Weighted Overlapping Image Combination for MRI Motion Artifact Reduction
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Solution Overview
Problem
Current methods for combining multiple overlapping images in medical imaging, such as MRI, can produce non-diagnostic images if one image has significant motion, leading to motion artifacts that degrade image quality.
Innovation Solution
An imaging apparatus and method that acquires and compares overlapping image data sets, applying different weights to frequency ranges based on image quality to generate a weighted combined image, reducing motion artifacts while maintaining signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If equal weighting is used to combine multiple overlapping images, then signal-to-noise ratio is improved, but motion artifacts are exacerbated when one image contains significant motion
Solution Approach 1:
The patent applies different weighting factors to different image data sets based on their individual quality characteristics. Instead of uniform weighting, each image receives a weight proportional to its quality metric (e.g., sharpness, contrast, noise level), allowing high-quality regions to contribute more to the final composite image while suppressing degraded regions with motion artifacts.
Solution Approach 2:
The patent dynamically adjusts the weighting parameters based on quality metrics calculated for each image. By computing quality scores and using them to determine weight values, the system adapts the combination process to the actual state of each image, optimizing the balance between noise suppression and artifact reduction.
2Reliability
If multiple overlapping images are acquired to suppress artifacts, then image quality is improved, but acquisition time increases
Solution Approach 1:
The patent extracts and utilizes the overlapping regions between multiple images to improve image quality through weighted combination. By focusing on the overlapping areas and applying quality-based weighting, the method maximizes the benefit of multiple acquisitions while minimizing the time penalty, as the processing leverages existing redundant data rather than requiring additional acquisition sequences.
3Object-affected harmful factors
If images with motion are detected and rejected, then motion artifacts are reduced, but image quality deteriorates when all images contain some motion
Solution Approach 1:
The patent changes the approach from binary rejection/acceptance to continuous quality-based weighting. Instead of discarding images with motion, the system calculates quality metrics and adjusts weights accordingly, allowing partially degraded images to still contribute useful information while reducing the impact of severe artifacts.
Solution Approach 2:
The patent creates a composite image by combining multiple individual images with different weightings. The final image is a weighted sum of contributions from multiple source images, where each image's quality characteristics determine its weight, resulting in a composite that optimizes overall quality by leveraging the strengths of each individual acquisition.
Data Source
AI summary
An imaging processing method that acquires first and second overlapping image data sets by performing first and second measurements on an overlapping location at first and second times, wherein the first and second times are different times; determines whether the first and second overlapping image data sets have substantially a same image quality; and generating and outputting, a first weighted overlapping combined image by combining (a) first weighted image data generated by applying a first weight to an overlapping frequency range of the overlapping image data set having a higher image quality and (b) second weighted image data generated by applying a second weight to the overlapping frequency range of the overlapping image data set having a lower image quality, wherein the first weight is larger than the second weight.