MRI Gradient Coil Regridding via Phase Difference Feedback
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Solution Overview
Problem
Conventional regridding processing in MRI systems for high-speed imaging techniques like EPI does not achieve optimal accuracy, leading to suboptimal image quality due to the non-linear gradient magnetic field in the readout direction, which results in unevenly spaced sampled data in k-space.
Innovation Solution
The MRI apparatus employs a method involving multiple template scans to calculate phase difference data and accurately reproduce the gradient magnetic field waveform, allowing for precise regridding of k-space data to achieve evenly spaced sampling, thereby improving image reconstruction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional regridding processing is used in EPI, then data acquisition time is reduced, but image reconstruction accuracy deteriorates due to non-linear gradient magnetic field causing unevenly spaced sampled data in k-space
Solution Approach 1:
The system performs template scans to measure the actual gradient magnetic field waveform, then uses this measured waveform as feedback to correct the regridding process. The measured gradient waveform information is fed back into the reconstruction algorithm to achieve accurate resampling despite non-linear gradient effects, resolving the contradiction between fast acquisition and accurate reconstruction.
Solution Approach 2:
The system performs template scans before the main EPI acquisition to preliminarily characterize the gradient magnetic field waveform. This preliminary measurement of the gradient waveform allows the subsequent regridding process to be accurately corrected, preparing the necessary correction data in advance to maintain reconstruction accuracy during fast imaging.
2Speed
If gradient magnetic field pulse width is shortened for high speed imaging, then imaging speed is improved, but the ratio of rising edge and falling edge regions increases causing greater non-linearity in the gradient waveform
Solution Approach 1:
The system uses template scans to measure the actual gradient waveform including rising and falling edge regions, then feeds this information back to correct the k-space sampling positions. This feedback mechanism compensates for the non-linearities introduced by short pulse widths and prominent edge regions, maintaining manufacturing precision despite high-speed operation.
Solution Approach 2:
The system changes the sampling strategy from uniform time-based sampling to non-uniform sampling based on the measured gradient waveform parameters. By adjusting sampling positions according to the actual gradient waveform characteristics (including rising/falling edge durations), the system maintains accurate k-space sampling despite shortened pulse widths and increased edge region ratios.
3Loss of time
If Ramp Sampling is used to sample data in rising edge and falling edge regions, then data acquisition time is reduced, but sampled data become unevenly spaced in k-space requiring complex regridding
Solution Approach 1:
The system uses template scan measurements of the gradient waveform as feedback to determine the exact sampling positions during Ramp Sampling. This feedback information about the actual gradient waveform characteristics allows for accurate calculation of k-space positions, simplifying the regridding process by providing precise mapping information rather than requiring complex iterative corrections.
Solution Approach 2:
The system performs preliminary template scans to characterize the gradient waveform and calculate the appropriate sampling positions before the main EPI acquisition. This preliminary calculation of sampling positions based on measured gradient parameters reduces the complexity of subsequent regridding by pre-determining the correct k-space mapping, rather than requiring complex real-time adjustments.
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 enhances the accuracy of regridding processing, leading to improved image quality by ensuring that sampled data are evenly spaced in k-space, even in regions with non-linear gradient magnetic field intensity, without extending imaging time.
Implementation Method 1
A gradient magnetic field pulse is generated by applying a pulse electric current to a gradient coil
Implementation Method 2
MRI is an imaging method which magnetically excites nuclear spin of an object (a patient) placed in a static magnetic field with an RF pulse having the Larmor frequency and reconstructs an image on the basis of MR signals generated due to the excitation
Data Source
AI summary
According to one embodiment, an MRI apparatus includes a gradient coil, an RF coil, an RF receiver, and processing circuitry which controls these components to perform each pulse sequence. The processing circuitry sets a main-scan pulse sequence, a first pulse sequence which includes application of a gradient magnetic field in a readout direction, and a second pulse sequence which includes application of the gradient magnetic field in a readout direction, and whose acquisition region is shifted from the first pulse sequence. The processing circuitry reconstructs image data of the main scan, based on magnetic resonance signals acquired by the main-scan pulse sequence and phase difference data in the readout direction between first k-space data generated from the magnetic resonance signals acquired by the first pulse sequence and second k-space data generated from the magnetic resonance signals acquired by the second pulse sequence.