Two-Stage Motion Correction for MRI Imaging
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Solution Overview
Problem
Magnetic resonance imaging (MRI) data is sensitive to object motion between acquisition steps, leading to motion artifacts in final images, especially in multi-repetition sequences with varying delay times.
Innovation Solution
Monitor object movement during each acquisition step using a camera system and adjust MRI data based on this monitoring, combining it with data comparison across steps to compensate for motion, thereby separating adjustments within and between steps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If camera-based motion monitoring and real-time data adjustment are implemented, then motion artifacts are reduced and image quality is improved, but device complexity and computational effort increase
Solution Approach 1:
The patent segments the motion correction process into two distinct stages: (1) real-time prospective correction during acquisition using camera monitoring, and (2) retrospective correction after acquisition using data comparison between steps. This segmentation allows each stage to handle specific aspects of motion correction independently, reducing the computational burden on any single stage while maintaining overall effectiveness.
Solution Approach 2:
The patent introduces camera-based motion monitoring as an intermediary system that continuously tracks object position and provides feedback for real-time data adjustment. This intermediary enables non-invasive motion detection and facilitates prospective correction without requiring direct modification of the MRI acquisition process itself.
2Manufacturing precision
If continuous camera monitoring and real-time adjustment are performed, then motion artifacts are minimized, but computational effort and processing time increase
Solution Approach 1:
The patent divides motion correction into prospective (real-time during acquisition) and retrospective (after acquisition) components. The prospective part handles motion during data collection, while the retrospective part processes and compares data between acquisition steps. This temporal segmentation reduces the computational load during critical real-time periods and allows batch processing afterward.
Solution Approach 2:
The patent performs preliminary motion monitoring and real-time data adjustment during the acquisition process itself, rather than waiting until after acquisition is complete. This preliminary action prevents motion artifacts from being introduced in the first place, reducing the need for extensive post-processing corrections.
3Measurement precision
If multi-repetition sequences with varying delay times are used, then signal-to-noise ratio is improved, but sensitivity to motion between acquisition steps increases
Solution Approach 1:
The patent implements feedback mechanisms at two levels: (1) real-time feedback from camera monitoring during each acquisition step to adjust data immediately, and (2) feedback from comparing acquisition steps to identify and correct motion artifacts. This multi-level feedback system maintains high signal-to-noise ratio while compensating for motion sensitivity in multi-repetition sequences.
Solution Approach 2:
The patent performs preliminary motion correction during each acquisition step using camera monitoring and real-time data adjustment, before the data is used in the final image reconstruction. This preliminary action prevents motion artifacts from accumulating across multiple repetitions, enabling reliable multi-repetition sequencing.
Data Source
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AI summary
For improving image quality in MRI, a method for magnetic resonance imaging of an object is provided which comprises obtaining MRI data during at least a first and a second acquisition step (1, 2, N). Each acquisition step (1, 2, N) comprises at least two data acquisition periods (11, 12, ..., NMN). A movement of the object is monitored by a camera system (7) during the acquisition steps (1, 2, N). Data obtained during the acquisition periods (11, 12, ..., NMN) is adjusted based on the monitoring. Data obtained during a first reference period (11) of the first acquisition step (1) is compared to data obtained during a second reference period (21) of the second acquisition step (2). The obtained or adjusted data is corrected based on a result of the comparison.