School of Information Science and Engineering, Northeastern University, Shenyang, CO 110819, China; Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, CO 110819, China.
Magn Reson Imaging. 2013 Oct;31(8):1390-8. doi: 10.1016/j.mri.2013.04.013. Epub 2013 Jun 4.
In PROPELLER, raw data are collected in N strips, each locating at the center of k-space and consisting of Mx sampling points in frequency encoding direction and L lines in phase encoding direction. Phase correction, rotation correction, and translation correction are used to remove artifacts caused by physiological motion and physical movement, but their time complexities reach O(Mx×Mx×L×N), O(N×RA×Mx×L×(Mx×L+RN×RN)), and O(N×(RN×RN+Mx×L)) where RN×RN is the coordinate space each strip gridded onto and RA denotes the rotation range. A CUDA accelerated method is proposed in this paper to improve their performances. Although our method is implemented on a general PC with Geforce 8800GT and Intel Core(TM)2 E6550 2.33GHz, it can directly run on more modern GPUs and achieve a greater speedup ratio without being changed. Experiments demonstrate that (1) our CUDA accelerated phase correction achieves exactly the same result with the non-accelerated implementation, (2) the results of our CUDA accelerated rotation correction and translation correction have only slight differences with those of their non-accelerated implementation, (3) images reconstructed from the motion correction results of CUDA accelerated methods proposed in this paper satisfy the clinical requirements, and (4) the speed up ratio is close to 6.5.
在 PROPELLER 中，原始数据以 N 条带的形式采集，每条带位于 k 空间的中心，由频率编码方向上的 Mx 个采样点和相位编码方向上的 L 条线组成。相位校正、旋转校正和平移校正用于去除由生理运动和物理运动引起的伪影，但它们的时间复杂度分别达到 O(Mx×Mx×L×N)、O(N×RA×Mx×L×(Mx×L+RN×RN))和 O(N×(RN×RN+Mx×L))，其中 RN×RN 是每条带网格化的坐标空间，RA 表示旋转范围。本文提出了一种 CUDA 加速方法来提高它们的性能。虽然我们的方法是在具有 Geforce 8800GT 和 Intel Core(TM)2 E6550 2.33GHz 的普通 PC 上实现的，但它可以直接在更现代的 GPU 上运行，并且无需更改即可实现更大的加速比。实验表明：(1)我们的 CUDA 加速相位校正与非加速实现完全相同；(2)我们的 CUDA 加速旋转校正和平移校正的结果与非加速实现的结果只有微小差异；(3)从本文提出的 CUDA 加速方法的运动校正结果重建的图像满足临床要求；(4)加速比接近 6.5。
