References
- Lee VS, Cardiovascular MRI: Physical Principles to Practical Protocols. Philadelphia: Lippincott Williams & Wilkins, 2006.
- Carpenter TA, Williams EJ. MRI - from basic knowledge to advanced strategies: hardware. Eur Radiol 1999;9:1015-1019 https://doi.org/10.1007/s003300050787
- Tsao J, Boesiger P, Pruessmann KP. k-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations. Magn Reson Med 2003;50:1031-1042 https://doi.org/10.1002/mrm.10611
- Schmitt M, Potthast A, Sosnovik DE, et al. A 128-channel receive-only cardiac coil for highly accelerated cardiac MRI at 3 Tesla. Magn Reson Med 2008;59:1431-1439 https://doi.org/10.1002/mrm.21598
- Liu F, Zhao H, Crozier S. On the induced electric field gradients in the human body for magnetic stimulation by gradient coils in MRI. IEEE Trans Biomed Eng 2003;50:804-815 https://doi.org/10.1109/TBME.2003.813538
- Glover PM. Interaction of MRI field gradients with the human body. Phys Med Biol 2009;54:R99-R115 https://doi.org/10.1088/0031-9155/54/21/R01
- Schoenberg SO, Dietrich O, Reiser MF, Parallel imaging in clinical MR applications. Berlin: Springer, 2007
- Riederer SJ, Tasciyan T, Farzaneh F, Lee JN, Wright RC, Herfkens RJ. MR fluoroscopy: technical feasibility. Magn Reson Med 1988;8:1-15 https://doi.org/10.1002/mrm.1910080102
- Doyle M, Walsh EG, Blackwell GG, Pohost GM. Block regional interpolation scheme for k-Space (BRISK): a rapid cardiac imaging technique. Magn Reson Med 1995;33:163-170 https://doi.org/10.1002/mrm.1910330204
- Jones RA, Haraldseth O, Muller TB, Rinck PA, Oksendal AN. K-space substitution: a novel dynamic imaging technique. Magn Reson Med 1993;29:830-834 https://doi.org/10.1002/mrm.1910290618
- Oesterle C, Strohschein R, Kohler M, Schnell M, Hennig J. Benefits and pitfalls of keyhole imaging, especially in first-pass perfusion studies. J Magn Reson Imaging 2000;11:312-323
- Donoho DL. Compressed sensing. IEEE Trans Inf Theory 2006;52:1289-1306 https://doi.org/10.1109/TIT.2006.871582
- Lustig M, Donoho D, Pauly JM. Sparse MRI: The application of compressed sensing for rapid MR imaging. Magn Reson Med 2007;58:1182-1195 https://doi.org/10.1002/mrm.21391
- Baraniuk RB. Compressive Sensing IEEE Sign Proc Mag 2007;24:118-124
- Jung H, Ye JC, Kim EY. Improved k-t BLAST and k-t SENSE using FOCUSS. Phys Med Biol 2007;52:3201-3226 https://doi.org/10.1088/0031-9155/52/11/018
- Liang D, DiBella EVR, Chen R-R, Ying L. k-t ISD: dynamic cardiac MR imaging using compressed sensing with iterative support detection. Magn Reson Med 2012;68:41-53 https://doi.org/10.1002/mrm.23197
- Jung H, Ye JC. Motion estimated and compensated compressed sensing dynamic magnetic resonance imaging: What we can learn from video compression techniques. Int J Imaging Syst Technol 2010;20:81-98 https://doi.org/10.1002/ima.20231
- Usman M, Atkinson D, Odille F, et al. Motion corrected compressed sensing for free-breathing dynamic cardiac MRI. Magn Reson Med 2013;70:504-516 https://doi.org/10.1002/mrm.24463
- Otazo R, Kim D, Axel L, Sodickson DK. Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI. Magn Reson Med 2010;64:767-776 https://doi.org/10.1002/mrm.22463
- Feng L, Grimm R, Block KT, 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. Magn Reson Med 2013;72:707-717
- Ahn CB. A New Compressed Sensing Technique by Iterative Truncation of Small Transformed Coefficients. Proc. ESMRMB 2012;e-Poster 641
- Bluemke DA, Boxerman JL, Atalar E, McVeigh ER. Segmented K-space cine breath-hold cardiovascular MR imaging: Part 1. Principles and technique. AJR Am J Roentgenol 1997;169:395-400 https://doi.org/10.2214/ajr.169.2.9242742
- Park J, Yoon JH, Yang YJ, Ahn CB. Cardiac magnetic resonance imaging using Multi-physiological intelligent trigger system. J Korean Soc Magn Reson Med 2014;18:244-252 https://doi.org/10.13104/jksmrm.2014.18.3.244
- Margosian P, Faster MR imaging-imaging with half the data. Proc SMRM 1985;1024-1025
- Bernstein MA, King KF, Zhou XJ. Handbook of MRI Pulse Sequences. Amsterdam: Elsevier, 2004.
- Lingala SG, Hu Y, DiBella E, Jacob M. Accelerated dynamic MRI exploiting sparsity and low-rank structure: k-t SLR. IEEE Trans Med Imaging 2011;30:1042-1054 https://doi.org/10.1109/TMI.2010.2100850
- Acharya T, Tsai P-S. JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures. New Jersey: John Wiley & Sons, 2005
- Gonzalez RC, Woods RE. Digital Image Processing. 3th ed. New Jersey: Pearson Education, 2010
- Vasanawala S, Murphy M, Alley M, et al. Practical parallel imaging compressed sensing MRI: Summary of two years of experience in acceleration body MRI of pediatric patients. Proc IEEE Int Symp Biomed Imaging 2011;1039-1043
- Sharma SD, Fong CL, Tzung BS, Law M, Nayak KS. Clinical image quality assessment of accelerated magnetic resonance neuroimaging using compressed sensing. Invest Radiol 2013;48:638-645 https://doi.org/10.1097/RLI.0b013e31828a012d
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