SoftwareESPIRiT: Programming Library and Software Toolbox for Compressed Sensing and Parallel ImagingA collection of reconstruction algorithms and tools with efficient implementations. Written by Martin Uecker, Patrick Virtue, Frank Ong, Mark J. Murphy and Marcus T. Alley. The library includes implementation of the ESPIRiT, and eigen-value based robust parallel imaging. The high complexity of advanced algorithms presents challenges for research and clinical application of new reconstructionmethods. While researchers need flexible and interactive tools, clinical evaluation and application require robust and highly efficient implementations. Here, we present a framework for image reconstruction, which consists of a programming library and a toolbox of command-line programs. The library provides common operations on multi-dimensional arrays, Fourier and wavelet transforms, as well as generic implementations of selected iterative optimization algorithms. The command-line tools provide direct access to basic operations on multi-dimensional arrays as well as efficient implementations of selected iterative reconstruction algorithms. Sparse MRISparseMRI is a collection of Matlab functions that implement the algorithms and examples described in the paper M. Lustig, D.L Donoho and J.M Pauly “Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging” Magnetic Resonance in Medicine, 2007 Dec; 58(6):1182-1195. And in the high-level, non-expert overview M. Lustig, D.L Donoho, J.M Santos and J.M Pauly “Compressed Sensing MRI”, IEEE Signal Processing Magazine, 2008; 25(2): 72-82
Time Optimal Gradient DesignAn implementation of the algorithms and examples described in the paper M. Lustig S-J Kim and J.M Pauly, “A Fast Method for Designing Time- Optimal Gradient Waveforms for Arbitrary k-Space Trajectories”, Transactions on Medical Imag- ing, 2008; 27(6): 866-873 The following is an improved method based on: S. Vaziri and M. Lustig “The Fastest Gradient Waveforms” which was accepeted for presentation at the annual Meeting of the ISMRM, 2012. The project was funded by the SRC Program and by an undergraduate research grant from Intel.
SPIRiT: iTerative Self Consistent Parallel Imaging Reconstruction from Arbitrary k-space SamplingThis code is a reference to the paper, M. Lustig and J. Pauly “SPIRiT: Iterative Self-Consistent Parallel Imaging Reconstruction from Arbitrary k-Space Sampling” which is now published in Magnetic Resonance in Medicine early-view (Early View, Preprint).
Nonrigid Motion Correction in 3D using Autofocussing and Buttefly NavigatorsPatient motion is a serious problem in MRI, and in particular when imaging pediatric patients. Butterfly navigators are modifications to the regular 2D/3DFT pulse sequence and allow collection of navigation information during the prewinder stage of the readout. In this work we use the navigators along with multi-channel array and autofocussing image criteria to correct for non-rigid motion in body MRI of pediatric patients. The following code was developed by Joseph Cheng and accompanies the paper: Cheng JY, Alley MT, Cunningham CH, Vasanawala SS, Pauly JM, Lustig M. “Nonrigid Motion Correction in 3D Using Autofocusing with Localized Linear Translations,” Magnetic Resonance in Medicine 2012.
Coil Compression for Accelerated Imaging with Cartesian SamplingCoil arrays are used to accelerate the acquisition of MRI by exploiting the spatial sensitivity of the coils for spatial encoding. The increasing number of channels in systems today provides better acceleration, but at the same time results in significant increase in computation time. This in particularly a problem in iterative reconstructions. In this work we exploit redundancy between the channels and the fact that the readout dimension in Cartesian imaging is never subsampled to compress the coils data into MUCH fewer virtual coils. The software provided here is a Matlab protoype developed by Tao Zhang. It is the implementation of the Technique described in Zhang T, Pauly JM, Vasanawala SS, Lustig M. “Coil Compression for Accelerated Imaging with Cartesian Sampling,” Magnetic Resonance in Medicine 2012: Early View..
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