3D Dental Appliance Design with Subgrid Volumetric Processing
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Solution Overview
Problem
Existing volumetric operations for digital 3D data, particularly in dental CAD, are computationally demanding and require significant memory and processing time, especially when dealing with large dental appliances and high-resolution meshes.
Innovation Solution
Representing the digital 3D volumetric space using subgrids, computing signed distances for each subgrid, and identifying a group of subgrids that correspond to the dental data to perform volumetric operations efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If volumetric operations are performed using traditional marching cubes algorithm with high-resolution grids, then mesh reconstruction precision is improved, but computational time and memory requirements increase significantly
Solution Approach 1:
The patent divides the 3D volumetric space into multiple subgrids (e.g., 8 subgrids per dimension, totaling 512 subgrids). Each subgrid is processed independently to compute signed distances, allowing parallel computation and reducing the computational burden on any single processor while maintaining overall precision through the systematic combination of subgrid results.
Solution Approach 2:
The patent introduces a hierarchical grid structure where subgrids are organized in multiple dimensions. By computing signed distances at the subgrid level rather than at the individual cell level, the system achieves a dimensional abstraction that reduces computational complexity while preserving the essential geometric information needed for accurate mesh reconstruction.
2Measurement precision
If volumetric operations are performed using traditional marching cubes algorithm with high-resolution grids, then mesh reconstruction precision is improved, but memory requirements increase significantly
Solution Approach 1:
The patent segments the volumetric data into subgrids, where each subgrid stores only the signed distance values for its local region. This segmentation allows the system to process and store data in smaller, manageable chunks rather than loading the entire high-resolution volumetric dataset into memory at once, significantly reducing peak memory requirements while maintaining reconstruction precision.
Solution Approach 2:
The patent computes signed distances for all subgrids within the bounding box of the dental data, even though not all subgrids may contain surface points. This partial computation approach ensures that only the necessary subgrids are processed, avoiding unnecessary memory allocation and computation for regions that do not contribute to the final mesh reconstruction.
3Reliability
If volumetric operations are performed on the entire bounding box, then completeness of data processing is improved, but computational efficiency deteriorates
Solution Approach 1:
The patent computes signed distances for subgrids based on their local relevance to the dental data. By evaluating each subgrid's position and content, the system can selectively process only those subgrids that intersect with or are adjacent to the dental structures, rather than uniformly processing the entire bounding box. This local quality approach maintains processing completeness for relevant regions while improving overall computational efficiency.
Data Source
AI summary
An aspect of the present disclosure is to provide a computer implemented method that performs volumetric operations faster and with reduced memory requirements. In an embodiment, this efficiency is achieved by representing, only partially, a digital 3D volumetric space of a digital 3D dental data with subgrids. It is an advantage to avoid computations in parts of a digital 3D volumetric space because execution times or memory requirements or both may be smaller. This may further be enhanced by the fact that the disclosure operates at subgrids level as opposed to individual cell level.