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Reconstruction of undersampled radial PatLoc imaging using total generalized variation
Florian Knoll1, Gerrit Schultz, Kristian Bredies
1Institute of Medical Engineering, Graz University of Technology, Kronesgasse 5, A-8010 Graz, Austria. florian.knoll@tugraz.at
Magnetic Resonance in Medicine
|August 1, 2012
Summary
A new iterative reconstruction method using total generalized variation significantly reduces star-shaped artifacts in undersampled radial imaging. This advanced technique improves image quality in parallel imaging with nonlinear spatial encoding fields.
Area of Science:
- Medical Imaging
- Image Reconstruction
- Magnetic Resonance Imaging (MRI)
Background:
- Radial imaging with nonlinear spatial encoding fields can produce star-shaped artifacts when undersampled.
- These artifacts degrade image quality in parallel imaging techniques like PatLoc (Positioning and Tracking Localization).
Purpose of the Study:
- To introduce a novel iterative reconstruction method to reduce star-shaped artifacts in undersampled radial imaging.
- To enhance image quality and reduce computational time for PatLoc reconstruction.
Main Methods:
- Developed an iterative reconstruction method based on total generalized variation (TGV).
- Implemented a sampling operator using a type-3 nonuniform fast Fourier transform (NUFFT), combining type-1 and type-2 NUFFTs.
- Utilized the sampling operator for an iterative conjugate gradient SENSE-based method for PatLoc reconstruction.
Main Results:
- The TGV-based method effectively reduces prominent star-shaped artifacts.
- Significant improvements in image quality were observed even with highly undersampled data (16 radial projections).
- The conjugate gradient SENSE method demonstrated a substantial reduction in computation time compared to conventional PatLoc methods.
Conclusions:
- The proposed TGV-based iterative reconstruction is a powerful tool for artifact reduction in undersampled radial MRI.
- This method offers improved image quality and computational efficiency for PatLoc imaging.
- The approach is validated through numerical simulations and in vivo measurements.
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