Reducing data acquisition times in phase-encoded velocity imaging using compressed sensing
Tài liệu tham khảo
Lustig, 2007, Sparse MRI: the application of compressed sensing for rapid MR imaging, Magn. Reson. Med., 58, 1182, 10.1002/mrm.21391
Gatehouse, 2005, Applications of phase-contrast flow and velocity imaging in cardiovascular MRI, Eur. Radiol., 15, 2172, 10.1007/s00330-005-2829-3
Fukushima, 1999, Nuclear magnetic resonance as a tool to study flow, Ann. Rev. Fluid Mech., 31, 95, 10.1146/annurev.fluid.31.1.95
Mantle, 2003, Dynamic MRI in chemical process and reaction engineering, Prog. Nucl. Mag. Res. Spectrosc., 43, 3, 10.1016/S0079-6565(03)00005-0
Callaghan, 1999, Rheo-NMR: nuclear magnetic resonance and the rheology of complex fluids, Rep. Prog. Phys., 62, 599, 10.1088/0034-4885/62/4/003
Sederman, 1998, Structure-flow correlations in packed beds, Chem. Eng. Sci., 53, 2117, 10.1016/S0009-2509(98)00059-1
Fukushima, 2006, Granular flows
Holland, 2008, Spatially resolved measurement of anisotropic granular temperature in gas-fluidized beds, Powder Tech., 182, 171, 10.1016/j.powtec.2007.06.030
Kose, 1991, Instantaneous flow-distribution measurements of the equilibrium turbulent region in a circular pipe using ultrafast NMR imaging, Phys. Rev. A, 44, 2495, 10.1103/PhysRevA.44.2495
Kose, 1991, One-shot velocity mapping using multiple spin-echo EPI and its application to turbulent flow, J. Magn. Reson., 92, 631
Sederman, 2004, MRI technique for measurement of velocity vectors, acceleration and autocorrelation functions in turbulent flow, J. Magn. Reson., 166, 182, 10.1016/j.jmr.2003.10.016
Galvosas, 2006, Fast magnetic resonance imaging and velocimetry for liquids under high flow rates, J. Magn. Reson., 181, 119, 10.1016/j.jmr.2006.03.020
Jung, 2008, Highly k-t-space-accelerated phase-contrast MRI, Magn. Reson. Med., 60, 1169, 10.1002/mrm.21764
Parasoglou, 2009, Quantitative single point imaging with compressed sensing, J. Magn. Reson., 201, 72, 10.1016/j.jmr.2009.08.003
Gamper, 2008, Compressed sensing in dynamic MRI, Magn. Reson. Med., 59, 365, 10.1002/mrm.21477
Sankey, 2009, Magnetic resonance velocity imaging of liquid and gas two-phase flow in packed beds, J. Magn. Reson., 196, 142, 10.1016/j.jmr.2008.10.021
Scheffler, 1998, Reduced circular field-of-view imaging, Magn. Reson. Med., 40, 474, 10.1002/mrm.1910400319
Peters, 2000, Undersampled projection reconstruction applied to MR angiography, Magn. Reson. Med., 43, 91, 10.1002/(SICI)1522-2594(200001)43:1<91::AID-MRM11>3.0.CO;2-4
Tsai, 2000, Reduced aliasing artifacts using variable-density k-space sampling trajectories, Magn. Reson. Med., 43, 452, 10.1002/(SICI)1522-2594(200003)43:3<452::AID-MRM18>3.0.CO;2-B
McGibney, 1993, Quantitative evaluation of several partial Fourier reconstruction algorithms used in MRI, Magn. Reson. Med., 30, 51, 10.1002/mrm.1910300109
Sodickson, 1997, Simultaneous acquisition of spatial harmonics (SMASH): fast imaging with radiofrequency coil arrays, Magn. Reson. Med., 38, 591, 10.1002/mrm.1910380414
Candès, 2006, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Trans. Inform. Theor., 52, 489, 10.1109/TIT.2005.862083
Donoho, 2006, Compressed sensing, IEEE Trans. Inform. Theor., 52, 1289, 10.1109/TIT.2006.871582
Taubman, 2002, JPEG2000: standard for interactive imaging, Proc. IEEE, 90, 1336, 10.1109/JPROC.2002.800725
Kim, 2007, A method for large-scale ℓ1-regularized least squares, IEEE J. Sel. Top. Signal., 1, 606, 10.1109/JSTSP.2007.910971
Fornasier, 2008, Iterative thresholding algorithms, Appl. Comput. Harmon. Anal., 25, 187, 10.1016/j.acha.2007.10.005
Yin, 2008, Bregman iterative algorithms for ℓ1-minimization with applications to compressed sensing, SIAM J. Imaging Sci., 1, 143, 10.1137/070703983
Candès, 2002, New multiscale transforms, minimum total variation synthesis: applications to edge-preserving image reconstruction, Signal Process., 82, 1519, 10.1016/S0165-1684(02)00300-6
Candès, 2006, Near optimal signal recovery from random projections: universal encoding strategies?, IEEE Trans. Inform. Theor., 52, 5406, 10.1109/TIT.2006.885507
M. Lustig, Sparse MRI, Ph.D. thesis, Stanford University, 2008.
Wood, 1999, Wavelet-packet denoising of magnetic resonance images: importance of Rician statistics at low SNR, Magn. Reson. Med., 41, 631, 10.1002/(SICI)1522-2594(199903)41:3<631::AID-MRM29>3.0.CO;2-Q
Trzasko, 2009, Highly undersampled magnetic resonance image reconstruction via homotopic ℓ0-minimization, IEEE Trans. Med. Imaging, 28, 106, 10.1109/TMI.2008.927346
Manz, 1999, Flow and dispersion in porous media: lattice-Boltzmann and NMR studies, AIChE J., 45, 1845, 10.1002/aic.690450902
Mantle, 2001, Single- and two-phase flow in fixed-bed reactors: MRI flow visualisation and lattice-Boltzmann simulations, Chem. Eng. Sci., 56, 523, 10.1016/S0009-2509(00)00256-6
Olshausen, 1996, Natural image statistics and efficient coding, Network Comp. Neural Syst., 7, 333, 10.1088/0954-898X_7_2_014
Lewicki, 2000, Learning overcomplete representations, Neural Comp., 12, 337, 10.1162/089976600300015826
Shapiro, 1993, Embedded image coding using zerotrees of wavelet coefficients, IEEE Trans. Signal Process., 41, 3445, 10.1109/78.258085
R.G. Baraniuk, V. Cevher, M. Duarte, C. Hegde, Model-based compressive sensing, IEEE Trans. Inform. Theor., submitted for publication, arXiv:0808.3572v5.