Positive-contrast susceptibility imaging based on first-order primal-dual optimization

Positive Contrast Susceptibility MR Imaging Using GPU-based Primal-Dual Algorithm

The susceptibility-based positive contrast MR technique was applied to estimate arbitrary magnetic susceptibility distributions of the metallic devices using a kernel deconvolution algorithm with a regularized L-1 minimization. Previously, the first-order primal-dual (PD) algorithm could provide a faster reconstruction time to solve the L-1 minimization, compared with other methods. Here, we propose to accelerate the PD algorithm of the positive contrast image using the multi-core multi-thread feature of graphics processor units (GPUs). The some experimental results showed that the GPU-based PD algorithm could achieve comparable accuracy of the metallic interventional devices in positive contrast imaging with less computational time. And the GPU-based PD approach was 4~15 times faster than the previous CPU-based scheme.Clinical Relevance-This can estimate arbitrary magnetic susceptibility distributions of the metallic devices with the processing efficacy of 4~15 times faster than before.