Du Yi, Yu Gongyi, Xiang Xincheng, Wang Xiangang
Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, 100084, China.
Department of Engineering, Macquarie University, Sydney, NSW, 2109, Australia.
Biomed Eng Online. 2017 Jan 5;16(1):2. doi: 10.1186/s12938-016-0293-8.
For cone-beam computed tomography (CBCT), which has been playing an important role in clinical applications, iterative reconstruction algorithms are able to provide advantageous image qualities over the classical FDK. However, the computational speed of iterative reconstruction is a notable issue for CBCT, of which the forward projection calculation is one of the most time-consuming components.
In this study, the cone-beam forward projection problem using the voxel-driven model is analysed, and a GPU-based acceleration method for CBCT forward projection is proposed with the method rationale and implementation workflow detailed as well. For method validation and evaluation, computational simulations are performed, and the calculation times of different methods are collected. Compared with the benchmark CPU processing time, the proposed method performs effectively in handling the inter-thread interference problem, and an acceleration ratio as high as more than 100 is achieved compared to a single-threaded CPU implementation.
The voxel-driven forward projection calculation for CBCT is highly paralleled by the proposed method, and we believe it will serve as a critical module to develop iterative reconstruction and correction methods for CBCT imaging.
对于在临床应用中发挥重要作用的锥束计算机断层扫描（CBCT），迭代重建算法能够提供优于传统FDK的图像质量。然而，迭代重建的计算速度是CBCT的一个显著问题，其中前向投影计算是最耗时的部分之一。
在本研究中，分析了使用体素驱动模型的锥束前向投影问题，并提出了一种基于GPU的CBCT前向投影加速方法，同时详细阐述了方法原理和实现流程。为了进行方法验证和评估，进行了计算模拟，并收集了不同方法的计算时间。与基准CPU处理时间相比，所提出的方法在处理线程间干扰问题方面表现有效，与单线程CPU实现相比，实现了高达100以上的加速比。
所提出的方法使CBCT的体素驱动前向投影计算具有高度并行性，我们相信它将成为开发CBCT成像迭代重建和校正方法的关键模块。
