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 of measurements, CCS-SWIFT effectively faster than SWIFT. In comparison with a recently proposed chaotic compressed sensing method for standard MRI (CCS-MRI), simulation results showed that CCS-SWIFT outperforms CCS-MRI in terms of the normalized relative error in the image reconstruction and the probability of exact reconstruction.

This paper concerns the deterministic and struc tured designs of the measurement matrix in compressed sensing (CS). The deterministic design is approached using chaotic sequences while the structured one is with a spread-spectrum technique using chirp modulation. We propose to combine these two approaches to take advantage of the simple hardware implementation of chaotic sequences, and of reduced the mutual coherence by a chirp modulation, which spreads the data in the acquired domain. The method is illustrated by the well-known application of CS for fast acquisition in magnetic resonance imag ing (MRI). Results and performance comparison are provided by numerical simulation, showing that the proposed method outperforms state-of-the-art CS techniques for MRI acquisition in terms of image reconstruction quality.Index Terms-Compressed sensing, deterministic design, struc tured design, chaotic sequence, spread-spectrum, magnetic reso nance imaging (MRI), fast acquisition.