CT Motion Compensation via View-Weighting
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Solution Overview
Problem
Computed tomography (CT) image reconstruction algorithms assume a stationary subject, leading to motion artifacts when the patient or object moves during data acquisition, which complicates image interpretation and increases computational expense.
Innovation Solution
A method that reconstructs multiple images from projection data, calculates a motion metric, and applies a view-weighting function to down-weight slices with motion artifacts, improving image quality while maintaining computational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If motion correction is performed using traditional approaches to determine motion path and compensate during reconstruction, then image quality is improved, but algorithmic complexity and computational expense increase significantly
Solution Approach 1:
The patent extracts and compensates for motion effects selectively by identifying and removing motion-related components from the projection data rather than applying comprehensive motion correction to all data. This involves separating motion-corrected and non-motion-corrected projection data and selectively applying correction only where motion artifacts are present, thereby reducing overall computational complexity while maintaining image quality.
Solution Approach 2:
The patent applies motion correction partially rather than universally. By using view-weighting functions that apply motion correction only to specific angular views where motion artifacts are detected, rather than correcting all projection data uniformly, the system achieves motion artifact reduction with reduced computational expense compared to full motion correction approaches.
2Manufacturing precision
If motion correction is performed using traditional approaches to determine motion path and compensate during reconstruction, then image quality is improved, but reconstruction time increases substantially
Solution Approach 1:
The patent extracts only the necessary motion-corrected projection data needed for reconstruction rather than processing all projection data through motion correction. By identifying and isolating the specific data components affected by motion and correcting only those, the system reduces reconstruction time while maintaining image quality.
Solution Approach 2:
The patent applies motion correction partially by using view-weighting functions that selectively correct only certain angular views where motion artifacts are detected. This partial correction approach significantly reduces reconstruction time compared to applying motion correction to all projection data, while still achieving acceptable image quality by addressing the most problematic regions.
3Productivity
If standard image reconstruction is performed assuming stationary subject, then computational efficiency is maintained, but motion artifacts appear in the tomographic images
Solution Approach 1:
The patent applies different processing qualities to different regions of the projection data. By using view-weighting functions that apply motion correction selectively to specific angular views where motion artifacts are detected, rather than uniformly processing all data, the system maintains computational efficiency for stationary regions while improving image quality in motion-affected regions.
Solution Approach 2:
The patent introduces view-weighting functions as an intermediary mechanism between the projection data and image reconstruction. These weighting functions act as a mediator that selectively attenuates or enhances specific angular views based on detected motion, allowing the system to maintain computational efficiency while reducing motion artifacts through the intermediate weighting step rather than requiring full motion correction.
Data Source
AI summary
Methods and systems are provided for motion compensation in computed tomography imaging. In one embodiment, a method comprises reconstructing at least two images from projection data, calculating a motion metric based on the at least two images, selecting a view-weighting function based on the motion metric, and generating a display from the projection data based on the selected view-weighting function. In this way, an image can be reconstructed with the selected view-weighting function which down-weights slices in the image containing motion artifacts. As a result, the image quality of the reconstructed image may be improved with computational efficiency.