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    Bacterial cell identification in differential interference contrast microscopy images. 
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    Bacterial cell identification in differential interference contrast microscopy images.

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    Published version (3.221Mb)
    Volume
    14
    Pagination
    134 - ?
    DOI
    10.1186/1471-2105-14-134
    Journal
    BMC Bioinformatics
    Metadata
    Show full item record
    Abstract
    BACKGROUND: Microscopy image segmentation lays the foundation for shape analysis, motion tracking, and classification of biological objects. Despite its importance, automated segmentation remains challenging for several widely used non-fluorescence, interference-based microscopy imaging modalities. For example in differential interference contrast microscopy which plays an important role in modern bacterial cell biology. Therefore, new revolutions in the field require the development of tools, technologies and work-flows to extract and exploit information from interference-based imaging data so as to achieve new fundamental biological insights and understanding. RESULTS: We have developed and evaluated a high-throughput image analysis and processing approach to detect and characterize bacterial cells and chemotaxis proteins. Its performance was evaluated using differential interference contrast and fluorescence microscopy images of Rhodobacter sphaeroides. CONCLUSIONS: Results demonstrate that the proposed approach provides a fast and robust method for detection and analysis of spatial relationship between bacterial cells and their chemotaxis proteins.
    Authors
    Obara, B; Roberts, MAJ; Armitage, JP; Grau, V
    URI
    http://qmro.qmul.ac.uk/xmlui/handle/123456789/34365
    Collections
    • Centre for Medical Education [102]
    Language
    eng
    Licence information
    CC-BY
    Copyright statements
    © Obara et al.; licensee BioMed Central Ltd. 2013
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