Medical Image Motion Artifact Reduction via Derivative of Planar Integrals
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Solution Overview
Problem
Medical imaging data often suffers from motion artifacts due to patient movement during data acquisition, leading to inaccurate diagnoses, as existing motion indexes are either inapplicable or inaccurate for various projection data sets.
Innovation Solution
The use of a derivative of planar integrals (DPI) as a motion index to select consistent portions of projection data, which are then used for improved image reconstruction, reducing motion artifacts by identifying data sets with minimal motion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing motion indexes (Helgason-Ludwig consistency condition, complementary rays) are used to identify motion-free data portions, then image quality may be improved, but the methods are either inapplicable to different situations or inaccurate over various projection data sets
Solution Approach 1:
The patent transforms the motion detection problem from checking geometric consistency conditions to analyzing temporal changes in projection data parameters. By computing the time derivative of projection data and comparing it to a threshold, the method adapts to different projection data sets without requiring modification of the underlying detection principle. This parameter-based approach replaces the rigid Helgason-Ludwig consistency checks with a flexible temporal derivative analysis that works across various imaging scenarios.
Solution Approach 2:
The patent segments the projection data into motion-affected and motion-free portions by evaluating the derivative magnitude at each data point. Instead of treating the entire data set uniformly or requiring complete data consistency, the method identifies and isolates specific segments of projection data where motion artifacts are minimal, allowing selective use of high-quality data for image reconstruction.
2Productivity
If all acquired projection data is used for image reconstruction, then productivity is improved, but motion artifacts degrade image quality
Solution Approach 1:
The patent applies partial action by using only the portions of projection data where the temporal derivative is below the threshold, rather than requiring all data to meet strict quality criteria. This allows the reconstruction process to proceed with sufficient quality data without discarding potentially useful information, balancing image quality with productive use of acquired data.
Solution Approach 2:
The motion detection mechanism is self-service in that it automatically identifies and flags motion-affected data portions without requiring external intervention or complex preprocessing. The derivative-based thresholding provides an automated quality assessment that integrates seamlessly into the reconstruction workflow, maintaining productivity while ensuring quality control.
Data Source
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AI summary
A data acquisition unit (11) acquires first raw data about an object at a first position and second raw data about the object at a second position. a processing unit (12) evaluates an amount of motion of the object between an acquisition time of the first raw data and an acquisition time of the second raw data. The processing unit (12) calculates a derivative of first plane integrals on a test plane including the first position and the second position by using the first raw data, calculates a derivative of second plane integrals on the test plane by using the second raw data, and evaluates the amount of motion by using a difference between the derivate of the first plane integrals and the derivate of the second plane integrals.