Moon Inkyu, Yi Faliu, Rappaz Benjamin
Appl Opt. 2016 Jan 20;55(3):A86-94. doi: 10.1364/AO.55.000A86.
Red blood cell (RBC) phase images that are numerically reconstructed by digital holographic microscopy (DHM) can describe the cell structure and dynamics information beneficial for a quantitative analysis of RBCs. However, RBCs investigated with time-lapse DHM undergo temporal displacements when their membranes are loosely attached to the substrate during sedimentation on a glass surface or due to the microscope drift. Therefore, we need to develop a tracking algorithm to localize the same RBC among RBC image sequences and dynamically monitor its biophysical cell parameters; this information is helpful for studies on RBC-related diseases and drug tests. Here, we propose a method, which is a combination of the mean-shift algorithm and Kalman filter, to track a single RBC and demonstrate that the optical path length of the single RBC can be continually extracted from the tracked RBC. The Kalman filter is utilized to predict the target RBC position in the next frame. Then, the mean-shift algorithm starts execution from the predicted location, and a robust kernel, which is adaptive to changes in the RBC scale, shape, and direction, is designed to improve the accuracy of the tracking. Finally, the tracked RBC is segmented and parameters such as the RBC location are extracted to update the Kalman filter and the kernel function for mean-shift tracking; the characteristics of the target RBC are dynamically observed. Experimental results show the feasibility of the proposed algorithm.
通过数字全息显微镜（DHM）进行数值重建得到的红细胞（RBC）相位图像，可以描述细胞结构和动力学信息，这有利于对红细胞进行定量分析。然而，当用延时DHM研究红细胞时，在玻璃表面沉降过程中，若其细胞膜与底物的附着较松散，或者由于显微镜漂移，红细胞会发生时间上的位移。因此，我们需要开发一种跟踪算法，以便在红细胞图像序列中定位同一个红细胞，并动态监测其生物物理细胞参数；这些信息有助于红细胞相关疾病的研究和药物测试。在此，我们提出一种将均值漂移算法和卡尔曼滤波器相结合的方法，用于跟踪单个红细胞，并证明可以从跟踪到的红细胞中持续提取单个红细胞的光程长度。卡尔曼滤波器用于预测下一帧中目标红细胞的位置。然后，均值漂移算法从预测位置开始执行，并设计了一个鲁棒核，该核能适应红细胞尺度、形状和方向的变化，以提高跟踪精度。最后，对跟踪到的红细胞进行分割，并提取诸如红细胞位置等参数，以更新卡尔曼滤波器和用于均值漂移跟踪的核函数；动态观察目标红细胞的特征。实验结果表明了所提算法的可行性。
