3D Dental Model Correction for Accurate Occlusion Mapping
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Solution Overview
Problem
Existing three-dimensional scanning methods for generating dental models often result in inaccuracies such as errors in stitching, twists, and skew, leading to poor quality occlusion mapping and bite articulation, which can cause issues like tooth wear and temporomandibular joint disorders.
Innovation Solution
A method involving obtaining 3D models of the upper and lower jaws, adjusting these models to correct errors, and generating an occlusion map by aligning and adjusting parameters to improve accuracy, using techniques like distortion functions and loss functions to minimize discrepancies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If three-dimensional scanning is used to generate dental models, then the scanning process is non-invasive and digital, but accumulated stitching errors result in inaccuracies of up to 0.5 mm in the distance between molars and absolute tooth positions
Solution Approach 1:
The patent introduces physical reference objects (such as articulators or bite blocks) as intermediaries between the scanning process and the final dental model. These physical references provide known geometric relationships that can be detected during scanning and used to correct accumulated stitching errors, thereby maintaining measurement precision while preserving the benefits of digital scanning.
Solution Approach 2:
The patent replaces traditional mechanical measurement methods (physical calipers, manual measurements) with a computational correction system that uses distortion functions and loss functions to mathematically adjust the 3D model. This substitution eliminates the need for post-scanning mechanical measurements while correcting the inaccuracies introduced during the scanning process.
2Measurement precision
If scan data is collected and three-dimensional models are generated, then occlusion mapping can be performed, but computing resources and processing time are consumed
Solution Approach 1:
The patent extracts and corrects only the specific geometric transformations (rigid body transformations and distortion) that cause measurement errors, rather than reprocessing the entire scan dataset. By isolating and correcting only the problematic components, the system reduces computing resource requirements while maintaining occlusion mapping accuracy.
Solution Approach 2:
The patent changes the parameters of the 3D model by applying correction factors derived from distortion functions and loss functions. These parameter adjustments (scaling, rotating, translating) are computationally efficient compared to complete model regeneration, allowing accurate occlusion mapping with reduced computing resource consumption.
3Adaptability or versatility
If stitching process is used to combine scan data, then complete three-dimensional models can be generated, but accumulated errors cause the distance between molars to be greater or less than actual distance
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors and compares the scanned geometry against expected anatomical relationships and physical reference objects. When deviations are detected (such as incorrect molar distances), the system uses this feedback to adjust and correct the stitching process, ensuring manufacturing precision is maintained while preserving complete model generation capability.
Solution Approach 2:
The patent applies preliminary corrections by detecting and compensating for stitching errors during the model generation process itself, rather than allowing errors to accumulate and correct them afterward. This preliminary action ensures that the distance between molars and other critical dimensions are accurate from the outset, maintaining both complete model generation and manufacturing precision.
Data Source
AI summary
A method may include receiving a 3D model of the patient's upper jaw, receiving a 3D model of the patient's lower jaw, and receiving a model of the patient's upper jaw in occlusion with the patient's lower jaw. The method may also include adjusting a shape of the one or both of the 3D model of the patient's upper jaw and the 3D model of the patient's lower jaw based on the model of the model of the patient's upper jaw in occlusion with the patient's lower jaw and fitting, after adjusting, the 3D model of the patient's upper jaw and the 3D model of the patient's upper jaw. The method may also include generating occlusion map for the patient based on the fitting of the adjusted model of the upper law and the adjusted model of the lower jaw.