Improved time series reconstruction for dynamic magnetic resonance imaging.

IEEE Transactions on Medical Imaging
Uygar SümbülJohn M Pauly

Abstract

Time series of in vivo magnetic resonance images exhibit high levels of temporal correlation. Higher temporal resolution reconstructions are obtained by acquiring data at a fraction of the Nyquist rate and resolving the resulting aliasing using the correlation information. The dynamic imaging experiment is modeled as a linear dynamical system. A Kalman filter based unaliasing reconstruction is described for accelerated dynamic magnetic resonance imaging (MRI). The algorithm handles arbitrary readout trajectories naturally. The reconstruction is causal and very fast, making it applicable to real-time imaging. In vivo results are presented for cardiac MRI of healthy volunteers.

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Citations

Jun 5, 2010·Nonlinear Biomedical Physics·Arvid Lundervold
Nov 19, 2015·Magnetic Resonance Imaging·Chen ChenJunzhou Huang
Aug 29, 2012·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Xue FengCraig H Meyer
Mar 24, 2012·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Bo XuYi Wang
Nov 19, 2013·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Housen LiAxel Munk
Sep 6, 2012·IEEE Transactions on Medical Imaging·Angshul MajumdarTyseer Aboulnasr
Aug 28, 2009·IEEE Transactions on Medical Imaging·Uygar SümbülJohn M Pauly
Jul 14, 2012·Magnetic Resonance Imaging·Angshul Majumdar, Rabab K Ward
Jul 31, 2013·Magnetic Resonance Imaging·Angshul Majumdar
Aug 3, 2010·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Brice FernandezJacques Felblinger
Nov 25, 2011·Magnetic Resonance in Medicine : Official Journal of the Society of Magnetic Resonance in Medicine·Dong LiangLeslie Ying
Aug 15, 2017·Computational and Mathematical Methods in Medicine·Yiran WangFeng Liu

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