Sparsity adaptive reconstruction for highly accelerated cardiac MRI
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Philip Schniter | Ning Jin | Chong Chen | Rizwan Ahmad | Yingmin Liu | Orlando Simonetti | Jason Craft | Philip Schniter | O. Simonetti | R. Ahmad | Yingmin Liu | N. Jin | J. Craft | Chong Chen
[1] José M. Bioucas-Dias,et al. Fast Image Recovery Using Variable Splitting and Constrained Optimization , 2009, IEEE Transactions on Image Processing.
[2] Sathish Ramani,et al. Monte Carlo SURE‐based parameter selection for parallel magnetic resonance imaging reconstruction , 2014, Magnetic resonance in medicine.
[3] Daniel K Sodickson,et al. Low‐rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components , 2015, Magnetic resonance in medicine.
[4] Ning Jin,et al. Fast implementation for compressive recovery of highly accelerated cardiac cine MRI using the balanced sparse model , 2017, Magnetic resonance in medicine.
[5] Jean-Philippe Thiran,et al. Sparsity Averaging for Compressive Imaging , 2012, IEEE Signal Processing Letters.
[6] Richard B. Thompson,et al. Reduced native right ventricular T1 in Anderson-Fabry disease as compared to patients with pulmonary hypertension , 2014, Journal of Cardiovascular Magnetic Resonance.
[7] Y. Mitsuhata. Adjustment of regularization in ill‐posed linear inverse problems by the empirical Bayes approach , 2004 .
[8] Robin M Heidemann,et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA) , 2002, Magnetic resonance in medicine.
[9] D. Donoho,et al. Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.
[10] Peter Boesiger,et al. Compressed sensing in dynamic MRI , 2008, Magnetic resonance in medicine.
[11] Sungheon Kim,et al. Golden‐angle radial sparse parallel MRI: Combination of compressed sensing, parallel imaging, and golden‐angle radial sampling for fast and flexible dynamic volumetric MRI , 2014, Magnetic resonance in medicine.
[12] Michael Elad,et al. ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA , 2014, Magnetic resonance in medicine.
[13] W. Segars,et al. MRXCAT: Realistic numerical phantoms for cardiovascular magnetic resonance , 2014, Journal of Cardiovascular Magnetic Resonance.
[14] P. Boesiger,et al. SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.
[15] Runze Li,et al. Regularization Parameter Selections via Generalized Information Criterion , 2010, Journal of the American Statistical Association.
[16] Terry M Peters,et al. Stationary wavelet transform for under-sampled MRI reconstruction. , 2014, Magnetic resonance imaging.
[17] Wenlong Song,et al. Compressed Sensing MRI Using Sparsity Averaging and FISTA , 2017 .
[18] Yoram Bresler,et al. MR Image Reconstruction From Highly Undersampled k-Space Data by Dictionary Learning , 2011, IEEE Transactions on Medical Imaging.
[19] Leon Axel,et al. XD‐GRASP: Golden‐angle radial MRI with reconstruction of extra motion‐state dimensions using compressed sensing , 2016, Magnetic resonance in medicine.
[20] Oren N Jaspan,et al. Compressed sensing MRI: a review of the clinical literature. , 2015, The British journal of radiology.
[21] Kurt Keutzer,et al. Practical parallel imaging compressed sensing MRI: Summary of two years of experience in accelerating body MRI of pediatric patients , 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[22] Yonina C. Eldar,et al. Smoothing and Decomposition for Analysis Sparse Recovery , 2013, IEEE Transactions on Signal Processing.
[23] X. Qu,et al. Combined sparsifying transforms for compressed sensing MRI , 2010 .
[24] Leon Axel,et al. Combination of Compressed Sensing and Parallel Imaging for Highly-Accelerated 3 D First-Pass Cardiac Perfusion MRI , 2009 .
[25] Leslie Ying,et al. Compressed Sensing Dynamic Cardiac Cine MRI Using Learned Spatiotemporal Dictionary , 2014, IEEE Transactions on Biomedical Engineering.
[26] Li Feng,et al. Accelerated phase‐contrast cine MRI using k‐t SPARSE‐SENSE , 2012, Magnetic resonance in medicine.
[27] Philip Schniter,et al. Iteratively Reweighted ℓ1 Approaches to Sparse Composite Regularization , 2015, IEEE Trans. Computational Imaging.
[28] T. Pock,et al. Second order total generalized variation (TGV) for MRI , 2011, Magnetic resonance in medicine.
[29] Yu Ding,et al. Variable density incoherent spatiotemporal acquisition (VISTA) for highly accelerated cardiac MRI , 2015, Magnetic resonance in medicine.
[30] G. Adluru,et al. Myocardial perfusion MRI with an undersampled 3D stack-of-stars sequence. , 2012, Medical physics.
[31] Mário A. T. Figueiredo,et al. Signal restoration with overcomplete wavelet transforms: comparison of analysis and synthesis priors , 2009, Optical Engineering + Applications.
[32] L. Ying,et al. Accelerating SENSE using compressed sensing , 2009, Magnetic resonance in medicine.
[33] S. Frick,et al. Compressed Sensing , 2014, Computer Vision, A Reference Guide.
[34] Jong Chul Ye,et al. k‐t FOCUSS: A general compressed sensing framework for high resolution dynamic MRI , 2009, Magnetic resonance in medicine.
[35] Manuel Desco,et al. Comparison of Total Variation with a Motion Estimation Based Compressed Sensing Approach for Self-Gated Cardiac Cine MRI in Small Animal Studies , 2014, PloS one.
[36] M. Lustig,et al. Compressed Sensing MRI , 2008, IEEE Signal Processing Magazine.
[37] Emmanuel J. Candès,et al. NESTA: A Fast and Accurate First-Order Method for Sparse Recovery , 2009, SIAM J. Imaging Sci..
[38] V. Morozov. On the solution of functional equations by the method of regularization , 1966 .
[39] Guochang Xu,et al. Regularization and Adjustment , 2013 .
[40] M. Lustig,et al. Venous and arterial flow quantification are equally accurate and precise with parallel imaging compressed sensing 4D phase contrast MRI , 2013, Journal of magnetic resonance imaging : JMRI.