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.
Translated title of the contribution | Detección automatizada de células fluorescentes en secciones de fluorescencia en resina para microscopía electrónica y de luz integrada |
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Original language | English |
Pages (from-to) | 109-119 |
Number of pages | 11 |
Journal | Journal of Microscopy |
Volume | 271 |
Issue number | 1 |
DOIs | |
State | Published - Jul 2018 |
Bibliographical note
Funding Information:This work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001999), the UK Medical Research Council (FC001999) and the Wellcome Trust (FC001999); by the MRC, BBSRC and EPSRC under grant award MR/K01580X/1 to LMC; and by Fondo de Ayuda a la Investigacion (FAI), Universidad de los Andes, under grant INV-IN-2017-05 to J.D.
Publisher Copyright:
© 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.
Keywords
- Cell segmentation
- correlative light and electron microscopy
- image processing
- in-resin fluorescence
- integrated light and electron microscopy
- watershed algorithm