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

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 so...

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Veröffentlicht in:Machine vision and applications 2012-07, Vol.23 (4), p.691-711
Hauptverfasser: Hermann, Gilles, Coudray, Nicolas, Buessler, Jean-Luc, Caujolle-Bert, Daniel, Rémigy, Hervé-William, Urban, Jean-Philippe
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Sprache:eng
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Zusammenfassung: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.
ISSN:0932-8092
1432-1769
DOI:10.1007/s00138-011-0357-5