New Image Reconstruction Methods for Accelerated Quantitative Parameter Mapping and Magnetic Resonance Angiography

Advanced MRI techniques often require sampling in additional (non-spatial) dimensions such as time or parametric dimensions, which significantly elongate scan time. Our purpose was to develop novel iterative image reconstruction methods to reduce amount of acquired data in such applications using prior knowledge about signal in the extra dimensions. The efforts have been made to accelerate two applications, namely, time resolved contrast enhanced MR angiography and T1 mapping. Our result demonstrate that significant acceleration (up to 27x times) may be achieved using our proposed iterative reconstruction techniques.

[1]  Stephen J Riederer,et al.  3D high temporal and spatial resolution contrast‐enhanced MR angiography of the whole brain , 2008, Magnetic resonance in medicine.

[2]  A. Alexander,et al.  Accelerating MR parameter mapping using sparsity‐promoting regularization in parametric dimension , 2013, Magnetic resonance in medicine.

[3]  P. Boesiger,et al.  Advances in sensitivity encoding with arbitrary k‐space trajectories , 2001, Magnetic resonance in medicine.

[4]  Walter F Block,et al.  Time‐resolved contrast‐enhanced imaging with isotropic resolution and broad coverage using an undersampled 3D projection trajectory , 2002, Magnetic resonance in medicine.

[5]  D. Peters,et al.  Undersampled projection reconstruction applied to MR angiography , 2000, Magnetic resonance in medicine.

[6]  E. Candès,et al.  Sparsity and incoherence in compressive sampling , 2006, math/0611957.

[7]  Kay Nehrke,et al.  k‐t PCA: Temporally constrained k‐t BLAST reconstruction using principal component analysis , 2009, Magnetic resonance in medicine.

[8]  Zhi-Pei Liang,et al.  SPATIOTEMPORAL IMAGINGWITH PARTIALLY SEPARABLE FUNCTIONS , 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[9]  Bob S. Hu,et al.  Fast Spiral Coronary Artery Imaging , 1992, Magnetic resonance in medicine.

[10]  Suyash P. Awate,et al.  Temporally constrained reconstruction of dynamic cardiac perfusion MRI , 2007, Magnetic resonance in medicine.

[11]  Alexey A Samsonov,et al.  Reconstruction of dynamic image series from undersampled MRI data using data‐driven model consistency condition (MOCCO) , 2015, Magnetic resonance in medicine.

[12]  James F Glockner,et al.  High temporal and spatial resolution 3D time‐resolved contrast‐enhanced magnetic resonance angiography of the hands and feet , 2011, Journal of magnetic resonance imaging : JMRI.

[13]  D. Noll,et al.  Homodyne detection in magnetic resonance imaging. , 1991, IEEE transactions on medical imaging.

[14]  B. Rutt,et al.  Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state , 2003, Magnetic resonance in medicine.

[15]  Horst Urbach,et al.  Cerebral arteriovenous malformation: Spetzler-Martin classification at subsecond-temporal-resolution four-dimensional MR angiography compared with that at DSA. , 2008, Radiology.

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

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