3D Data Alignment Without Segmentation for Dental CAD/CAM
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Solution Overview
Problem
Current methods for aligning three-dimensional volumetric and surface data in dental CAD/CAM applications are inefficient due to the need for segmentation processes, which are time-consuming and prone to user-dependent errors, and are affected by artifacts from metallic materials, leading to inaccurate location alignment.
Innovation Solution
A three-dimensional data alignment apparatus and method that directly aligns volumetric and surface data without segmentation, using vertex extraction, intensity value interpolation, and exclusion of voxels with high reference intensity values to minimize location errors and prevent distortion from metallic artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If segmentation process is used to align volumetric and surface data, then location alignment can be achieved, but the process becomes time-consuming and user-dependent errors increase
Solution Approach 1:
The patent extracts key geometric features (vertices, edges, surfaces) directly from the volumetric data without performing full segmentation. By extracting only the necessary geometric elements needed for alignment, the method avoids the time-consuming full segmentation process while maintaining alignment accuracy through direct feature matching between volumetric and surface data.
Solution Approach 2:
The patent performs a form of segmentation by dividing the volumetric data into meaningful geometric components (vertices, edges, surfaces) that can be directly matched with surface data. This selective segmentation approach identifies only the relevant geometric features needed for alignment, reducing processing time compared to complete segmentation while preserving alignment precision.
2Measurement precision
If segmentation process is used to align volumetric and surface data, then location alignment can be achieved, but user-dependent errors increase
Solution Approach 1:
The alignment method performs self-service by automatically identifying corresponding geometric features between volumetric and surface data through mathematical operations. The system independently extracts vertices, edges, and surfaces from volumetric data and matches them with surface data features without requiring user intervention, thereby eliminating user-dependent errors and ensuring consistent, reproducible alignment results.
Solution Approach 2:
The patent employs feedback mechanisms by calculating alignment errors and iteratively optimizing the transformation parameters. The system evaluates the accuracy of feature matching and adjusts the alignment transformation accordingly, providing continuous feedback to improve alignment precision while maintaining consistency across different datasets.
3Quantity of substance
If all voxels including high intensity artifacts are used for alignment, then more data points are available, but distortion from metallic materials increases
Solution Approach 1:
The patent applies local quality by treating different regions of the volumetric data differently based on their intensity characteristics. High-intensity voxels corresponding to metallic artifacts are identified and excluded from the alignment calculation, while normal-intensity voxels are retained. This selective approach maintains the quality of alignment data by removing only the harmful artifact regions while preserving the majority of valid data points.
Solution Approach 2:
The method extracts and removes high-intensity voxels that represent metallic artifacts from the dataset used for alignment. By taking out these problematic data points through intensity-based filtering, the system prevents artifact-induced distortion while retaining sufficient remaining voxels to perform accurate alignment. This extraction approach balances data quantity with data quality.
4Adaptability or versatility
If volumetric data is used for alignment, then internal structures can be captured, but measurement accuracy is lower compared to surface data
Solution Approach 1:
The patent merges the advantages of both volumetric and surface data by using surface data as the primary reference for alignment (leveraging its high measurement precision) while incorporating volumetric data features to maintain adaptability. The method combines geometric features from both data types, using surface data for accurate feature extraction and volumetric data for complementary structural information, thereby achieving both versatility and precision.
Data Source
AI summary
The present disclosure discloses a three-dimensional data alignment apparatus, a three-dimensional data alignment method, and a recording medium, which may align a location between volumetric data and surface data even without a segmentation process of extracting a surface from the volumetric data. A three-dimensional data alignment apparatus according to an exemplary embodiment of the present disclosure includes a three-dimensional data alignment unit for aligning a location between first three-dimensional data and second three-dimensional data expressed in different data forms with regard to a target to be measured. The first three-dimensional data are three-dimensional data acquired in a voxel form with regard to the target to be measured, and the second three-dimensional data are three-dimensional data acquired in a surface form with regard to the target to be measured. The three-dimensional data alignment unit is configured to extract one or more vertices from the second three-dimensional data; extract the first voxel values of first voxels located around each vertex from the first three-dimensional data, based on a location of each vertex extracted from the second three-dimensional data; determine corresponding points between the first three-dimensional data and the second three-dimensional data based on the first voxel values extracted from the first three-dimensional data; and calculate location conversion information minimizing a location error between the first three-dimensional data and the second three-dimensional data based on the corresponding points.