Literature DB >> 19859952

Radial k-t FOCUSS for high-resolution cardiac cine MRI.

Hong Jung1, Jaeseok Park, Jaeheung Yoo, Jong Chul Ye.   

Abstract

A compressed sensing dynamic MR technique called k-t FOCUSS (k-t FOCal Underdetermined System Solver) has been recently proposed. It outperforms the conventional k-t BLAST/SENSE (Broad-use Linear Acquisition Speed-up Technique/SENSitivity Encoding) technique by exploiting the sparsity of x-f signals. This paper applies this idea to radial trajectories for high-resolution cardiac cine imaging. Radial trajectories are more suitable for high-resolution dynamic MRI than Cartesian trajectories since there is smaller tradeoff between spatial resolution and number of views if streaking artifacts due to limited views can be resolved. As shown for Cartesian trajectories, k-t FOCUSS algorithm efficiently removes artifacts while preserving high temporal resolution. k-t FOCUSS algorithm applied to radial trajectories is expected to enhance dynamic MRI quality. Rather than using an explicit gridding method, which transforms radial k-space sampling data to Cartesian grid prior to applying k-t FOCUSS algorithms, we use implicit gridding during FOCUSS iterations to prevent k-space sampling errors from being propagated. In addition, motion estimation and motion compensation after the first FOCUSS iteration were used to further sparsify the residual image. By applying an additional k-t FOCUSS step to the residual image, improved resolution was achieved. In vivo experimental results show that this new method can provide high spatiotemporal resolution even from a very limited radial data set. Copyright (c) 2009 Wiley-Liss, Inc.

Mesh:

Year:  2010        PMID: 19859952     DOI: 10.1002/mrm.22172

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  32 in total

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6.  A framework for generalized reference image reconstruction methods including HYPR-LR, PR-FOCUSS, and k-t FOCUSS.

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8.  Functional imaging of murine hearts using accelerated self-gated UTE cine MRI.

Authors:  Abdallah G Motaal; Nils Noorman; Wolter L de Graaf; Verena Hoerr; Luc M J Florack; Klaas Nicolay; Gustav J Strijkers
Journal:  Int J Cardiovasc Imaging       Date:  2014-09-10       Impact factor: 2.357

9.  Motion-compensated data decomposition algorithm to accelerate dynamic cardiac MRI.

Authors:  Azar Tolouee; Javad Alirezaie; Paul Babyn
Journal:  MAGMA       Date:  2017-05-31       Impact factor: 2.310

10.  Highly accelerated real-time cardiac cine MRI using k-t SPARSE-SENSE.

Authors:  Li Feng; Monvadi B Srichai; Ruth P Lim; Alexis Harrison; Wilson King; Ganesh Adluru; Edward V R Dibella; Daniel K Sodickson; Ricardo Otazo; Daniel Kim
Journal:  Magn Reson Med       Date:  2012-08-06       Impact factor: 4.668

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