CompuMAINE Laboratory, Department of Mathematics & Statistics, University of Maine, Orono, ME 04469, USA.
The Motility Group, Division of Aerospace Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA; Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA.
Methods. 2018 Mar 1;136:60-65. doi: 10.1016/j.ymeth.2017.09.003. Epub 2017 Sep 13.
We propose an automated wavelet-based method of tracking particles in unreconstructed off-axis holograms to provide rough estimates of the presence of motion and particle trajectories in digital holographic microscopy (DHM) time series. The wavelet transform modulus maxima segmentation method is adapted and tailored to extract Airy-like diffraction disks, which represent bacteria, from DHM time series. In this exploratory analysis, the method shows potential for estimating bacterial tracks in low-particle-density time series, based on a preliminary analysis of both living and dead Serratia marcescens, and for rapidly providing a single-bit answer to whether a sample chamber contains living or dead microbes or is empty.
我们提出了一种基于小波的自动粒子跟踪方法，用于对离轴全息图进行重构，以提供数字全息显微镜 (DHM) 时间序列中运动和粒子轨迹的大致估计。小波变换模极大值分割方法被适应和定制，以从 DHM 时间序列中提取代表细菌的类艾里衍射盘。在这项探索性分析中，该方法显示出了在低粒子密度时间序列中估计细菌轨迹的潜力，初步分析了活的和死的粘质沙雷氏菌，并且可以快速提供一个二进制答案，即样本室中是否含有活的或死的微生物，或者是空的。
