使用珠子作为焦点基准来帮助显微镜中基于软件的自动对焦精度。

IF 1.1 Q3 BIOLOGY
Isabel Gibson, Elizabeth Julie Osterlund, Ray Truant
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引用次数: 0

摘要

亮场显微镜是一种理想的应用研究活细胞系统在一个微创的方式。这有利于长期实验研究动态细胞过程,如应激反应。根据样品类型和制备方法的不同,明场显微镜的固有特性是对比度非常低,这可能导致焦点漂移、测序滞后和软件自动对焦系统完全失败等技术问题。在这里,我们描述了使用微珠作为长期活细胞成像的焦点辅助,以解决这些自动聚焦问题。该方案实施成本低廉,无需大量额外的样品制备,并可用于以无标记方式捕获透明细胞的聚焦图像。为了验证该方案,使用宽视场倒置显微镜和基于软件的自动对焦在夜间以延时格式成像,展示了珠子在长期实验中防止焦点漂移的使用。这提高了相对便宜的显微镜的自动对焦精度,而无需使用基于硬件的对焦辅助。为了验证该协议,使用KNIME物流软件训练随机森林模型进行二值图像分类。主要特点•无标签活细胞成像的延时格式。•排除软件自动对焦的亮场模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Using Beads as a Focus Fiduciary to Aid Software-Based Autofocus Accuracy in Microscopy.

Using Beads as a Focus Fiduciary to Aid Software-Based Autofocus Accuracy in Microscopy.

Using Beads as a Focus Fiduciary to Aid Software-Based Autofocus Accuracy in Microscopy.

Using Beads as a Focus Fiduciary to Aid Software-Based Autofocus Accuracy in Microscopy.

Brightfield microscopy is an ideal application for studying live cell systems in a minimally invasive manner. This is advantageous in long-term experiments to study dynamic cellular processes such as stress response. Depending on the sample type and preparation, the inherent qualities of brightfield microscopy, being very low contrast, can contribute to technical issues such as focal drift, sequencing lags, and complete failure of software autofocus systems. Here, we describe the use of microbeads as a focus aid for long-term live cell imaging to address these autofocus issues. This protocol is inexpensive to implement, without extensive additional sample preparation, and can be used to capture focused images of transparent cells in a label-free manner. To validate this protocol, a widefield inverted microscope was used with software-based autofocus to image overnight in time-lapse format, demonstrating the use of the beads to prevent focal drift in long-term experiments. This improves autofocus accuracy on relatively inexpensive microscopes without using hardware-based focus aids. To validate this protocol, the KNIME logistics software was used to train a random forest model to perform binary image classification. Key features • Label-free live cell imaging in time-lapse format. • Troubleshooting software autofocus for brightfield mode.

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CiteScore
1.50
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