MRI Motion Correction via Sensor-Based K-Space Data Filtering
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Solution Overview
Problem
Existing MRI techniques struggle to effectively correct for body motions other than respiration, leading to image quality deterioration due to incomplete data exclusion and potential artifacts in high-speed imaging.
Innovation Solution
An MRI system equipped with a sensor capable of detecting various body motions, analyzing the spatial and temporal characteristics of these motions, and adjusting data collection and image reconstruction processes accordingly to minimize motion-induced artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data collection is performed in high-speed imaging with acceleration rate, then imaging speed is improved, but image quality deteriorates due to body motion artifacts
Solution Approach 1:
The system performs preliminary detection of body motion characteristics before image reconstruction, analyzing temporal and spatial patterns of motion to predict which k-space data will be affected by artifacts, allowing proactive adjustment of data selection criteria
Solution Approach 2:
The system uses feedback from body motion detection sensors to continuously adjust data selection during high-speed imaging, comparing detected motion characteristics with k-space data acquisition status to dynamically determine which data to exclude or prioritize in reconstruction
2Object-affected harmful factors
If body motion data is excluded from k-space data, then influence of body motion is reduced, but image quality deteriorates due to insufficient data for reconstruction
Solution Approach 1:
The system changes parameters of k-space data selection based on detected body motion characteristics, adjusting which regions of k-space are excluded or prioritized depending on the temporal and spatial pattern of motion, rather than uniformly excluding all data acquired during motion periods
Solution Approach 2:
The system selectively excludes only the specific k-space data that corresponds to periods of significant body motion, while retaining and prioritizing data from stable periods, using partial exclusion rather than complete data rejection to maintain sufficient data for reconstruction
3Object-affected harmful factors
If respiratory motion detection is used to exclude body motion data, then respiration-related artifacts are reduced, but other body motions cause image quality deterioration
Solution Approach 1:
The system uses a universal body motion detection approach that can detect and analyze multiple types of body motions (respiration, cardiac, voluntary movement) using the same sensor and analysis framework, making the system adaptable to various motion types rather than being specialized for only respiratory motion
4Manufacturing precision
If k-space data is collected from low-frequency to high-frequency domain, then low-frequency data is obtained first, but high-frequency data collection is vulnerable to body motion artifacts
Solution Approach 1:
The system performs preliminary detection and analysis of body motion characteristics during the low-frequency data collection phase, using this information to predict and prepare for potential motion artifacts during subsequent high-frequency data collection
Solution Approach 2:
The system uses feedback from continuous body motion monitoring to dynamically adjust data acquisition priorities, reducing or pausing high-frequency data collection when motion is detected while maintaining low-frequency data collection that is less susceptible to motion artifacts
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for targeted and effective correction of body motions, reducing image quality degradation and preventing artifacts associated with incomplete data exclusion, thereby producing high-quality images.
Implementation Method 1
a sensor capable of detecting not only a respiratory motion but also general body motions
Implementation Method 2
a measurement unit configured to measure a nuclear magnetic resonance signal of a subject
Data Source
AI summary
Appropriate processing is executed in a method for excluding body motion data and image reconstruction according to a type and a characteristic of a body motion, so as to reduce an influence of the body motion, and prevent deterioration of image quality caused by exclusion of data generated during the body motion. An MRI apparatus includes a processing determination unit that collects k-space data and acquires body motion information from a sensor capable of detecting not only a respiratory motion but also general body motions, analyzes the body motion information obtained by the sensor, and branches and executes processing for subsequent data collection and image reconstruction according to the analysis result. The MRI apparatus determines, based on a temporal characteristic such as a duration and a frequency, and a spatial characteristic of the body motion, particularly a generation pattern in a k-space, body motion data to be excluded, and executes image reconstruction suitable for k-space data after exclusion of the body motion data.