Machine Vision and Applications

, Volume 23, Issue 4, pp 691–711 | Cite as

ANIMATED-TEM: a toolbox for electron microscope automation based on image analysis

  • Gilles Hermann
  • Nicolas Coudray
  • Jean-Luc Buessler
  • Daniel Caujolle-Bert
  • Hervé-William Rémigy
  • Jean-Philippe UrbanEmail author
Special Issue Paper


To automate electron microscopy tasks, the main challenge is to integrate image interpretation. This article presents a first achievement in the domain of electron microscopy. ANalysis of IMages for Automatic Targeting and Extraction of Data in Transmission Electron Microscopy (ANIMATED-TEM) is a software toolbox composed of a set of image analysis algorithms and an examination scenario. Combined with microscope software, it runs all the microscope tasks and manages the exploration strategy of the carbon-coated grids on which the sample of interest (viruses, proteins, bi-dimensional crystal of membrane proteins, etc.) has been deposited. ANIMATED-TEM realizes the automatic examination of biological samples, working at several magnifications without human intervention. Online image analysis of micrographs is an essential part both to extract characteristic data and to manage automation, as interesting regions need to be identified to trigger new acquisitions at higher magnifications. This toolbox has been developed to perform high-throughput screening of 2D-crystallization experiments. It is operational on a microscope equipped with an automatic grid loading system, allowing the continuous and automatic analysis of up to 96 samples. Intensive testing over a period of several months confirms that ANIMATED-TEM achieves full automation with an efficient target selection and in a suitable computational time.


Automated image acquisition Transmission electron microscope Target selection Specimen characterization Fully automated electron microscope 


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  1. 1.
    Suloway C., Pulokas J., Fellmann D., Cheng A., Guerra F., Quispe J., Stagg S., Potter C.S., Carragher B.O.: Automated molecular microscopy: the new Leginon system. J. Struct. Biol. 151, 41–60 (2005)CrossRefGoogle Scholar
  2. 2.
    Zhang J., Nakamura N., Shimizu Y., Liang N., Liu X., Jakana J., Marsh M.P., Booth C.R., Shinkawa T., Nakata M., Chiu W.: JADAS: a customizable automated data acquisition system and its application to ice-embedded single particles. J. Struct. Biol. 165, 1–9 (2009)CrossRefGoogle Scholar
  3. 3.
    Nickell S., Förster F., Linaroudis A., Del Net W., Beck F., Hegerl R., Baumeister W., Plitzko J.M.: TOM software toolbox: acquisition and analysis for electron tomography. J. Struct. Biol. 149, 227–234 (2005)CrossRefGoogle Scholar
  4. 4.
    Potter C.S., Pulokas J., Smith P., Suloway C., Carragher B.: Robotic grid loading system for a transmission electron microscope. J. Struct. Biol. 146, 431–440 (2004)CrossRefGoogle Scholar
  5. 5.
    Lefman J., Morrison R., Subramaniam S.: Automated 100-position specimen loader and image acquisition system for transmission electron microscopy. J. Struct. Biol. 158, 318–326 (2007)CrossRefGoogle Scholar
  6. 6.
    Coudray N., Hermann G., Caujolle-Bert D., Karathanou A., Erne-Brand F., Buessler J.-L., Daum P., Plitzko J., Chami M., Mueller U., Kihl H., Urban J.-P., Engel A., Rémigy H.-W.: Automated screening of 2D crystallization trials using transmission electron microscopy: a high-throughput tool-chain for sample preparation and microscopic analysis. J. Struct. Biol. 173(2), 365–374 (2011)CrossRefGoogle Scholar
  7. 7.
    Koster A.J., Chen H., Sedat J.W., Agard D.A.: Automated microscopy for electron tomography. Ultramicroscopy 46, 207–227 (1992)CrossRefGoogle Scholar
  8. 8.
    Fan G.Y., Mercurio P.J., Young S.J., Ellisman M.H.: Telemicroscopy. Ultramicroscopy 52, 499–503 (1993)CrossRefGoogle Scholar
  9. 9.
    Kisseberth N., Whittaker M., Weber D., Potter C.S., Carragher B.O.: emScope: a tool kit for control and automation of a remote electron microscope. J. Struct. Biol. 120, 309–319 (1997)CrossRefGoogle Scholar
  10. 10.
    Fung J.C., Liu W., Ruijter W.J.d., Chen H., Abbey C.K., Sedat J.W., Agard D.A.: Toward fully automated high-resolution electron tomography. J. Struct. Biol. 116, 181–189 (1996)CrossRefGoogle Scholar
  11. 11.
    Dierksen K., Typke D., Hegerl R., Walz J., Sackmann E., Baumeister W.: 3-Dimensional structure of lipid vesicles embedded in vitreous ice and investigated by automated electron tomography. Biophys. J. 68, 1416–1422 (1995)CrossRefGoogle Scholar
  12. 12.
    Mastronarde D.N.: Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005)CrossRefGoogle Scholar
  13. 13.
    Oostergetel G.T., Keegstra W., Brisson A.: Automation of specimen selection and data acquisition for protein electron crystallography. Ultramicroscopy 74, 47–59 (1998)CrossRefGoogle Scholar
  14. 14.
    Anderson J.R., Jones B.W., Yang J.-H., Shaw M.V., Watt C.B., Koshevoy P., Spaltenstein J., Jurrus E., UV K., Whitaker R.T., Mastronarde D., Tasdizen T., Marc R.E.: A computational framework for ultrastructural mapping of neural circuitry. Plos Biol. 7, 493–512 (2009)CrossRefGoogle Scholar
  15. 15.
    Baker T.S., Cheng R.H.: A model-based approach for determining orientations of biological macromolecules imaged by cryoelectron microscopy. J. Struct. Biol. 116, 120–130 (1996)CrossRefGoogle Scholar
  16. 16.
    Nicholson W.V., Glaeser R.M.: Automatic particle detection in electron microscopy. J. Struct. Biol. 133, 90–101 (2001)CrossRefGoogle Scholar
  17. 17.
    Suloway C., Shi J., Cheng A., Pulokas J., Carragher B., Potter C.S., Zheng S.Q., Agard D.A., Jensen G.J.: Fully automated, sequential tilt-series acquisition with Leginon. J. Struct. Biol. 167, 11–18 (2009)CrossRefGoogle Scholar
  18. 18.
    Zheng S.Q., Keszthelyi B., Branlund E., Lyle J.M., Braunfeld M.B., Sedat J.W., Agard D.A.: UCSF tomography: an integrated software suite for real-time electron microscopic tomographic data collection, alignment, and reconstruction. J. Struct. Biol. 157, 138–147 (2007)CrossRefGoogle Scholar
  19. 19.
    Shi J., Williams D.R., Stewart P.L.: A script assisted microscopy (SAM) package to improve data acquisition rates on FEI tecnai electron microscopes equipped with Gatan CCD cameras. J. Struct. Biol. 164, 166–169 (2008)CrossRefGoogle Scholar
  20. 20.
    Lei J.L., Frank J.: Automated acquisition of cryo-electron micrographs for single particle reconstruction on an FEI Tecnai electron microscope. J. Struct. Biol. 150, 69–80 (2005)CrossRefGoogle Scholar
  21. 21.
    Stagg S.M., Lander G.C., Pulokas J., Fellmann D., Cheng A., Quispe J.D., Mallick S.P., Avila R.M., Carragher B.O., Potter C.S.: Automated cryoEM data acquisition and analysis of 284 742 particles of GroEL. J. Struct. Biol. 155, 470–481 (2006)CrossRefGoogle Scholar
  22. 22.
    Cheng A., Leung A., Fellmann D., Quispe J., Suloway C., Pulokas J., Carragher B., Potter C.S.: Towards automated screening of two-dimensional crystals. J. Struct. Biol. 160, 324–331 (2007)CrossRefGoogle Scholar
  23. 23.
    Hu M., Vink M., Kim C., Derr K., Koss J., D’Amico K., Cheng A., Pulokas J., Ubarretxena-Belandia I., Stokes D.: Automated electron microscopy for evaluating two-dimensional crystallization of membrane proteins. J. Struct. Biol. 171, 102–110 (2010)CrossRefGoogle Scholar
  24. 24.
    Kylberg, G., Sintorn, I.-M., and Borgefors, G.: Towards automated TEM for virus diagnostics: segmentation of grid squares and detection of regions of interest. Image Analysis, Lecture Notes in Computer Science, vol. 5575, pp. 169–178 (2009). doi: 10.1007/978-3-642-02230-2_18
  25. 25.
    Karathanou, A., Coudray, N., Hermann, G., Buessler, J.L., Urban, J.P.: Automatic TEM image analysis of membranes for 2D crystal detection. In: Arabnia, H.R. (ed.) Advances in Computational Biology, vol. 680. Springer AEMB, Berlin (2010)Google Scholar
  26. 26.
    Coudray N., Buessler J.L., Urban J.P.: A robust thresholding algorithm for unimodal image histograms. Pattern Recogn. Lett. 31, 1010–1019 (2010)CrossRefGoogle Scholar
  27. 27.
    Coudray, N., Buessler, J.-L., Kihl, H., Urban, J.P.: Multi-scale and first derivative analysis for edge detection in TEM images. In: 4th International Conference on Image Analysis and Recognition (ICIAR 2007), Montréal, Canada, pp. 1005–1016 (2007)Google Scholar
  28. 28.
    Karathanou, A., Buessler, J.-L., Kihl, H., Urban, J.P.: Detection of low contrasted membranes in electron microscope images: statistical contour validation. In: Digital Imaging Sensors and Applications, Part of the Imaging Science and Technology/SPIE, 21th Annual Symposium on Electronic Imaging, San Jose, USA (2009)Google Scholar
  29. 29.
    Hermann, G., Coudray, N., Karathanou, A., Buessler, J.L., Urban, J.P.: Autoadaptive algorithm for the stacking-level estimation of membranes in TEM images. ISRN Signal Processing, vol. 2011, p. 10, Article ID 650546 (2011)Google Scholar
  30. 30.
    Meyer F.: Topographic distance and watershed lines. Signal Process. 38, 113–125 (1994)zbMATHCrossRefGoogle Scholar
  31. 31.
    Hermann, G., Kihl, H., Urban, J.P.: Detection and characterization of vesicles in EM images. In: The 2010 International Conference on Bioinformatics and Computational Biology (Biocomp), Las Vegas, USA (2010)Google Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Gilles Hermann
    • 1
  • Nicolas Coudray
    • 1
  • Jean-Luc Buessler
    • 1
  • Daniel Caujolle-Bert
    • 2
  • Hervé-William Rémigy
    • 2
    • 3
  • Jean-Philippe Urban
    • 1
    Email author
  1. 1.MIPS laboratoryUniversity of Haute AlsaceMulhouseFrance
  2. 2.C-CINA, M.E. Mueller Institute for Structural BiologyBiozentrum, University of BaselBaselSwitzerland
  3. 3.FEI Electron Optics BVEindhovenThe Netherlands

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