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We consider the application of Compressed Sensing (CS) to enhance the acquisition speed in Magnetic Resonance Imaging (MRI). For CS-based MRI, random sampling is often implemented in the k-space and depends on the uniform distribution and energy distribution of MRI images in the k-space. In contrast, we propose a new deterministic sampling method for CS-based MRI using the logistic map, which has...
This paper proposed a tensor completion algorithm by tracking the Parallel Factor (PARAFAC) decomposition of incomplete third-order tensors with one dimension growing with time. The proposed algorithm first tracks a low-dimensional subspace, then updates the loading matrices of the PARAFAC decomposition. Simulation results showed that the algorithm is reliable and fast, in comparison to the state-of-the-art...
Sweep imaging Fourier transform (SWIFT) is an efficient (fast and quiet) specialized magnetic resonance imaging (MRI) method for imaging tissues or organs that give only short-lived signals due to fast spin-spin relaxation rates. Based on the idea of compressed sensing, this paper proposes a novel method for further enhancing SWIFT using chaotic compressed sensing (CCS-SWIFT). With reduced number...
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 measurements, can accelerate the speed of MRI acquisition...
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