PROMISE: Parallel‐imaging and compressed‐sensing reconstruction of multicontrast imaging using SharablE information

A typical clinical MR examination includes multiple scans to acquire images with different contrasts for complementary diagnostic information. The multicontrast scheme requires long scanning time. The combination of partially parallel imaging and compressed sensing (CS‐PPI) has been used to reconstruct accelerated scans. However, there are several unsolved problems in existing methods. The target of this work is to improve existing CS‐PPI methods for multicontrast imaging, especially for two‐dimensional imaging.

[1]  Robin M Heidemann,et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA) , 2002, Magnetic resonance in medicine.

[2]  Simon Bauer,et al.  Increasing efficiency of parallel imaging for 2D multislice acquisitions , 2009, Magnetic resonance in medicine.

[3]  Dong Liang,et al.  k-t CSPI: A dynamic MRI reconstruction framework for combining compressed sensing and parallel imaging , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).

[4]  P. Boesiger,et al.  SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.

[5]  Bernhard Schölkopf,et al.  Optimization of k‐space trajectories for compressed sensing by Bayesian experimental design , 2010, Magnetic resonance in medicine.

[6]  Roland Bammer,et al.  Diffusion tensor imaging using single‐shot SENSE‐EPI , 2002, Magnetic resonance in medicine.

[7]  D. Donoho,et al.  SPIR-iT : Autocalibrating Parallel Imaging Compressed Sensing , 2008 .

[8]  Zhi-Pei Liang,et al.  Anatomically constrained reconstruction from noisy data , 2008, Magnetic resonance in medicine.

[9]  Yu Li,et al.  Correlation imaging for multiscan MRI with parallel data acquisition , 2012, Magnetic resonance in medicine.

[10]  Henk Koop.  The Tree Model , 1989 .

[11]  Gunilla Borgefors,et al.  Distance transformations in digital images , 1986, Comput. Vis. Graph. Image Process..

[12]  D. Donoho,et al.  Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.

[13]  K. T. Block,et al.  Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint , 2007, Magnetic resonance in medicine.

[14]  Arne Reykowski,et al.  GRAPPA operator for wider radial bands (GROWL) with optimally regularized self‐calibration , 2010, Magnetic resonance in medicine.

[15]  Vivek K Goyal,et al.  Multi‐contrast reconstruction with Bayesian compressed sensing , 2011, Magnetic resonance in medicine.

[16]  Norbert Schuff,et al.  Improved diffusion imaging through SNR‐enhancing joint reconstruction , 2013, Magnetic resonance in medicine.

[17]  M. Jacob,et al.  Optimal Sampling of k-Space with Cartesian Grids for Parallel MR Imaging , 1999 .

[18]  H. Carr,et al.  The Principles of Nuclear Magnetism , 1961 .

[19]  Peter Kellman,et al.  Dynamic autocalibrated parallel imaging using temporal GRAPPA (TGRAPPA) , 2005, Magnetic resonance in medicine.

[20]  Jeff A. Bilmes,et al.  A gentle tutorial of the em algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models , 1998 .

[21]  Leslie Ying,et al.  Accelerating SENSE using distributed compressed sensing , 2009 .

[22]  L. Ying,et al.  Accelerating SENSE using compressed sensing , 2009, Magnetic resonance in medicine.

[23]  Robert D. Nowak,et al.  Wavelet-based statistical signal processing using hidden Markov models , 1998, IEEE Trans. Signal Process..

[24]  Richard G. Baraniuk,et al.  Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[25]  F. Sebert,et al.  SparseSENSE: Randomly-Sampled Parallel Imaging using Compressed Sensing , 2007 .

[26]  Suyash P. Awate,et al.  Computer Vision, Graphics, and Image Processing , 2016, Lecture Notes in Computer Science.

[27]  Matthias F. Mueller,et al.  Parallel magnetic resonance imaging using the GRAPPA operator formalism , 2005, Magnetic resonance in medicine.

[28]  David Atkinson,et al.  Beyond the g‐factor limit in sensitivity encoding using joint histogram entropy , 2006, Magnetic resonance in medicine.

[29]  Chun Yuan,et al.  A New Designed 36-Channel Neurovascular Coil at 3 T , 2011 .

[30]  Wei Lin,et al.  A rapid and robust numerical algorithm for sensitivity encoding with sparsity constraints: Self‐feeding sparse SENSE , 2010, Magnetic resonance in medicine.

[31]  M. Lustig,et al.  SPIRiT: Iterative self‐consistent parallel imaging reconstruction from arbitrary k‐space , 2010, Magnetic resonance in medicine.