CS-SENSE Reconstruction using a Two-Level Variable Density Sampling Pattern

Mariya Doneva^1,2, Peter Brnert¹, Alfred Mertins²

The synthesis of CS and parallel imaging is of consierable interest. Several works have proposed a combination of SENSE and CS as an iterative sparsity constrained SENSE reconstruction. Typically a variable density pseudo-random sampling is used as a compromise between regular and irregular sampling. Based on the properties of CS and SENSE, we propose a two-step CS-SENSE reconstruction, in which the two reconstruction steps are used to recover distinct parts of k-space and apply a two-level variable density sampling pattern.