MRI Motion Correction Using Multi-Region Body Movement Tracking
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Solution Overview
Problem
Existing MRI technologies struggle to accurately analyze and correct for body movements during examinations, leading to issues such as image blurring or artifacts due to overcorrection or undercorrection of body movement, particularly with irregular movements.
Innovation Solution
An MRI apparatus equipped with a processor that sets a target region for monitoring body movements, analyzes the movement and retention time of the subject within and outside this region, and adjusts body movement correction accordingly, using surveillance cameras and nuclear magnetic resonance signals to provide detailed body movement information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If body movement correction is performed using conventional methods, then artifacts caused by body movement can be reduced, but image blurring occurs due to overcorrection or insufficient correction due to lack of detailed movement analysis
Solution Approach 1:
The video monitoring area is divided into multiple regions (first region, second region, third region) with different distances from the examination area. Each region provides different levels of movement information, allowing progressive analysis from gross movement detection to precise movement quantification. This segmentation enables accurate differentiation between subject body movement and examination target movement.
Solution Approach 2:
The invention adds spatial dimensionality to body movement detection by creating multiple monitoring regions at different distances from the examination area. Instead of single-point detection, the system uses multi-regional video analysis to capture movement gradients, providing both magnitude and direction information for more accurate correction decisions.
2Measurement precision
If detailed body movement analysis is implemented using multiple monitoring regions, then correction accuracy improves, but device complexity and processing requirements increase
Solution Approach 1:
The video processing system is segmented into region-specific analysis modules, where each region (first, second, third) has dedicated processing logic. This modular segmentation simplifies the overall complexity by breaking down the complex task of detailed movement analysis into manageable regional comparisons, making the system more implementable despite the enhanced precision requirements.
3Productivity
If conventional body movement detection methods are used, then processing time is reduced, but the ability to detect movement direction and magnitude is insufficient
Solution Approach 1:
The invention extracts specific movement information (direction, magnitude, retention time) from video data by comparing subject position across multiple predefined regions. Instead of processing entire video frames for general movement detection, the system extracts only the relevant positional information relative to the examination area, maintaining processing efficiency while capturing complete movement characteristics.
Solution Approach 2:
Multiple monitoring regions are pre-defined and positioned at specific distances from the examination area before the examination begins. This preliminary setup of regional boundaries and detection zones allows for rapid real-time comparison during the examination without requiring complex on-the-fly calculations, thus maintaining high processing speed while enabling detailed movement analysis.
Data Source
AI summary
Provided are a unit capable of more detailed analysis of a body movement occurring during an MRI examination and an MR image in which body movement correction with high accuracy is performed by the unit.An MRI apparatus includes a processor configured to perform body movement processing. The processor is configured to set, in a video of an imaging device that monitors a body movement, a region (target region) for monitoring a body movement with respect to an examination target, monitor a movement of a subject between the target region and a region outside the target region along with a retention time in each region, and accurately specify a part of measurement data to be a target of body movement correction.