4D MRI Temporal Basis Extraction for Fetal Motion Artifact Reduction
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Solution Overview
Problem
Conventional MRI systems are limited in their ability to simultaneously visualize anatomical and functional aspects of developing fetuses and placentas, particularly in capturing dynamic movements and functional activities with high spatial and temporal resolution, due to limitations in frame rates and the inability to differentiate active from inactive brain areas, which hinders clinical diagnostics.
Innovation Solution
A 4D MRI system and method that combines spatially encoded data collection with direct extraction of temporal basis functions and iterative calculation of coefficient images, allowing for the generation of 4D images that provide both structural and functional visualization of tissues with high frame rates, enabling simultaneous assessment of fetal and placental development, morphology, and functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MRI sequences are used to achieve high spatial resolution, then anatomical visualization is improved, but scan time increases and temporal resolution deteriorates
Solution Approach 1:
The patent segments the imaging process into multiple undersampled k-space measurements acquired at different time points, allowing parallel processing and reconstruction of multiple frames from a single scan session. This segmentation enables high spatial resolution for each frame while reducing the total scan time through efficient data utilization
Solution Approach 2:
The system employs periodic undersampled k-space measurements acquired at regular time intervals, creating a time-resolved sequence of measurements that can be reconstructed into multiple frames. This periodic sampling approach maintains high spatial resolution while achieving high frame rates through the temporal structure of the acquisitions
2Speed
If conventional MRI is used to capture dynamic fetal movements, then temporal resolution is improved, but spatial resolution and image quality deteriorate due to motion artifacts
Solution Approach 1:
The system uses a low-rank model that incorporates temporal correlations across frames as a form of feedback constraint during reconstruction. This model leverages the fact that consecutive frames are highly similar, using this temporal redundancy to suppress motion artifacts and maintain image quality even at high frame rates where fetal movements occur
Solution Approach 2:
The patent changes the imaging parameters by using undersampled k-space measurements with specific sampling patterns that are optimized for dynamic imaging. By adjusting the sampling rate and pattern along with the low-rank reconstruction parameters, the system achieves high frame rates while maintaining image quality through mathematical constraints that compensate for motion
3Loss of information
If fMRI is used to evaluate brain functional activity, then functional information is improved, but scan time increases significantly
Solution Approach 1:
The system applies partial sampling in k-space combined with low-rank reconstruction, acquiring only a subset of the full k-space data at each time point. This partial action approach captures sufficient functional information through the temporal correlations, significantly reducing scan time while maintaining the ability to evaluate brain functional activity
Solution Approach 2:
The low-rank reconstruction framework serves multiple functions simultaneously: it enables high frame rate imaging, maintains high spatial resolution, and provides functional information through temporal analysis. This multi-functional approach allows a single scan to address both anatomical and functional evaluation needs without requiring separate dedicated scans
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
The system achieves high spatial and temporal resolution, allowing for the imaging of multiple fetuses and placentas with uncorrelated motions, reducing artifacts from motion and enabling the evaluation of internal dynamics and tissue responses to external changes, thus overcoming the limitations of conventional MRI in fetal imaging.
Implementation Method 1
Magnetic Resonance Imaging (MRI)... collecting spatially encoded data from a subject using an MRI system
Implementation Method 2
directly extracting a number of temporal basis functions using at least a first portion of the spatially encoded data... iteratively calculating a number of coefficient images using the number of temporal basis functions and at least a second portion of the spatially encoded data
Data Source
AI summary
A magnetic resonance imaging method is includes collecting spatially encoded data from a subject using an MRI system, and directly extracting a number of temporal basis functions using at least a first portion of the spatially encoded data. The method further includes, after directly extracting the number of temporal basis functions, iteratively calculating a number of coefficient images using the number of temporal basis functions and at least a second portion of the spatially encoded data. Finally, the method includes generating a 4D image based on the number of temporal basis functions and the number of coefficient images.