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      Technical note: Accelerated nonrigid motion‐compensated isotropic 3D coronary MR angiography

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          Abstract

          Purpose

          To develop an accelerated and nonrigid motion‐compensated technique for efficient isotropic 3D whole‐heart coronary magnetic resonance angiography ( CMRA) with Cartesian acquisition.

          Methods

          Highly efficient whole‐heart 3D CMRA was achieved by combining image reconstruction from undersampled data using compressed sensing ( CS) with a nonrigid motion compensation framework. Undersampled acquisition was performed using a variable‐density Cartesian trajectory with radial order ( VDCAPR). Motion correction was performed in two steps: beat‐to‐beat 2D translational correction with motion estimated from interleaved image navigators, and bin‐to‐bin 3D nonrigid correction with motion estimated from respiratory‐resolved images reconstructed from undersampled 3D CMRA data using CS. Nonrigid motion fields were incorporated into an undersampled motion‐compensated reconstruction, which combines CS with the general matrix description formalism. The proposed approach was tested on 10 healthy subjects and compared against a conventional twofold accelerated 5‐mm navigator‐gated and tracked acquisition.

          Results

          The proposed method achieves isotropic 1.2‐mm Cartesian whole‐heart CMRA in 5 min ± 1 min (~8× acceleration). The proposed approach provides good‐quality images of the left and right coronary arteries, comparable to those of a twofold accelerated navigator‐gated and tracked acquisition, but scan time was up to about four times faster. For both coronaries, no significant differences ( P > 0.05) in vessel sharpness and length were found between the proposed method and reference scan.

          Conclusion

          The feasibility of a highly efficient motion‐compensated reconstruction framework for accelerated 3D CMRA has been demonstrated in healthy subjects. Further investigation is required to assess the clinical value of the method.

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          Most cited references46

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          SENSE: Sensitivity encoding for fast MRI

          New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999. Copyright 1999 Wiley-Liss, Inc.
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            Compressed Sensing MRI

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              Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems.

              This paper studies gradient-based schemes for image denoising and deblurring problems based on the discretized total variation (TV) minimization model with constraints. We derive a fast algorithm for the constrained TV-based image deburring problem. To achieve this task, we combine an acceleration of the well known dual approach to the denoising problem with a novel monotone version of a fast iterative shrinkage/thresholding algorithm (FISTA) we have recently introduced. The resulting gradient-based algorithm shares a remarkable simplicity together with a proven global rate of convergence which is significantly better than currently known gradient projections-based methods. Our results are applicable to both the anisotropic and isotropic discretized TV functionals. Initial numerical results demonstrate the viability and efficiency of the proposed algorithms on image deblurring problems with box constraints.
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                Author and article information

                Contributors
                teresa.correia@kcl.ac.uk
                Journal
                Med Phys
                Med Phys
                10.1002/(ISSN)2473-4209
                MP
                Medical Physics
                John Wiley and Sons Inc. (Hoboken )
                0094-2405
                2473-4209
                12 December 2017
                January 2018
                : 45
                : 1 ( doiID: 10.1002/mp.2018.45.issue-1 )
                : 214-222
                Affiliations
                [ 1 ] Division of Imaging Sciences and Biomedical Engineering King's College London London UK
                [ 2 ] Philips Healthcare Guildford Surrey UK
                [ 3 ] Pontificia Universidad Católica de Chile Escuela de Ingeniería Santiago Chile
                Author notes
                [*] [* ]Author to whom correspondence should be addressed. Electronic mail: teresa.correia@ 123456kcl.ac.uk .
                Article
                MP12663
                10.1002/mp.12663
                5814733
                29131353
                bc56ca9e-b0ad-4e20-a4ab-258fc11743b8
                © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 August 2017
                : 09 October 2017
                : 01 November 2017
                Page count
                Figures: 4, Tables: 0, Pages: 9, Words: 6553
                Funding
                Funded by: Medical Research Council (MRC)
                Award ID: MR/L009676/
                Funded by: Wellcome Trust
                Funded by: EPSRC
                Award ID: WT 088641/Z/09/Z
                Funded by: National Institute for Health Research (NIHR)
                Funded by: King's College Hospital NHS Foundation Trust
                Categories
                Technical Note
                DIAGNOSTIC IMAGING (IONIZING AND NON‐IONIZING)
                Technical Notes
                Custom metadata
                2.0
                mp12663
                January 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.3.2.2 mode:remove_FC converted:16.02.2018

                compressed sensing,coronary mra,image navigator,respiratory motion compensation

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