微离轴数字全息显微镜定量相位成像的活细胞分析框架

Qian Shen, Zhuoshi Li, Jiasong Sun, Yao Fan, Yuanyuan Chen, Haojie Gu, P. Gao, Qian Chen, C. Zuo
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引用次数: 0

摘要

无标记定量相位成像是生命科学各个研究领域研究体外活细胞的重要工具。数字全息显微镜(DHM)是一种非破坏性的全场显微镜技术,通过直接测量光程差来提供相位图像,这有助于细胞分割,并允许确定几个重要的细胞物理特征,如干物质。在这项工作中,我们提出了一个用于活细胞成像和形态学表征的系统分析框架,称为LAF(活细胞分析框架)。该框架中涉及的所有图像处理算法都是在我们之前提出的微离轴全息系统(FPDH)和相关重建方法获得的高分辨率无伪影定量相位图像上实现的。应用一种高度鲁棒的自动细胞分割方法来提取有效的细胞区域,然后使用活细胞分析框架算法来确定每个细胞的物理和形态特性,包括面积、周长、不规则性、体积和干质量。在活HeLa细胞上的实验证明了所提出的框架的有效性和有效性,揭示了其在多种生物医学应用中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Live-cell analysis framework for quantitative phase imaging with slightly off-axis digital holographic microscopy
Label-free quantitative phase imaging is an essential tool for studying in vitro living cells in various research fields of life sciences. Digital holographic microscopy (DHM) is a non-destructive full-field microscopy technique that provides phase images by directly measuring the optical path differences, which facilitates cell segmentation and allows the determination of several important cellular physical features, such as dry mass. In this work, we present a systematic analysis framework for live-cell imaging and morphological characterization, terms as LAF (live-cell analysis framework). All image processing algorithms involved in this framework are implemented on the high-resolution artifact-free quantitative phase images obtained by our previously proposed slightly off-axis holographic system (FPDH) and associated reconstruction methods. A highly robust automated cell segmentation method is applied to extract the valid cellular region, followed by live-cell analysis framework algorithms to determine the physical and morphological properties, including the area, perimeter, irregularity, volume and dry mass, of each individual cell. Experiments on live HeLa cells demonstrate the validity and effectiveness of the presented framework, revealing its potential for diverse biomedical applications.
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