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定量相显微镜:自动背景校正技术与智能时间相位解包裹

Quantitative phase microscopy: automated background leveling techniques and smart temporal phase unwrapping.

作者信息

Goldstein Goldie, Creath Katherine

出版信息

Appl Opt. 2015 Jun 1;54(16):5175-85. doi: 10.1364/AO.54.005175.

Abstract

In order for time-dynamic quantitative phase microscopy to yield meaningful data to scientists, raw phase measurements must be converted to sequential time series that are consistently phase unwrapped with minimal residual background shape. Beyond the initial phase unwrapping, additional steps must be taken to convert the phase to time-meaningful data sequences. This consists of two major operations both outlined in this paper and shown to operate robustly on biological datasets. An automated background leveling procedure is introduced that consistently removes background shape and minimizes mean background phase value fluctuations. By creating a background phase value that is stable over time, the phase values of features of interest can be examined as a function of time to draw biologically meaningful conclusions. Residual differences between sequential frames of data can be present due to inconsistent phase unwrapping, causing localized regions to have phase values at similar object locations inconsistently changed by large values between frames, not corresponding to physical changes in the sample being observed. This is overcome by introducing a new method, referred to as smart temporal unwrapping that temporally unwraps and filters the phase data such that small motion between frames is accounted for and phase data are unwrapped consistently between frames. The combination of these methods results in the creation of phase data that is stable over time by minimizing errors introduced within the processing of the raw data.

摘要

为了使时间动态定量相显微镜能够为科学家提供有意义的数据,原始相位测量值必须转换为连续的时间序列,这些序列要经过一致的相位展开,且残余背景形状最小。除了初始的相位展开之外,还必须采取额外的步骤将相位转换为具有时间意义的数据序列。本文概述了两个主要操作,并证明它们在生物数据集上能稳健运行。引入了一种自动背景平整程序,该程序能持续去除背景形状并最小化平均背景相位值波动。通过创建一个随时间稳定的背景相位值,可以将感兴趣特征的相位值作为时间的函数进行检查,从而得出具有生物学意义的结论。由于相位展开不一致,数据连续帧之间可能存在残余差异,导致局部区域在相似物体位置的相位值在帧间不一致地大幅变化,这与所观察样本的物理变化不对应。通过引入一种新方法(称为智能时间展开)可以克服这一问题,该方法在时间上对相位数据进行展开和滤波,以便考虑帧间的微小运动,并使帧间相位数据一致地展开。这些方法的结合通过最小化原始数据处理过程中引入的误差,从而生成随时间稳定的相位数据。

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