MRI K-Space Sampling With Calibration Lines for Motion Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing magnetic resonance imaging (MRI) techniques face challenges in efficiently correcting for patient motion during data acquisition, particularly with distributed reordering schemes like 'checkered', which lead to severe motion artefacts and computational inefficiencies, making them unsuitable for clinical applications.
Innovation Solution
A method that combines linear sampling with additional calibration k-space lines, primarily in the central region, to facilitate robust and fast-converging retrospective motion correction, minimizing artefacts and computation time, while maintaining image quality and spatial resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distributed reordering schemes like 'checkered' are used for k-space sampling, then motion estimation capability is improved, but motion artefacts increase severely and computational efficiency decreases
Solution Approach 1:
The patent segments the k-space sampling into two distinct parts: calibration lines sampled in every shot for motion estimation, and imaging lines sampled in a distributed manner for image acquisition. This segmentation allows the calibration lines to provide consistent reference data for motion tracking while the imaging lines maintain the distributed sampling benefits, thereby reducing motion artifacts compared to fully distributed schemes.
Solution Approach 2:
The patent performs preliminary action by acquiring calibration k-space lines at the beginning of each shot before the main imaging acquisition. These calibration lines are used to estimate motion parameters that are then applied to correct the subsequent imaging data, allowing motion correction to be prepared in advance rather than requiring complex post-processing of fully distributed samples.
2Measurement precision
If distributed reordering schemes like 'checkered' are used for k-space sampling, then motion estimation capability is improved, but computation time increases excessively
Solution Approach 1:
The patent segments the data processing into two separate steps: first estimating motion parameters using only the calibration lines from each shot, then reconstructing the image using the corrected imaging lines. This segmentation avoids the computationally expensive joint optimization required by fully distributed schemes, reducing computation time to clinically acceptable levels while maintaining motion estimation capability.
Solution Approach 2:
The patent uses partial action by sampling only a subset of k-space lines (calibration lines) in every shot dedicated to motion estimation, rather than using all k-space samples for motion correction. This partial sampling approach provides sufficient motion information while significantly reducing the computational burden compared to using the full distributed dataset for motion estimation.
3Measurement precision
If additional calibration k-space lines are acquired in each shot, then motion correction accuracy is improved, but scan time increases
Solution Approach 1:
The patent applies partial action by acquiring only a limited number of calibration k-space lines in each shot rather than sampling the entire k-space. These partial calibration samples provide sufficient information for accurate motion estimation while minimizing the additional scan time, achieving a practical balance between motion correction accuracy and total acquisition duration.
Solution Approach 2:
The patent performs preliminary action by acquiring calibration lines at the beginning of each shot before the main imaging sequence. This preliminary calibration allows motion parameters to be estimated early, and these parameters are then used to correct the subsequent imaging data, ensuring accurate motion correction without requiring extensive additional scan time throughout the sequence.
4Productivity
If linear sampling is used without additional calibration lines, then scan time is reduced, but motion correction robustness decreases
Solution Approach 1:
The patent segments the k-space sampling into calibration lines and imaging lines, where calibration lines are sampled in every shot using linear ordering for robust motion tracking, while imaging lines use efficient sampling patterns. This segmentation ensures that motion correction robustness is maintained through consistent calibration sampling without significantly impacting overall scan efficiency.
Solution Approach 2:
The patent performs preliminary action by acquiring calibration lines at the beginning of each shot to establish motion reference data before the main imaging acquisition. This preliminary calibration ensures that reliable motion parameters are available for correction, improving motion correction robustness while keeping the additional time requirement minimal and confined to the preliminary calibration phase only.
Data Source
AI summary
A method for acquiring a magnetic resonance image dataset of an object includes using an imaging protocol in which a number of k-space lines are acquired in one shot. The imaging protocol includes a plurality of shots. A plurality of additional k-space lines are acquired in at least a subset of the shots, such that movement of the object is detected throughout the imaging protocol. A method for generating a motion-corrected magnetic resonance image dataset from the dataset thus acquired, a magnetic resonance imaging apparatus, and a computer program are also provided.