3D TMJ Modeling With Precise Condyle and Fossa Contours
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Solution Overview
Problem
Existing methods for automated segmentation of CT images to construct 3D models of the temporomandibular joint (TMJ) suffer from significant imprecision, particularly in the condyles and articular fossae, leading to distorted perceptions of volume and reduced clinical significance due to inaccuracies in recognizing borderline values and manual segmentation being time-consuming.
Innovation Solution
A method involving multi-planar reconstruction of CT data to precisely visualize and encircle contours of condyles and articular fossae, using software tools to create 3D objects with a precision of up to 100 microns, and integrating these with dental arch models to form accurate 3D models of the mandible and maxilla.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated segmentation of CT images is used to construct 3D models of TMJ, then productivity is improved, but manufacturing precision deteriorates due to significant imprecision in condyles and articular fossae areas
Solution Approach 1:
The patent applies segmentation by dividing the TMJ region into distinct anatomical components (condyles, articular fossae, joint space) and processing each separately with specialized algorithms. This allows automated high-speed processing while maintaining precision for each specific structure through targeted segmentation strategies.
Solution Approach 2:
The patent introduces an intermediary manual verification and adjustment step where clinicians can review and refine automated segmentation results. This intermediary process corrects borderline cases and cartilage interpretation errors while maintaining overall automation efficiency, resolving the contradiction between speed and precision.
2Manufacturing precision
If manual segmentation of CT images is used to construct 3D models of TMJ, then manufacturing precision is improved, but productivity deteriorates due to time-consuming process
Solution Approach 1:
The patent performs preliminary automated segmentation to generate initial 3D models quickly, then applies targeted manual refinement only to specific problematic areas (borderline regions, cartilage interfaces). This preliminary action approach maintains high precision while dramatically reducing total processing time compared to fully manual segmentation.
Solution Approach 2:
The patent applies partial manual intervention rather than complete manual segmentation. By using automated methods for clear-cut regions and applying manual refinement only where necessary (partial action), the system achieves near-manual precision with fraction of the time investment.
3Ease of operation
If automated segmentation algorithms are used, then ease of operation is improved, but measurement precision deteriorates due to inability to recognize borderline values
Solution Approach 1:
The patent implements feedback mechanisms where the system identifies uncertain or borderline segmentation cases and flags them for review. This feedback loop allows automated processing to proceed for clear cases while directing attention to ambiguous regions, maintaining both ease of operation and measurement precision through adaptive processing.
Solution Approach 2:
The patent replaces purely algorithmic mechanical segmentation with a hybrid system that incorporates clinician expertise and judgment. This substitution of automated mechanical processing with human cognitive evaluation for borderline cases improves measurement precision while maintaining operational simplicity through the automated framework.
4Productivity
If automated segmentation is used, then productivity is improved, but reliability deteriorates due to distorted perception of volume and inaccurate joint space measurement
Solution Approach 1:
The patent applies different segmentation parameters and threshold values for different anatomical regions and tissue types (bone vs. cartilage). By changing parameters adaptively based on local anatomical characteristics, the system maintains high productivity while improving reliability of volume and joint space measurements through region-specific optimization.
Solution Approach 2:
The patent introduces an intermediary quality control step where automated segmentation results are verified and adjusted for volumetric accuracy. This intermediary verification process corrects systematic errors in volume perception and joint space measurement while maintaining the overall efficiency of automated processing.
Data Source
AI summary
In CT visualization software, zones of the right and left temporomandibular joints (TMJs) are visualized sequentially. In a frontal plane, each of the condylar processes of the TMJs are delimited into sections. In a sagittal plane, separate 3D contours of the fossae and the condyles of the TMJs are created. The contours of the condyles are combined with a 3D model of the mandibular teeth, and a 3D model of the mandible with the teeth and the condylar processes is obtained. The contours of the fossae are combined with a 3D model of the maxillary teeth, and a 3D model of the maxilla with the teeth and the contours of the glenoid fossae is obtained. The 3D scene objects obtained are distributed according to side and identification code, and precise tracking of the movement of the condyles and the fossae of the TMJs during movement of the mandible is provided.