论文标题
使用基于GPU的原始二元算法的正对比度敏感性MR成像
Positive Contrast Susceptibility MR Imaging Using GPU-based Primal-Dual Algorithm
论文作者
论文摘要
基于易感性的阳性对比度MR技术被应用于具有正则化的L-1最小化的内核反向卷积算法对金属设备的任意磁敏感性分布。此次，一阶原始二 - 二（PD）算法可提供更快的回归时间与其他1-1 minimation相比。在这里，我们建议使用图形处理器单元（GPU）的多核多核多读特征加速正对比图像的PD算法。一些实验结果表明，基于GPU的PD算法可以在较少的计算时间内实现高度对比度成像中金属介入设备的可比精度。基于GPU的PD方法的速度比以前的基于CPU的方案快4至15倍。
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.
