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在树脂荧光切片中自动检测荧光细胞,用于整合光镜和电镜。

Automated detection of fluorescent cells in in-resin fluorescence sections for integrated light and electron microscopy.

机构信息

School of Engineering and Applied Sciences, Universidad de los Andes, Santiago, Chile.

Department of Computer Science, University College London, London, United Kingdom.

出版信息

J Microsc. 2018 Jul;271(1):109-119. doi: 10.1111/jmi.12700. Epub 2018 Apr 26.

Abstract

Integrated array tomography combines fluorescence and electron imaging of ultrathin sections in one microscope, and enables accurate high-resolution correlation of fluorescent proteins to cell organelles and membranes. Large numbers of serial sections can be imaged sequentially to produce aligned volumes from both imaging modalities, thus producing enormous amounts of data that must be handled and processed using novel techniques. Here, we present a scheme for automated detection of fluorescent cells within thin resin sections, which could then be used to drive automated electron image acquisition from target regions via 'smart tracking'. The aim of this work is to aid in optimization of the data acquisition process through automation, freeing the operator to work on other tasks and speeding up the process, while reducing data rates by only acquiring images from regions of interest. This new method is shown to be robust against noise and able to deal with regions of low fluorescence.

摘要

整合式面扫电子显微镜技术将荧光和电子显微镜超微切片成像整合在一台显微镜中,可实现荧光蛋白与细胞细胞器和膜的高精度高分辨率关联。大量的连续切片可以顺序成像,从而从两种成像模式产生对齐的体积,从而产生必须使用新技术处理和处理的大量数据。在这里,我们提出了一种在薄树脂切片中自动检测荧光细胞的方案,然后可以通过“智能跟踪”来驱动从目标区域自动获取电子图像。这项工作的目的是通过自动化来辅助优化数据采集过程,使操作人员可以自由地处理其他任务并加快处理速度,同时通过仅从感兴趣区域获取图像来降低数据速率。该新方法被证明对噪声具有鲁棒性,并且能够处理荧光强度低的区域。

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