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Auto-calibration approach for k-t SENSE.
Irene P Ponce1, Martin Blaimer, Felix A Breuer
1Department of Experimental Physics 5, University of Würzburg, Würzburg, Germany.
Magnetic Resonance in Medicine
|April 5, 2013
Summary
This study introduces auto-calibrated k-t SENSE, improving spatial resolution in dynamic imaging. This method enhances temporal fidelity without increasing scan times, offering high-quality reconstructions.
Area of Science:
- Medical Imaging
- Magnetic Resonance Imaging (MRI)
- Image Reconstruction
Background:
- k-t SENSE enables high-quality dynamic imaging at accelerated rates.
- Low-resolution training data in k-t SENSE can lead to temporal filtering artifacts.
Purpose of the Study:
- To enhance the spatial resolution of training data for k-t SENSE.
- To improve dynamic image reconstruction without sacrificing temporal resolution or acquisition time.
Main Methods:
- Implemented a feedback regularization approach for k-t SENSE auto-calibration.
- Generated full-resolution training data from accelerated data using TSENSE reconstruction.
- Evaluated temporal filtering using modulation transfer function and noise via Monte-Carlo simulations.
Main Results:
- Auto-calibrated k-t SENSE demonstrated improved temporal fidelity compared to standard k-t SENSE.
- Computer simulations and cardiac imaging experiments validated the approach.
Conclusions:
- Auto-calibrated k-t SENSE offers superior reconstruction quality for dynamic imaging.
- This method addresses limitations of standard k-t SENSE in dynamic MRI.
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