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Software tools for automated transmission electron microscopy.

Martin SchorbIsabella HaberboschWim J H HagenYannick SchwabDavid N Mastronarde
Published in: Nature methods (2019)
The demand for high-throughput data collection in electron microscopy is increasing for applications in structural and cellular biology. Here we present a combination of software tools that enable automated acquisition guided by image analysis for a variety of transmission electron microscopy acquisition schemes. SerialEM controls microscopes and detectors and can trigger automated tasks at multiple positions with high flexibility. Py-EM interfaces with SerialEM to enact specimen-specific image-analysis pipelines that enable feedback microscopy. As example applications, we demonstrate dose reduction in cryo-electron microscopy experiments, fully automated acquisition of every cell in a plastic section and automated targeting on serial sections for 3D volume imaging across multiple grids.
Keyphrases
  • electron microscopy
  • high throughput
  • deep learning
  • machine learning
  • single cell
  • high resolution
  • artificial intelligence
  • data analysis
  • working memory
  • bone marrow
  • optical coherence tomography