Michael Andreas Bieri1, Christoph Barmet1, Bertram Jakob Wilm1, Klaas Paul Pruessmann1
1Institute for Biomedical
Engineering, University & ETH
FFT-based MR reconstruction algorithms get increasingly complex when incorporating various encoding terms such as static off-resonance, dynamic higher-order fields, coil sensitivity maps, non-Cartesian k-space sampling, etc. Therefore in this work a versatile algebraic reconstruction is employed that allows for incorporating various encoding mechanisms with only minor increase in complexity. A drawback is the enormous computing time even for small images. A 100x100 image needs minutes to be reconstructed on a current high end CPU. By implementing the algorithm on a graphics processing unit (GPU), speed-up of about 600x was achieved compared to a CPU. All result are shown at the example of dynamic higher order fields combined with static off-resonance and sensitivity encoding.