3D Dental Prosthesis Surface Generation With AI Margin Detection
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Solution Overview
Problem
Conventional methods for generating prostheses manually result in increased operator fatigue, variability in quality and time, and depend heavily on the proficiency of the dentist or dental technician, leading to inconsistent outcomes.
Innovation Solution
An automated method using 3D scan data to generate an intermediate surface, inner surface, and outer surface of a prosthesis, utilizing artificial intelligence neural networks to determine tooth number, margin lines, and connect these surfaces, with adjustments for minimal thickness and cement gaps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual prosthesis generation method is used, then flexibility in customization is improved, but operator fatigue increases and productivity decreases
Solution Approach 1:
The system performs automated prosthesis generation using 3D scan data, margin line detection, and AI-based tooth number identification. The automated workflow reduces reliance on manual operator intervention while maintaining customization capabilities through programmable parameters and adaptive algorithms.
Solution Approach 2:
The patent replaces manual mechanical operations with computational processes. 3D scanning technology captures oral cavity geometry, AI algorithms automatically identify tooth numbers and margin lines, and software automatically generates prosthesis designs, substituting manual measurement and drawing operations with automated digital processes.
2Adaptability or versatility
If manual prosthesis generation method is used, then operator can adjust according to patient condition, but quality variability increases depending on operator proficiency
Solution Approach 1:
The system incorporates feedback mechanisms where 3D scan data provides accurate geometric information about the patient's oral cavity, margin line detection provides precise boundary information, and AI-based tooth number identification provides verification. This feedback loop ensures consistent, accurate results while maintaining patient-specific customization.
Solution Approach 2:
The patent creates accurate digital copies of the patient's oral cavity using 3D scanning technology. These digital models serve as precise replicas that can be manipulated and measured without affecting the original, enabling consistent reproduction of patient-specific anatomy across multiple prostheses and operators.
3Productivity
If automated method is used, then productivity and accuracy are improved, but device complexity increases
Solution Approach 1:
The automated system is divided into distinct functional modules: 3D scanning module for data acquisition, margin line detection module for boundary identification, AI-based tooth number identification module for classification, and prosthesis generation module for design creation. This segmentation allows each module to be optimized independently while working together as an integrated system.
Data Source
AI summary
An automated method for generating a prosthesis from a three dimensional (“3D”) scan data, the method includes generating an intermediate surface of the prosthesis extending toward an outside of a prepared tooth from a margin line of the prepared tooth in the 3D scan data, generating an inner surface of the prosthesis by determining a gap from a surface of the prepared tooth, generating an outer surface of the prosthesis and connecting the outer surface of the prosthesis and the intermediate surface of the prosthesis.