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Your selection: Cell analysis

Cell analysisLemnaTec Scanalyzer HTS systems are mainly used in those parts of medical and drug screening programmes where the objects or areas to be screened per sample are too large for microscopes or too inhomogeneous for the measurement of spectra in specific points. In theses cases LemnaTec provides its expertise of whole organism assessment which in this case includes screening of cell colony growth on agar absorbed on surfaces. The high depth of field for the specialised optics provides excellent images without or only with a minimised need to refocus, for example in single well imaging of 96-well plates. The meniscus in such samples or cells in different agar layers can be much better kept in focus than it would ever be possible with microscopes optimised for much higher resolutions.

The LemnaCount software package provides the framework – a reliable quantification of high-throughput screening tests for non-mobile organisms. Depending on the type of test a broad set of parameters, e. g. number, size, colour or covered area/size is measured. These parameters provide a comprehensive quantitative response pattern against toxicants, more than meeting the requirements of conventional yes/no- or classifying schemes.

In addition to image analysis, LemnaTec provides positioning inlays for the specific test vessels. Consultancy for result interpretation can also be supplied, if desired. Data is stored consistently, in accordance with quality insurance protocols, in the LemnaBase database. Raw data can be further transformed mathematically into e. g. growth rates and inhibition values by using the LemnaMiner. The results can then be reorganised into exportable files for further processing with specific statistical programmes. Alternatively, data can be directly transferred to other databases by customised data exchange protocols.

The use of the LemnaTec Scanalyzer HTS allows testing in a wide range of vessels, from petri dishes to multiwell plates up to 96 wells, in some cases even larger well numbers per plate. In all cases backlight, top light, dark field illumination or customised light sources may be implemented. If necessary, movement can be induced in mobilised organisms by using UV-light or heat sources.

The immense flexibility of the LemnaTec hard- and software systems represents an investment targeted at the future, even under changing requirements.

Hardware

  • Scanalyzer HTS

    The scanalyzer HTS is the best option for the analysis of small plants in multiwell plates or trays in specific growth chambers.

Software

  • LemnaCount

    For large numbers of biological objects to be quantified according to number, size, shape or colour.

  • LemnaBase

    The core database structure based on Oracle or Linux PostgreSQL technology can handle datasets of up to 100 TB.

  • LemnaControl

    Monitoring the fully integrated automatisation of all LemnaTec scanalyzer systems.

  • LemnaMiner

    The LemnaMiner extracts data from -LemnaTec databases and employs user-friendly tools to organise and visualise them.

  • LemnaLauncher

    This comprehensive and intuitive interface manages all LemnaTec products.
     

  • LemnaShare

    LemnaGrid image analysis grids can be supplied online, as well as shared and exchanged, by using the LemnaGrid exchange interface.

  • LemnaGrid

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    The demands in phenotyping are very wide ranged and strongly depend on the field of research and of course on the species. To cover all applications LemnaTec provides an Image processing toolbox called LemnaGrid. This toolbox is a graphical dataflow programming language (similar to LabView or Microsoft Robotics Studio) that can easily connect different algorithms and extract the desired properties from the original image.

    To fulfill the needs of High Throughput image processing the Image processing chains (grids) are usually designed for some reference images for a certain species and can then be applied to whole datasets consisting of thousands of images.

    In each Image processing chain there are four typical steps to extract properties from the image

     

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    Load Reference Image

    One or multiple reference images are loaded. These Images should represent the average and extreme case to make the grid cover all possible images in the dataset that is later applied.

     

     

     

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    Separate Object from background

    There are plenty of algorithms available to separate the object from the background. In addition to simple techniques like picking background color from the RGB color space, there are also more advanced concepts using HIS, LUV or LAB color spaces.

     

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    Attach desired Properties

    As soon as the object is separated from the background it contains a lot of mathematical properties such as size, length, width and many more.

    Other carameters can be attached to the objects as well using additional algorithm such as color classification or skeleton information.

     

     

     

     

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    Save results to Database

    The so called Database Writer gives the user the choice what information he wants to store in the Database. The general choice to make is whether to store all available properties of the extracted objects or just an overview containing the size and some other basic parameters.