TRADITIONAL POSTER - ismrm

Poster Sessions
iterative SENSE for reconstruction. Unfortunately this reconstruction is a time consuming process. We demonstrate however that the reconstruction time can
be brought to a clinically acceptable level using commodity graphics hardware (GPUs).
2870. Calibrationless Parallel Imaging Reconstruction by Structured Low-Rank Matrix Completion
Michael Lustig 1,2 , Michael Elad 3 , John Mark Pauly 2
1 Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA, United States; 2 Electrical
Engineering, Stanford University, Stanford, CA, United States; 3 Computer Science, Technion IIT, Haifa, Israel
A new method for parallel imaging that requires no special autocalibration lines or calibration scans is presented. Instead, the method jointly calibrates, and
synthesizes missing data from the entire acquired k-space. The proposed method is based on low-rank matrix completion, which is an extension of the
compressed sensing theory to matrices. It is implemented by iterative singular value thresholding. The method can be used to reconstruct undersampled data,
to generate calibration data for GRAPPA-like methods, or just to improve calibration when the calibration area is too small.
2871. Context Based GRAPPA Reconstruction Using a Small Kernel
Berkay Kanberoglu 1 , Lina J. Karam 1 , Josef P. Debbins 2
1 Electrical Engineering, Arizona State University, Tempe, AZ, United States; 2 Keller Center for Imaging Innovation, Barrow
Neurological Institute, Phoenix, AZ, United States
For GRAPPA reconstruction, large kernel sizes can be disadvantageous in some cases due to the large number of GRAPPA coefficients. A system like this
needs a large number of equations to construct an over-determined system. Small kernel sizes can be advantageous when there is a small number of
equations. Proposed algorithm employs a small kernel size and a clustering method to produce more than one set of GRAPPA weights within a slice.
2872. Sinusoidal Perturbations Improve the Noise Behavior in Parallel EPI
Maximilian Haeberlin 1 , Bertram Wilm 1 , Christoph Barmet 1 , Sebastian Kozerke 1 , Georgios Katsikatsos 1 ,
Klaas Paul Pruessmann 1
1 Department of Electrical Engineering, ETH Zurich, Zurich, Switzerland
Perturbing EPI phase encoding lines in a sinusoidal fashion improves the g-factor map for SENSE reconstruction. Concurrent field monitoring ensures
artifact-free reconstruction for 3-fold undersampled data.
2873. Non-Linear Inversion in Parallel MRI: Considerations on Noise Amplification in the Joint Estimation
of Image and Coil Sensitivities
Julien Sénégas 1 , Martin Uecker 2
1 Philips Research Europe, Hamburg, Germany; 2 Biomedizinische NMR Forschungs GmbH, Göttingen, Germany
Recently, iterative joint estimation algorithms have been proposed to reconstruct aliasing free images and coil sensitivities in a single step from selfcalibrating
sampling trajectories such as Cartesian with variable density. Due to the non-linearity of the reconstruction method, their behavior with respect
to noise amplification is more difficult to predict. In this work, we extend the non-linear inversion algorithm (NLINV) by incorporating the noise covariance
of the coil array in the minimization function and by applying additional regularization for the coil sensitivities, both with the aim of improving the SNR of
the reconstructed image. We present detailed results on the noise amplification properties of this joint reconstruction scheme and evaluate the proposed
algorithm in vivo.
2874. Optimally Regularized GRAPPA/GROWL with Experimental Verifications
Wei Lin 1 , Feng Huang 1 , Hu Cheng 2 , Yu Li 1 , Arne Reykowski 1
1 Advanced Concepts Development, Invivo Corporation, Philips Healthcare, Gainesville, FL, United States; 2 Indiana University,
Bloomington, IN, United States
The performance of GRAPPA-based parallel imaging methods can suffer when the size of the auto-calibration signal (ACS) region becomes small. Based on
an analysis of condition number for GRAPPA calibration equation, an optimal Tikhonov regularization factor is proposed to improve the quality of image
reconstruction. Alternatively, an optimal amount of noise can be added to the ACS data to stabilize the system. The technique was applied to both GRAPPA
and GRAPPA operator for wider radial bands (GROWL), a self-calibrated radial parallel imaging methods. Results show that minimal reconstruction errors
are always obtained with the proposed automatic regularization scheme.
2875. Iterative Approach to Atlas Based Sparsification of Image and Theoretical Estimation (Iterative
ABSINTHE)
Eric Y. Pierre 1 , Nicole Seiberlich 2 , Stephen Yutzy 1 , Vikas Gulani 2 , Felix Breuer 3 , Mark Griswold 2
1 Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; 2 Departments of Radiology, Case Western
Reserve University, Cleveland, OH, United States; 3 Research Center Magnetic Resonance Bavaria e.V., Würzburg, Germany
The ABSINTHE technique has been shown to allow better GRAPPA reconstructions at high undersampling factors by sparsifying the undersampled image
to reconstruct. This study seeks to further increase the effectiveness of ABSINTHE by improving the PCA approximation which generates this sparse image.
After a first standard ABSINTHE estimation, iterative ABSINTHE uses fully-sampled eigenvectors to generate an even sparser representation of the
undersampled data. The efficacy of this technique for simulated data and longitudinal simulations is demonstrated, and an improved image quality is shown
for iterative ABSINTHE in comparison to the standard ABSINTHE and GRAPPA techniques.
2876. Tailored 3D Random Sampling Patterns for Nonlinear Parallel Imaging
Florian Knoll 1 , Christian Clason 2 , Rudolf Stollberger 1
1 Institute of Medical Engineering, Graz University of Technology, Graz, Austria; 2 Institute for Mathematics and Scientific Computing,
University of Graz, Graz, Austria
The idea of randomized 3D Cartesian subsampling was proposed within the framework of compressed sensing. The optimal design of these sampling
patterns is an open problem, especially the determination of the correct ratio of low to high frequency sample points. The goal of this work is to show that it