Intraoral Scan Alignment via Overlap Threshold
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Solution Overview
Problem
Existing methods for aligning three-dimensional intraoral images often result in inaccurate alignments when automatic alignment is selected, as they consistently perform initial alignment again, leading to positions that are more incorrect than before the alignment.
Innovation Solution
A data processing method that determines whether the relationship between two scan data sets satisfies specific alignment criteria, allowing for the omission of initial alignment and direct precise alignment, thereby preventing incorrect alignment positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic alignment is performed by consistently executing initial alignment followed by precise alignment, then the alignment process is simplified and can be automatically executed, but the alignment accuracy deteriorates because the images may be realigned to incorrect positions
Solution Approach 1:
The system changes the operational parameters of the alignment process by introducing a conditional branch: when the degree of overlap between scan data exceeds a predetermined threshold, the system executes only precise alignment (changing the process parameters) rather than the standard initial alignment followed by precise alignment. This parameter change resolves the contradiction by maintaining automatic operation while improving alignment accuracy in cases where the scans already have sufficient overlap.
Solution Approach 2:
The alignment process is made dynamic by adapting the execution path based on the degree of overlap between scan data. The system dynamically selects between two different alignment strategies: full alignment (initial + precise) when overlap is insufficient, and precise alignment only when overlap is sufficient. This dynamic adaptation resolves the contradiction by optimizing the process for each specific case rather than using a fixed procedure.
2Reliability
If initial alignment is always performed before precise alignment, then the alignment process is more robust for poorly overlapping scans, but unnecessary computation is performed when scans are already well-aligned
Solution Approach 1:
The system changes the computational parameters by conditionally executing the initial alignment step. When the degree of overlap exceeds the threshold, the system skips initial alignment and proceeds directly to precise alignment, thereby reducing computational energy consumption. When overlap is insufficient, the system executes both initial and precise alignment to ensure robustness. This parameter-based conditional execution resolves the contradiction between reliability and energy loss.
Solution Approach 2:
The system extracts and removes the initial alignment step from the standard alignment process when it is determined to be unnecessary. By checking the degree of overlap first, the system can extract (skip) the initial alignment computation when scans are already well-aligned, thereby reducing energy consumption while maintaining alignment robustness when needed.
3Manufacturing precision
If the user manually selects matching points for alignment, then alignment accuracy can be maximized for critical features, but the operation becomes complex and time-consuming
Solution Approach 1:
The system performs self-service by automatically determining the alignment parameters (degree of overlap) and selecting the appropriate alignment strategy without requiring manual user intervention. The system serves itself by checking the overlap condition and automatically choosing between full alignment and precise alignment only, thereby maintaining high precision while improving operational simplicity.
Solution Approach 2:
The system replaces the mechanical manual process of selecting matching points with an automated computational system that calculates the degree of overlap and determines the optimal alignment strategy. This substitution of manual mechanical operation with automated computational analysis resolves the contradiction by achieving both precision and simplicity.
Data Source
AI summary
Disclosed is a data processing method performed by a data processing device, the data processing method including obtaining a first scan model and a second scan model, determining whether to initially align the first scan model and the second scan model, and in response to determining not to initially align the first scan model and the second scan model, precisely aligning the first scan model and the second scan model.