论文标题
超级波(S波):加速光声模拟
Superposed Wave (s-Wave): Accelerating Photoacoustic Simulation
论文作者
论文摘要
近年来,由于光声成像在许多临床前和临床应用中的表现都非常快。但是,它仍处于发展阶段,并且必须在模拟设置中进行许多实验。为了模拟计算机中的光声成像,K-Wave是目前最受欢迎的MATLAB工具箱。许多研究小组选择K-Wave工具箱来执行前向投影过程,也可以将其描述为前向模型。但是,通过求解复杂的部分微分方程,k波在计算时间中遭受了很大的影响。为了加速光声模拟,在本文中,我们提出了一种基于超级波(S波)的直接模拟方法。具体而言,我们将初始压力分布视为一组单像素。然后,通过从单像素中预先计算标准传感器数据,我们可以轻松地使用循环和乘法运算符来更改给定像素的传感器数据的相位和振幅。我们使用三个不同的2D样品和两个3D样品来测试时间成本。与K波相比,我们提出的S波方法的结果较小得多。尤其是在3D中稀疏配置中,S波比K-Wave快2000倍以上,在获得几乎相同的传感器数据时。
Photoacoustic imaging develops very fast in recent years due to its superior performance in many preclinical and clinical applications. However, it is still in a developing stage, and a lot of experiments have to be performed in a simulation setting. To simulate photoacoustic imaging in a computer, k-Wave is currently the most popular MATLAB toolbox. Lots of research groups choose k-Wave toolbox to perform the forward projection process, which also can be described as forward model. However, by solving complex partial differential equation, k-Wave suffers a lot from computation time. To accelerate photoacoustic simulation, in this paper, we propose a straightforward simulation approach based on superposed Wave (s-Wave). Specifically, we treat the initial pressure distribution as a set of single pixels. Then by pre-obtaining a standard sensor data from single pixel, we can easily use loop and multiplication operators to change phase and amplitude of sensor data for given pixels. We use three different 2D samples and two 3D samples to test the time cost. The result of our proposed s-Wave method shows much less time consumption compared with k-wave. Especially in a sparse configuration in 3D, s-Wave is more than 2000 times faster than k-Wave, whiling getting nearly same sensor data.