CBCT Motion Artefact Reduction via Spatial Transformation
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Solution Overview
Problem
CBCT imaging is hindered by patient movement during scanning, causing blurring in reconstructed volumetric images, and existing solutions like metal markers are cumbersome and introduce additional artefacts.
Innovation Solution
A method that involves creating and optimizing spatial transformation parameters for each imaging angle to correct for unknown transformations of the patient during scanning, using simulated projections to find the best-fitting images and iteratively refining the reconstruction process without relying on metal markers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metal markers are affixed to the patient to track motion, then motion artefacts are reduced, but the procedure becomes time-consuming and introduces additional imaging artefacts
Solution Approach 1:
The invention extracts and removes the metal markers from the imaging system entirely. Instead of using physical markers to track motion, the system uses the patient's own anatomical structures visible in the X-ray images as natural landmarks for motion tracking. This eliminates the need for marker affixing procedures and removes the source of additional imaging artefacts while maintaining motion tracking capability
Solution Approach 2:
The invention creates a digital copy or model of the patient's anatomy from the X-ray images themselves, using image processing algorithms to identify and track anatomical landmarks. This digital representation serves the same function as physical markers would, but without the drawbacks of physical marker implementation
2Measurement precision
If the patient is restrained to prevent movement during scanning, then image clarity is improved, but the procedure becomes impractical and time-consuming
Solution Approach 1:
The system continuously monitors patient motion during the scanning process by analyzing sequential X-ray images and comparing anatomical landmark positions. This motion information is fed back in real-time to the reconstruction algorithm, which dynamically adjusts to compensate for detected movements. This feedback mechanism allows clear imaging without requiring patient restraint
Solution Approach 2:
The system performs preliminary identification and tracking of anatomical landmarks before the main reconstruction process. By establishing reference points and motion patterns in advance, the system can anticipate and compensate for patient movements during scanning, eliminating the need for restrictive positioning measures
3Measurement precision
If multiple spatial transformation parameters are optimized for each imaging angle, then motion artefacts are reduced, but computational complexity increases
Solution Approach 1:
The invention segments the motion correction problem by angle, optimizing spatial transformation parameters independently for each imaging angle rather than attempting a global optimization. This divides the complex computational task into manageable angle-specific subproblems, reducing overall computational complexity while maintaining correction accuracy
Solution Approach 2:
The system optimizes only the necessary spatial transformation parameters for each angle rather than all possible parameters. By focusing on the minimal set of parameters that actually affect motion artefacts at each angle, the computation remains tractable while achieving sufficient correction accuracy
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces motion-related imaging artefacts, improves image clarity, and minimizes the need for patient restraint or additional markers, enhancing the accuracy and efficiency of CBCT imaging.
Implementation Method 1
the penetrating radiation is not necessarily restricted to X-ray radiation, and the present disclosure is also applicable to other forms of penetrating imaging
Data Source
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AI summary
Motion artefact reduction for penetrating imaging comprises: obtaining (2-02) a sequence of captured images, each associated with an imaging angle (ϕ); applying an initial reconstruction (2-04) on captured images, thereby creating an initial reconstructed volumetric image; simulating projections (2-14) of the initial reconstructed volumetric image by varying spatial transformations, thereby generating simulated image sets from the initial reconstructed volumetric image, each set having a common imaging angle, wherein the simulated images within each set differ by different spatial transformations; for each set, determining (2- 16) the image having a best fit with the image associated with the common imaging angle; and applying a second reconstruction (2-22) on the spatially transformed versions of the captured images, thereby creating a transformation-corrected reconstructed volumetric image.