for treatment planning.
Current methods for articulating digital dental models are often inaccurate and time-consuming.

Purpose of the Study:

To present an automated and efficient approach for articulating digital dental models to maximum intercuspation (MI).

Main Methods:

The method involves an initial positioning step using dental curves and point matching.
A novel iterative surface-based minimum distance mapping with collision constraints is used for final positioning to MI.

Main Results:

The automated approach was validated on 12 sets of digital dental models.
Results demonstrated accurate and effective articulation of digital dental models to the MI position.

Conclusions:

The proposed automated method offers an accurate and efficient solution for articulating digital dental models.
This technique has the potential to streamline digital dentistry workflows.