Analysis of generalized rosette trajectory for compressed sensing MRI

摘要: Purpose: The application of compressed sensing (CS) technology in magnetic resonance imaging (MRI) is to accelerate the MRI scan speed by incoherent undersampling k-space data and nonlinear iterative reconstruction images. This paper generalizes existing rosette trajectories configure sampling patterns for undersampled acquisition scans. arch curvature characteristics generalized are analyzed explore their feasibility advantages CS Methods: Two key properties crucial application, incoherence trajectories, analyzed. analysis on based transversal time derived from evaluation point spread function measurement matrix. results supported extensive simulations where performances rosette, spiral, radial at different acceleration factors compared. Results: It shown that compared with spiral more feasible meet physical requirements terms shortness area. further pattern trajectory has higher than other can thus achieve performance. Reconstruction illustrate about 10% peak signal-to-noise ratio under high factor R = 10. Conclusions: be a desirable candidate MRI.