共焦laser扫描显微镜图像相关用于纳米颗粒流动速度测量
Confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry
摘要：
我们提出了一种新的粒子图像相关技术解决纳米粒子的流速，使用共聚焦激光扫描显微镜（CLSM）。使基于纳米粒子扫描激光图像相关（SLIC）的测速复杂化的两个主要问题是（1）使用扩散主导的纳米粒子作为流动示踪剂，其将随机去相关误差引入到速度估计中，以及（2）扫描激光图像采集的影响，其引入偏差误差。到目前为止，没有研究量化这些错误或证明了一种方法来处理它们在SLIC测速。在这项工作中，我们建立在强大的相位相关（RPC）和现有的方法SLIC量化和减轻这些错误。首先，我们实现了一个合奏RPC，而不是使用合奏标准互相关，并开发了SLIC最佳滤波器，最大限度地提高相关强度，以可靠和准确地检测相关峰代表最可能的平均位移的纳米粒子。其次，我们开发了一个分析模型的SLIC测量偏置误差，由于图像扫描扩散为主的示踪粒子。我们表明，偏差误差只取决于的比的平均速度的示踪粒子的激光扫描仪，我们使用这个模型来校正引起的误差。我们使用合成图像和实验获得的纳米颗粒流经微通道的SLIC图像验证了我们的技术。我们的技术减少了高达10倍的误差相比，其他SLIC算法在这项研究中测试的图像。此外，我们优化的RPC滤波器减少了集合相关收敛所需的图像对的数量，与标准互相关相比减少了两个数量级。
英文摘要：
We present a new particle image correlation technique for resolving nanoparticle flow velocity using confocal laser scanning microscopy (CLSM). The two primary issues that complicate nanoparticle scanning laser image correlation (SLIC) based velocimetry are (1) the use of diffusion dominated nanoparticles as flow tracers, which introduce a random decorrelating error into the velocity estimate, and (2) the effects of the scanning laser image acquisition, which introduces a bias error. To date, no study has quantified these errors or demonstrated a means to deal with them in SLIC velocimetry. In this work, we build upon the robust phase correlation (RPC) and existing methods of SLIC to quantify and mitigate these errors. First, we implement an ensemble RPC instead of using an ensemble standard cross correlation, and develop an SLIC optimal filter that maximizes the correlation strength in order to reliably and accurately detect the correlation peak representing the most probable average displacement of the nanoparticles. Secondly, we developed an analytical model of the SLIC measurement bias error due to image scanning of diffusion dominated tracer particles. We show that the bias error depends only on the ratio of the mean velocity of the tracer particles to that of the laser scanner and we use this model to correct the induced errors. We validated our technique using synthetic images and experimentally obtained SLIC images of nanoparticle flow through a micro-channel. Our technique reduced the error by up to a factor of ten compared to other SLIC algorithms for the images tested in this study. Moreover, our optimized RPC filter is reducing the number of image pairs required for the convergence of the ensemble correlation by two orders of magnitude compared to the standard cross correlation.
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