On the implementation of chaotic compressed sensing for MRI

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 good statistical properties and can be easily converted to uniform-like chaotic sequences. Simulation results confirmed that the proposed method is equivalent to state-of-the-art methods in terms of the relative root-mean-square error and the probability of exact reconstruction.