SpiralReco

Reconstruction package for model-based reconstruction of accelerated 3D stack-of-spirals data.

Features

• GIRF correction
• Density compensation function calculation
• easily switch NUFFT algorithms
  • 2D/3D CPU (from MIRT toolbox)
  • 3D GPU (from gpuNUFFT)
• B0 correction with time/frequency segmentation
• Parallel imaging reconstruction
  • CGSENSE
  • SPIRIT (not tested well)
• B0 map preprocessing functions
  • spatial/temporal unwrap
  • iterative denoising of field maps
• Nifti creation

Installation

For Basic setup

cd(userpath)
!git clone --depth=1 https://github.com/pehses/mapVBVD.git
!git clone --depth=1 https://github.com/praveenivp/SpiralReco.git
addpath(fullfile(pwd,'mapVBVD'))
addpath(genpath(fullfile(pwd,'SpiralReco')))

The package also can integrate with gpuNUFFT. Refer here for additional information. Furthermore, BART was used for coil sensitivity estimation is not included.

Usage

Refer to demos

• demo 1 [matlab livescript],[PDF]
  • Demonstrates features of this package with 3D phantom data.
• demo 2 [matlab livescript],[PDF]
  • Demonstrates features of this package with simulated data.

The Documentation I used for HPC reconstruction and post-processing can be found here.

known issues

• GPU NUFFT and undersampling along two direction has problems.
• more to come

Acknowledgements

This package has unmodified/modified code from other open-source packages.

• CPU NUFFT functions are from MIRT toolbox by Jeff Fessler and his group.
• Trajectory calculation are from spiraltraj by Philipp Ehses and Miki Lustig.
• gpuNUFFT functions are from gpuNUFFT.
• SPIRIT3D related functions are adapted from ESPIRIT package by Miki Lustig.
• Small parts from GIRF and ismrm_sunrise_matlab
• coding styles along with some snippets from Philipp Ehses and Miki Lustig.
• more to come

References

Please cite the people who developed all these nice methods. Some are listed here.

1. Fessler JA, Sutton BP. Nonuniform fast fourier transforms using min-max interpolation. IEEE Transactions on Signal Processing. 2003;51(2):560-574. doi:10.1109/TSP.2002.807005

2. Sutton BP, Noll DC, Fessler JA. Fast, iterative image reconstruction for MRI in the presence of field inhomogeneities. IEEE Transactions on Medical Imaging. 2003;22(2):178-188. doi:10.1109/TMI.2002.808360

3. Man LC, Pauly JM, Macovski A. Multifrequency interpolation for fast off-resonance correction. Magnetic Resonance in Medicine. 1997;37(5):785-792. doi:10.1002/mrm.1910370523

4. Pruessmann KP, Weiger M, Börnert P, Boesiger P. Advances in sensitivity encoding with arbitrary k-space trajectories. Magnetic Resonance in Medicine. 2001;46(4):638-651. doi:10.1002/mrm.1241

5. Funai AK, Fessler JA, Yeo DTB, Noll DC, Olafsson VT. Regularized field map estimation in MRI. IEEE Transactions on Medical Imaging. 2008;27(10):1484-1494. doi:10.1109/TMI.2008.923956

6. Lustig M, Kim SJ, Pauly JM. A fast method for designing time-optimal gradient waveforms for arbitrary k-space trajectories. IEEE Transactions on Medical Imaging. 2008;27(6):866-873. doi:10.1109/TMI.2008.922699

7. Vannesjo SJ, Graedel NN, Kasper L, et al. Image reconstruction using a gradient impulse response model for trajectory prediction. Magnetic Resonance in Medicine. 2016;76(1):45-58. doi:10.1002/mrm.25841

8. Robson PM, Grant AK, Madhuranthakam AJ, Lattanzi R, Sodickson DK, McKenzie CA. Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions. Magnetic Resonance in Medicine.