Voxel Grid Surface Model Generation for Geometric Structures
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Solution Overview
Problem
Conventional methods for generating multi-dimensional surface models of geometric structures, such as the heart, often result in inaccurate representations due to false positive volumes and non-manifold surfaces, requiring additional processing and increasing complexity and time.
Innovation Solution
A computer-implemented method and system that constructs a bounding box around location data points, adds calculated points to ensure integer voxel dimensions, and identifies voxels in a voxel grid to generate a multi-faceted surface model, using techniques like alpha-hull approximation and Boolean Union operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If convex hull or star-shaped domain approximation techniques are used to generate individual surface models, then water-tight surfaces suitable for multi-dimensional Boolean operations are provided, but false positive volumes are created that misrepresent the actual region, reducing manufacturing precision
Solution Approach 1:
The patent creates a voxel grid that copies and represents the three-dimensional space occupied by the point cloud data. Each voxel acts as a discrete copy of a spatial volume element, allowing accurate representation of the actual region without the false positives inherent in convex hull methods. The voxel grid serves as a faithful digital copy of the physical space occupied by the points.
2Manufacturing precision
If alpha-shape technique is used to generate individual surface models, then more accurate approximations of the region are provided, but open and non-manifold surfaces are created that require additional processing, increasing device complexity and processing time
Solution Approach 1:
The patent performs preliminary action by pre-processing the point cloud data into a voxel grid representation before surface model generation. This preliminary voxelization step organizes the data into a structured format that inherently produces water-tight, manifold surfaces, eliminating the need for subsequent complex processing to fix non-manifold issues. The preliminary structuring of data prevents problems rather than requiring corrective actions later.
3Productivity
If conventional techniques are used to generate composite surface models from multiple individual surface models, then models can be created, but additional processing is required to handle non-manifold surfaces, increasing loss of time
Solution Approach 1:
The patent merges the voxel grids from multiple individual surface models into a single composite voxel grid, then extracts the composite surface model from this unified representation. This merging approach in the voxel domain simplifies the combination process and guarantees water-tight, manifold surfaces without requiring complex post-processing to handle non-manifold conditions that arise when traditional surface models are joined.
Data Source
AI summary
A method of constructing a bounding box comprises: acquiring a set of sensed data points; adding, for each sensed data point, at least one calculated data point; and defining a bounding box containing the sensed and calculated data points. A method of identifying voxels in a voxel grid corresponding to a plurality of data points comprises: calculating, for each data point, a distance between it and each voxel; creating a subset of voxels comprising voxels having a distance from one data point that is less than a predetermined distance; creating another subset comprising those voxels that neighbor a voxel in the first subset; computing, for each voxel in the second subset, a distance between it and each voxel in the first subset; and identifying each voxel in the first subset that is a distance away from each voxel in the second subset that exceeds a predetermined distance.