Automated 3D Dental Model Reconstruction After Appliance Removal
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Solution Overview
Problem
Existing 3D image editing tools require significant manual effort and are inefficient in removing orthodontic appliances like brackets from patient scans, often resulting in incomplete or inaccurate 3D models.
Innovation Solution
An automated method for detecting and removing orthodontic appliances from 3D images, followed by reconstructing the tooth surface beneath, using machine learning and image processing to create a refined 3D model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual 3D image editing tools are used to remove orthodontic appliances, then the removal can be performed, but the process requires significant manual effort and time
Solution Approach 1:
The system performs automatic detection and removal of orthodontic appliances without requiring manual user intervention. The algorithm independently identifies appliance locations, segments them from the 3D scan data, and reconstructs the underlying tooth surfaces, making the entire process self-service and fully automated.
Solution Approach 2:
The patent replaces manual mechanical editing operations with an automated computational system that uses image processing algorithms and machine learning models to detect, segment, and remove orthodontic appliances from 3D dental scans, substituting human manual work with intelligent automated processing.
2Manufacturing precision
If existing 3D image editing tools are used to remove brackets, then bracket removal is possible, but the tools lack the capability to reconstruct the surface of the teeth resulting in holes or blank spots
Solution Approach 1:
The system extracts and removes only the orthodontic appliance components from the 3D scan data while preserving the underlying tooth structure. By selectively extracting the appliance geometry and separating it from the tooth model, the system creates clean removal boundaries that enable accurate surface reconstruction without leaving holes or artifacts.
Solution Approach 2:
The system performs preliminary segmentation and separation of the orthodontic appliance from the tooth structure before final removal. By pre-processing the 3D data to identify and isolate appliance boundaries, the system prepares the model for clean reconstruction, ensuring that the underlying tooth surfaces can be accurately recovered without manual intervention.
3Productivity
If manual editing is performed to remove appliances and reconstruct surfaces, then complete 3D models can be achieved, but the process is labor intensive and requires multiple hours
Solution Approach 1:
The system implements a continuous automated workflow that processes 3D dental scans through detection, segmentation, removal, and reconstruction stages without interruption or manual intervention. The pipeline maintains continuous processing from input scan to output model, eliminating idle time and manual transfer steps between operations.
Solution Approach 2:
The system uses the original 3D scan data as a template to reconstruct tooth surfaces after appliance removal. By copying and utilizing the underlying tooth geometry information that exists in the original scan, the system can rapidly regenerate complete surface models without requiring time-consuming manual sculpting or reconstruction techniques.
Data Source
AI summary
A system and method that is a web based application for creating and managing 3D models used in orthodontic laboratory prescriptions within a dental clinic or lab. The method includes automatically detecting and removing any appliances contained within the 3D image file. After the appliances have been removed, the system then automatically replaces the removed image data with new image data that is calculated to approximate the surface of the tooth disposed beneath the deleted appliance in order to create a clean, second 3D image. The method may further automatically refine the second 3D image of the patients teeth or delete any artifacts which remain after creation of the second 3D image. The second 3D image may then be used as the basis on which to change the patients orthodontic or dental prescription.