high performance computing on graphics processing units: hgpu.org

For the last two years, we have been experimenting with applying compressed sensing parallel imaging for body imaging of pediatric patients. It is a joint-effort by teams from UC Berkeley, Stanford University and GE Healthcare. This paper aims to summarize our experience so far. We describe our acquisition approach: 3D spoiled-gradient-echo with poisson-disc random undersampling of the phase encodes. Our reconstruction approach: l1-SPIRiT, an iterative autocalibrating parallel imaging reconstruction that enforces both data consistency and joint-sparsity in the wavelet domain. Our implementation: an on-line parallelized implementation of l1-SPIRiT on multi-core CPU and General Purpose Graphics Processors (GPGPU) that achieves sub-minute 3D reconstructions with 8-channels. Clinical results showing higher quality reconstruction and better diagnostic confidence than parallel imaging alone at accelerations on the order of number of coils.