Intraoral Gingival Recession Measurement With Automated TMD Assessment
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Solution Overview
Problem
Current methods for assessing gingival recession and Temporomandibular Disorder (TMD) are inaccurate, time-consuming, and prone to human error, leading to inconsistent diagnosis and treatment plans.
Innovation Solution
An intraoral scan-based system using machine learning to measure and categorize gingival recession, and a combination of audio, video, and CBCT data to assess TMD, providing automated and standardized diagnostic outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual clinical evaluation methods are used for gingival recession measurement, then diagnostic flexibility is maintained, but measurement accuracy and consistency deteriorate due to human error and variability
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated intraoral scanning system that captures 3D digital impressions. The system uses optical scanning technology to obtain precise measurements of gingival recession without manual intervention, thereby improving measurement accuracy and consistency while eliminating human error associated with traditional clinical evaluation methods.
Solution Approach 2:
The patent creates a digital copy of the patient's oral structures through intraoral scanning. This digital model serves as a replica that can be repeatedly measured and analyzed without affecting the actual patient anatomy, enabling precise and consistent measurements of gingival recession while maintaining diagnostic flexibility through software-based analysis.
2Reliability
If comprehensive TMD assessment using multiple data types is implemented, then diagnostic accuracy improves, but assessment time and complexity increase
Solution Approach 1:
The patent combines multiple data types including intraoral scan data, audio recordings of jaw movements, video footage, and CBCT imaging into a single integrated assessment system. By merging these diverse data sources into one comprehensive platform, the system achieves high diagnostic accuracy for TMD while streamlining the assessment process through automated analysis algorithms that process all data types simultaneously rather than sequentially.
Solution Approach 2:
The patent performs preliminary processing and analysis of audio, video, and imaging data automatically as part of the assessment workflow. The system pre-processes these data types to extract relevant features and prepare them for integrated analysis, reducing the time required for comprehensive TMD evaluation by eliminating manual preprocessing steps and enabling parallel processing of multiple data streams.
Data Source
AI summary
A method is provided for measuring and categorizing gingival recession. In some cases, the method can include receiving intraoral scan data of a dentition of a patient. The method can include segmenting the intraoral scan data into a plurality of oral structures that comprise at least a tooth in the dentition of the patient, a gingiva, and a representation of an intersection between a first portion of the tooth and a second portion of the tooth. The method can include determining a gingival recession measurement indicative of a distance between the gingiva and the intersection. The method can include providing, to the user device, the gingival recession measurement.