MRI K-space Equal Interval Sampling for Time-Series Image Quality
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Solution Overview
Problem
Current magnetic resonance imaging (MRI) techniques using under-sampled data acquisition face challenges in achieving high-quality time-series images due to aliasing artifacts caused by unevenly spaced sample points in k-space, which degrade image quality.
Innovation Solution
A magnetic resonance imaging apparatus and method that performs under-sampled data acquisition with sample points at equal intervals in k-space, generates multiple k-space frames with varying time resolutions, and integrates these frames to produce time-series images using a machine-learning model to reduce signal loss and aliasing artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If under-sampled data acquisition is performed with unevenly spaced sample points in k-space, then data acquisition speed is improved, but image quality deteriorates due to aliasing artifacts
Solution Approach 1:
The patent segments the k-space data acquisition into multiple frames with different temporal resolutions. By dividing the acquisition into separate time points (e.g., first frame at time t1, second frame at time t2), the system can apply different sampling strategies to each segment, reducing aliasing artifacts while maintaining accelerated acquisition speed.
Solution Approach 2:
The patent changes the sampling interval parameter in k-space from uneven spacing to equal spacing. By setting uniform intervals between sample points across different frames, the mathematical reconstruction process can more effectively suppress aliasing components, thereby improving image quality while preserving the benefits of under-sampling.
2Loss of time
If under-sampled data acquisition is performed, then scanning time is reduced, but aliasing components increase and degrade image quality
Solution Approach 1:
The patent employs periodic sampling across multiple frames where sample points are systematically positioned at equal intervals in each frame. This periodic structure in the temporal domain allows reconstruction algorithms to distinguish between true signal and aliasing components, reducing harmful artifacts while maintaining reduced scanning time.
Solution Approach 2:
The patent creates multiple copies of the k-space sampling pattern across different time frames. By acquiring replicated data sets at equal intervals in each frame and combining them through reconstruction, the system can suppress aliasing components that appear as inconsistent patterns across the copied frames, thereby reducing harmful artifacts.
3Manufacturing precision
If sample points are located at equal intervals in k-space across multiple frames, then image quality is improved by suppressing aliasing, but data processing complexity increases
Solution Approach 1:
The patent creates a universal sampling pattern that functions effectively across multiple frames and different reconstruction scenarios. The equal-interval sampling approach serves multiple purposes: it suppresses aliasing, enables efficient FFT-based reconstruction, and works with various acceleration factors, thereby managing processing complexity through a multi-functional design.
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 improves image quality by suppressing aliasing components and enhancing the resolution of time-series images, resulting in high-definition images with reduced artifacts from under-sampled data acquisition.
Implementation Method 1
Magnetic resonance imaging apparatus and method
Data Source
AI summary
According to one embodiment, a magnetic resonance imaging apparatus includes sequence control circuitry and processing circuitry. The sequence control circuitry performs under-sampled data acquisition whose sample points are located at an equal interval in k-space and acquires k-space frames. The processing circuitry generates a plurality of k-space frames related to a plurality of time resolutions based on the k-space frames. In each of the plurality of k-space frames, the sample points are located at an equal interval, and the interval differs for each of the plurality of k-space frames. The processing circuitry generates a time-series image based on the plurality of k-space frames.