Spherical finite rate of innovation theory for the recovery of fiber orientations
In this paper, we investigate the reconstruction of a signal defined as the sum of orientations from samples taken with a kernel defined on the 3D rotation group. A potential application is the recovery of fiber orientations in diffusion magnetic resonance imaging. We propose an exact reconstruction...
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sg-ntu-dr.10356-987132020-03-07T13:24:48Z Spherical finite rate of innovation theory for the recovery of fiber orientations Deslauriers-Gauthier, Samuel Marziliano, Pina School of Electrical and Electronic Engineering Annual International Conference of the IEEE Engineering in Medicine and Biology Society (34th : 2012 : San Diego, USA) DRNTU::Engineering::Electrical and electronic engineering In this paper, we investigate the reconstruction of a signal defined as the sum of orientations from samples taken with a kernel defined on the 3D rotation group. A potential application is the recovery of fiber orientations in diffusion magnetic resonance imaging. We propose an exact reconstruction algorithm based on the finite rate of innovation theory that makes use of the spherical harmonics representation of the signal. The number of measurements needed for perfect recovery, which may be as low as, depends only on the number of orientations and the bandwidth of the kernel used. Furthermore, the angular resolution of our method does not depend on the number of available measurements. We illustrate the performance of the algorithm using several simulations. 2013-07-30T08:08:19Z 2019-12-06T19:58:45Z 2013-07-30T08:08:19Z 2019-12-06T19:58:45Z 2012 2012 Conference Paper https://hdl.handle.net/10356/98713 http://hdl.handle.net/10220/12529 10.1109/EMBC.2012.6346421 en |
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DRNTU::Engineering::Electrical and electronic engineering Deslauriers-Gauthier, Samuel Marziliano, Pina Spherical finite rate of innovation theory for the recovery of fiber orientations |
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In this paper, we investigate the reconstruction of a signal defined as the sum of orientations from samples taken with a kernel defined on the 3D rotation group. A potential application is the recovery of fiber orientations in diffusion magnetic resonance imaging. We propose an exact reconstruction algorithm based on the finite rate of innovation theory that makes use of the spherical harmonics representation of the signal. The number of measurements needed for perfect recovery, which may be as low as, depends only on the number of orientations and the bandwidth of the kernel used. Furthermore, the angular resolution of our method does not depend on the number of available measurements. We illustrate the performance of the algorithm using several simulations. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Deslauriers-Gauthier, Samuel Marziliano, Pina |
format |
Conference or Workshop Item |
author |
Deslauriers-Gauthier, Samuel Marziliano, Pina |
author_sort |
Deslauriers-Gauthier, Samuel |
title |
Spherical finite rate of innovation theory for the recovery of fiber orientations |
title_short |
Spherical finite rate of innovation theory for the recovery of fiber orientations |
title_full |
Spherical finite rate of innovation theory for the recovery of fiber orientations |
title_fullStr |
Spherical finite rate of innovation theory for the recovery of fiber orientations |
title_full_unstemmed |
Spherical finite rate of innovation theory for the recovery of fiber orientations |
title_sort |
spherical finite rate of innovation theory for the recovery of fiber orientations |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/98713 http://hdl.handle.net/10220/12529 |
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1681039433644638208 |