Automated Motion Tracking and Data Extraction for Red Blood Cell Biomechanics.
Arun Kumar, Brendan R Schmidt, Zyrina Alura C Sanchez, Feyza Yazar, Ronald W Davis, Anand K Ramasubramanian, Amit K Saha
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Abstract
Red blood cell biomechanics can provide us with a deeper understanding of macroscopic physiology and have the potential of being used for diagnostic purposes. In diseases like sickle cell anemia and malaria, reduced red blood cell deformability can be used as a biomarker, leading to further assays and diagnoses. A microfluidic system is useful for studying these biomechanical properties. We can observe detailed red blood cell mechanical behavior as they flow through microcapillaries using high-speed imaging and microscopy. Microfluidic devices are advantageous over traditional methods because they can serve as high-throughput tests. However, to rapidly analyze thousands of cells, there is a need for powerful image processing tools and software automation. We describe a workflow process using Image-Pro to identify and track red blood cells in a video, take measurements, and export the data for use in statistical analysis tools. The information in this protocol can be applied to large-scale blood studies where entire cell populations need to be analyzed from many cohorts of donors. © 2020 The Authors. Basic Protocol 1: Enhancing raw video for motion tracking Basic Protocol 2: Extracting motion tracking data from enhanced video.
红细胞生物力学的自动运动跟踪和数据提取。
红细胞生物力学可以为我们提供对宏观生理学的更深入的理解,并具有用于诊断目的的潜力。在镰状细胞性贫血和疟疾等疾病中,红细胞变形能力降低可以作为一种生物标志物,用于进一步的检测和诊断。微流体系统有助于研究这些生物力学特性。我们可以使用高速成像和显微镜观察红细胞在微血管中流动时的详细力学行为。微流控装置优于传统方法,因为它们可以作为高通量测试。然而,要快速分析数千个细胞,需要强大的图像处理工具和自动化软件。我们描述了使用Image-Pro识别和跟踪视频中的红细胞的工作流程,进行测量,并导出数据用于统计分析工具。该方案中的信息可应用于大规模血液研究,其中需要分析来自许多献血者队列的整个细胞群。©2020作者。基本协议1:增强运动跟踪的原始视频。基本协议2:从增强的视频中提取运动跟踪数据。
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