Accelerated Parallel Magnetic Resonance Imaging with Multi-Channel Chaotic Compressed Sensing
Fast acquisition in magnetic resonance imaging (MRI) is considered in this paper. Often, fast acquisition is achieved using parallel imaging (pMRI) techniques. It has been shown recently that the combination of pMRI and compressed sensing (CS), which enables exact reconstructi...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
International Conference on Advanced Technologies for Communications ATC 2010
2016
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| Subjects: | |
| Online Access: | http://repository.vnu.edu.vn/handle/VNU_123/14442 |
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| Institution: | Vietnam National University, Hanoi |
| Language: | English |
| Summary: | Fast acquisition in magnetic resonance imaging
(MRI) is considered in this paper. Often, fast acquisition is
achieved using parallel imaging (pMRI) techniques. It has been
shown recently that the combination of pMRI and compressed
sensing (CS), which enables exact reconstruction of sparse or
compressible signals from a small number of
random
measure-
ments, can accelerate the speed of MRI acquisition because the
number of measurements are much smaller than that by pMRI
per se. Also recently in CS, chaos filters were designed to obtain
chaotic
measurements. This chaotic CS approach potentially
offers simpler hardware implementation. In this paper, we
combine chaotic CS and pMRI. However, instead of using
chaos filters, the measurements are obtained by chaotically
undersampling the
k
-space. MRI image reconstruction is then
performed by using nonlinear conjugate gradient optimization.
For pMRI, we use the well-known approach SENSE – sensitivity
encoding –, which requires an estimation of the sensitivity maps.
The performance of the proposed method is analyzed using the
point spread function, the transform point spread function, and
the reconstruction error measure. |
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