MR k-space Sampling Segmentation to Reduce Artifacts
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Solution Overview
Problem
Segmented acquisition techniques in magnetic resonance imaging, such as the RESOLVE sequence, are susceptible to phase inconsistencies, leading to artifacts like ringing and grid-like mesh artifacts when partial Fourier techniques are used.
Innovation Solution
A method that acquires incomplete measurement data sets with varying partial factors to minimize unsampled k-space regions, allowing for the creation of a combined data set that supplements missing data using techniques like zero-filling or POCS algorithms to avoid artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If segmented acquisition techniques with partial Fourier methods are used, then acquisition time is reduced, but artifacts like ringing and grid-like mesh artifacts occur due to phase inconsistencies
Solution Approach 1:
The k-space data acquisition is divided into multiple segments with different partial factors. Each segment acquires incomplete data according to a specific sampling pattern, and the segments are combined to form complete k-space data. This segmentation allows acceleration while maintaining completeness through coordinated sampling across segments.
Solution Approach 2:
Each individual measurement data set acquires only partial k-space data (partial Fourier), but the combination of multiple such partial data sets provides complete k-space coverage. This partial action approach enables time savings in each acquisition while achieving full data completeness through aggregation.
2Manufacturing precision
If multiple measurement data sets with varying partial factors are acquired, then complete k-space data is achieved, but acquisition time increases
Solution Approach 1:
The patent dynamically varies the partial factor across different measurement data sets. Instead of using a fixed partial Fourier approach, the sampling pattern changes between acquisitions to ensure that the union of all acquired data covers the complete k-space. This dynamic adaptation optimizes the balance between acquisition speed and data completeness.
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 reduces acquisition time and minimizes artifacts in MR images by ensuring complete k-space data acquisition, improving image quality and signal-to-noise ratio.
Implementation Method 1
the examination object is positioned for this purpose in a comparatively strong static, homogeneous basic magnetic field, also called a B0 field
Implementation Method 2
radio-frequency excitation pulses (RF pulses) are irradiated into the examination object, the resolved nuclear spin resonances are measured
Implementation Method 3
the basic magnetic field is overlaid with fast-switched magnetic gradient fields, called gradients for short
Implementation Method 4
An associated MR image can be reconstructed, for example by means of a multi-dimensional Fourier transform, from the k-space matrix occupied by values
Data Source
AI summary
In a method for avoiding artifacts during acquisition of MR data, a first measurement data set (MDS) of a target region of the examination object and at least one second MDS of the target region are acquired, and a combined MDS is created based on the acquired data sets. The first MDS does not sample a first region of k-space to be sampled according to Nyquist and corresponding to a first partial factor, and a second MDS does not sample a second region of k-space to be sampled according to Nyquist and corresponding to a second partial factor. The first and second regions of the k-space are different from each other. Advantageously, a k-space region acquired in none of the acquisitions made can be minimized by the inventive variation in the respective sampling pattern of the acquired MDS, so artifacts are reduced/avoided in MR images reconstructed from the MDS.