Compressed sensing based MR image reconstruction from multiple partial K space scans
In Magnetic Resonance Imaging (MRI) signal averaging is an established technique for reducing white Gaussian noise or motion artifacts. Acquiring multiple scans for signal averaging is time consuming. To reduce the data acquisition time, Compressed Sensing (CS) based techniques advocate partial scanning of the K space only. Instead of using averaging techniques in conjunction with CS based reconstruction, this work proposes a novel formulation that produces extremely accurate reconstruction results. Our method gives the same reconstruction accuracy at 50% K space sampling as does the conventional signal averaging of the full K space.
2011 IEEE Workshop on Signal Processing Systems (SiPS)