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Optimal gradient waveform design for projection imaging and projection reconstruction echoplanar spectroscopic
1Center for Functional Imaging, University of California, Berkeley, USA.
Magnetic Resonance in Medicine
|May 20, 1999
Summary
New magnetic resonance imaging (MRI) and spectroscopic imaging (MRSI) techniques use modulated gradient waveforms to optimize k-space sampling. This improves signal-to-noise ratio and reduces data acquisition time for better image reconstruction.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Magnetic Resonance Spectroscopic Imaging (MRSI)
- Medical Imaging Physics
Background:
- k-space sampling density is crucial for image quality in MRI and MRSI.
- Reconstruction window functions are used to mitigate artifacts like k-space truncation.
- Optimizing sampling density to match reconstruction filters can enhance signal-to-noise ratio (SNR).
Purpose of the Study:
- To propose modulated B0 projection gradient waveforms for MRI and MRSI.
- To shape k-space sampling density to match reconstruction window functions.
- To improve SNR and reduce data acquisition time efficiently.
Main Methods:
- Developed a nonlinear constrained optimization (NLCO) method to design gradient waveforms.
- Minimized reconstruction noise variance subject to gradient magnitude and slew rate constraints.
- Investigated 2D and 3D cases, including twisting projection trajectories.
Main Results:
- Demonstrated that modulated B0 projection waveforms can match k-space sampling to reconstruction windows.
- NLCO effectively minimizes noise variance and can optimize trajectory twisting for faster acquisition.
- Simulations for 1H MRSI showed potential advantages of the new sampling schemes.
Conclusions:
- Modulated B0 projection gradient waveforms offer a novel approach for optimizing MRI/MRSI sampling.
- NLCO provides a robust method for designing these waveforms, balancing SNR and acquisition speed.
- The proposed techniques have potential for improving clinical MRI and MRSI.