Cartesian Acquisition with Projection-Reconstruction-like sampling is a SENSE-type parallel 3DFT acquisition paradigm for 4D contrast-enhanced magnetic resonance angiography that has been demonstrated capable of providing high spatial and temporal resolution, diagnostic-quality images at very high acceleration rates. However, Cartesian Acquisition with Projection- Reconstruction-like sampling images are typically reconstructed online using Tikhonov regularization and partial Fourier methods, which are prone to exhibit noise amplification and undersampling artifacts when operating at very high acceleration rates. In this work, a sparsity-driven offline reconstruction framework for Cartesian Acquisition with Projection-Reconstruction-like sampling is developed and demonstrated to consistently provide improvements over the currently-employed reconstruction strategy against these ill-effects. Moreover, the proposed reconstruction strategy requires no changes to the existing Cartesian Acquisition with Projection-Reconstruction-like sampling acquisition protocol, and an efficient numerical optimization and hardware system are described that allow for a 256 × 160 × 80 volume contrast-enhanced magnetic resonance angiography volume to be reconstructed from an eight-channel data set in less than 2 min.
- compressed sensing
- compressive sensing
- image reconstruction
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging