Towards a general framework for fast and feasible k-space trajectories for MRI based on projection methods.

摘要: Abstract The design of feasible trajectories to traverse the k-space for sampling in magnetic resonance imaging (MRI) is important while considering ways reduce scan time. Over recent years, non-Cartesian have been observed result benign artifacts and being less sensitive motion. In this paper, we propose a generalized framework that encompasses projection-based methods generate trajectories. This allows construct from both random or structured initial trajectories, e.g., based on traveling salesman problem (TSP). We evaluate performance proposed by simulating reconstruction 128 × 128 256 × 256 phantom brain MRI images terms structural similarity (SSIM) index peak signal-to-noise ratio (PSNR) using compressed sensing techniques. It TSP-based projection method with constant acceleration parameterization (CAP) better compared velocity (CVP) similar read-out Further, random-like are be than as they time providing quality. A reduction upto 67% achieved permutation (PP) method.