Simultaneous CBCT–3D Scan Matching for Motion Correction
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Solution Overview
Problem
Existing dental CBCT and 3D face scan imaging technologies require fixing mechanisms that obstruct the representation of a patient's actual appearance, making it difficult to capture realistic images.
Innovation Solution
A method and apparatus that synchronize acquisition time points and conform coordinate systems of cone beam CT and 3D scan data, using iterative closest point (ICP) algorithms to correct patient motion, allowing for the construction of clear 3D images without fixing mechanisms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If fixing mechanisms (chin rest, additional fixing mechanisms) are used to minimize patient motion during imaging, then imaging stability is improved, but the patient's actual appearance is obscured and realistic representation is lost
Solution Approach 1:
The patent separates the functions of motion stabilization and appearance capture by processing multiple frames independently. Each frame is captured without physical constraints, then stabilized through computational matching of depth maps and coordinate transformations, allowing realistic appearance to be preserved while achieving imaging stability post-capture
Solution Approach 2:
The patent replaces mechanical fixing mechanisms with a computational stabilization system. Instead of using chin rests and additional fixing mechanisms to prevent motion, the system uses depth map matching, ICP algorithms, and coordinate transformations to stabilize images digitally after capture, eliminating the need for physical constraints that obscure appearance
2Ease of manufacture
If multiple frames are captured without fixing mechanisms to show actual appearance, then realistic representation is improved, but motion blur increases due to patient movement
Solution Approach 1:
The patent implements feedback through depth map matching between consecutive frames. The system compares depth maps, identifies motion differences, and uses this feedback to transform and align subsequent frames, progressively reducing motion blur while preserving the realistic appearance captured without fixing mechanisms
Solution Approach 2:
The patent performs preliminary coordinate system conforming and depth map matching before final image construction. By establishing transformation relationships between frames in advance and applying them systematically, the system prepares the data structure needed to eliminate motion blur during image synthesis while maintaining realistic appearance features
3Productivity
If CBCT and 3D scan imaging are performed simultaneously without fixing mechanisms, then operational efficiency is improved, but coordinate system alignment becomes more difficult
Solution Approach 1:
The patent implements a universal coordinate system conforming process that handles both CBCT and 3D scan data through the same ICP algorithm and transformation framework. This multi-functional approach simultaneously manages coordinate alignment for different imaging modalities, simplifying the overall system architecture despite the complexity of simultaneous multi-modal imaging
Solution Approach 2:
The patent introduces depth maps as an intermediary element that facilitates coordinate system alignment between CBCT and 3D scan data. By using depth maps as a common reference framework, the system enables accurate spatial correspondence between different imaging modalities without requiring complex direct transformation methods
Data Source
AI summary
The present invention provides a method of matching data, which is performed by an apparatus for matching data, the method including synchronizing acquisition time points of cone beam computed tomography (CBCT) data and 3D scan data, conforming coordinate systems of the CBCT data and the 3D scan data, constructing a 3D scan image in which a motion is corrected by matching depth maps created each time the 3D scan data are acquired, and constructing a CBCT 3D image in which the motion is corrected from the CBCT data by applying motion information acquired by matching the depth maps.