ArticleJournal of microscopy2018
Automated detection of fluorescent cells in in-resin fluorescence sections for integrated light and electron microscopy.
Article in Journal of microscopy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Correlative Organelle Microscopy: Fluorescence Guided Volume Electron Microscopy of Intracellular Processes.Frontiers in cell and developmental biology · 2022Article
- Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images of Mouse Embryos Using Convolutional Neural Networks.IEEE access : practical innovations, open solutions · 2022Article
- A workflow for streamlined acquisition and correlation of serial regions of interest in array tomography.BMC biology · 2021Article
- Integrated Array Tomography for 3D Correlative Light and Electron Microscopy.Frontiers in molecular biosciences · 2021Article
- Optimization of negative stage bias potential for faster imaging in large-scale electron microscopy.Journal of structural biology: X · 2021Article
- Q&A: Array tomography.BMC biology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.