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Field-of-view limitations in parallel imaging.
Mark A Griswold1, Stephan Kannengiesser, Robin M Heidemann
1Department of Physics EP5, University of Würzburg, Germany. mark@physik.uni-wuerzburg.de
Magnetic Resonance in Medicine
|October 28, 2004
Summary
Generalized autocalibrating partially parallel acquisition (GRAPPA) reconstructs aliased images effectively, unlike sensitivity encoding (SENSE), which fails unless using specific coil sensitivity maps. This highlights key differences in parallel imaging reconstruction methods.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Medical Imaging Technology
Background:
- Parallel imaging accelerates MRI acquisitions, but methods differ in handling aliasing.
- Sensitivity Encoding (SENSE) and Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) are key techniques.
- Aliasing in full Field-of-View (FOV) reconstruction is a critical differentiator.
Purpose of the Study:
- To compare the performance of SENSE and GRAPPA in reconstructing MR images with aliasing.
- To elucidate the reasons behind the differing behaviors of SENSE and GRAPPA regarding aliasing.
- To demonstrate how modified SENSE (mSENSE) can overcome limitations.
Main Methods:
- Illustrative examples and in vivo experiments were used to compare SENSE and GRAPPA.
- Investigated SENSE reconstruction failures with standard sensitivity maps.
- Examined GRAPPA's ability to handle aliasing in reconstructed images.
- Explored the use of aliased high-resolution coil sensitivity maps for accurate SENSE reconstruction.
Main Results:
- SENSE reconstruction fails when the reconstructed FOV is smaller than the imaged object.
- GRAPPA successfully reconstructs images with aliasing, mimicking conventional imaging.
- Modified SENSE (mSENSE) with appropriate coil sensitivity maps enables accurate reconstruction.
- SENSE failures are linked to sensitivity maps not accounting for object size and aliasing.
Conclusions:
- GRAPPA inherently handles aliasing in a predictable manner, similar to non-accelerated scans.
- SENSE requires specific coil sensitivity maps that account for object size and aliasing for accurate reconstruction.
- Understanding these reconstruction differences can reduce operator errors and clarify underlying processes.
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