Journal Article10.1002/MRM.1113
Adaptive sensitivity encoding incorporating temporal filtering (TSENSE).
TL;DR: An adaptive method of sensitivity encoding is presented which incorporates both spatial and temporal filtering and a high degree of alias artifact rejection may be achieved with less stringent requirements on accuracy of coil sensitivity estimates and temporal low‐pass filter selectivity than would be required using each method individually.
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Abstract: A number of different methods have been demonstrated which increase the speed of MR acquisition by decreasing the number of sequential phase encodes. The UNFOLD technique is based on time interleaving of k-space lines in sequential images and exploits the property that the outer portion of the field-of-view is relatively static. The differences in spatial sensitivity of multiple receiver coils may be exploited using SENSE or SMASH techniques to eliminate the aliased component that results from undersampling k-space. In this article, an adaptive method of sensitivity encoding is presented which incorporates both spatial and temporal filtering. Temporal filtering and spatial encoding may be combined by acquiring phase encodes in an interleaved manner. In this way the aliased components are alternating phase. The SENSE formulation is not altered by the phase of the alias artifact; however, for imperfect estimates of coil sensitivities the residual artifact will have alternating phase using this approach. This is the essence of combining temporal filtering (UNFOLD) with spatial sensitivity encoding (SENSE). Any residual artifact will be temporally frequency-shifted to the band edge and thus may be further suppressed by temporal low-pass filtering. By combining both temporal and spatial filtering a high degree of alias artifact rejection may be achieved with less stringent requirements on accuracy of coil sensitivity estimates and temporal low-pass filter selectivity than would be required using each method individually. Experimental results that demonstrate the adaptive spatiotemporal filtering method (adaptive TSENSE) with acceleration factor R = 2, for real-time nonbreath-held cardiac MR imaging during exercise induced stress are presented.
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Citations
k-t BLAST and k-t SENSE: Dynamic MRI with high frame rate exploiting spatiotemporal correlations
TL;DR: Based on this approach, two methods were developed to significantly improve the performance of dynamic imaging, named k‐t BLAST (Broad‐use Linear Acquisition Speed‐up Technique) and k-t SENSE (SENSitivity Encoding) for use with a single or multiple receiver coils, respectively.
953
Accelerated Dynamic MRI Exploiting Sparsity and Low-Rank Structure: k-t SLR
TL;DR: A novel algorithm to reconstruct dynamic magnetic resonance imaging data from under-sampled k-t space data using the compact representation of the data in the Karhunen Louve transform (KLT) domain to exploit the correlations in the dataset.
Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI
Li Feng,Robert Grimm,Kai Tobias Block,Hersh Chandarana,Sungheon Kim,Jian Xu,Leon Axel,Daniel K. Sodickson,Ricardo Otazo +8 more
TL;DR: To develop a fast and flexible free‐breathing dynamic volumetric MRI technique, iterative Golden‐angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed sensing, parallel imaging, and golden‐angle radial sampling.
695
Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI.
TL;DR: Comp compressed sensing and parallel imaging are combined by merging the k‐t SPARSE technique with sensitivity encoding (SENSE) reconstruction to substantially increase the acceleration rate for perfusion imaging and a new theoretical framework is presented for understanding the combination of k-t SParSE with SENSE based on distributed compressed sensing theory.
605
Parallel MR imaging.
Anagha Deshmane,Vikas Gulani,Vikas Gulani,Mark A. Griswold,Mark A. Griswold,Nicole Seiberlich,Nicole Seiberlich +6 more
TL;DR: The advantages of parallel imaging in a clinical setting include faster image acquisition, which can be used, for instance, to shorten breath‐hold times resulting in fewer motion‐corrupted examinations and recent advancements and promising research in parallel imaging are briefly reviewed.
576
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