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  • Multistage Spatial Property Based Segmentation for Quantification of Fluorescence Distribution in Cells

    Author(s)
    Zhang, Guangyun
    Jia, Xiuping
    Pham, Tuan D
    Crane, Denis I
    Griffith University Author(s)
    Crane, Denis I.
    Year published
    2010
    Metadata
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    Abstract
    The interpretation of the distribution of fluorescence in cells is often by simple visualization of microscope-derived images for qualitative studies. In other cases, however, it is desirable to be able to quantify the distribution of fluorescence using digital image processing techniques. In this paper, the challenges of fluorescence segmentation due to the noise present in the data are addressed. We report that intensity measurements alone do not allow separation of overlapping data between target and background. Consequently, spatial properties derived from neighborhood profile were included. Mathematical Morphological ...
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    The interpretation of the distribution of fluorescence in cells is often by simple visualization of microscope-derived images for qualitative studies. In other cases, however, it is desirable to be able to quantify the distribution of fluorescence using digital image processing techniques. In this paper, the challenges of fluorescence segmentation due to the noise present in the data are addressed. We report that intensity measurements alone do not allow separation of overlapping data between target and background. Consequently, spatial properties derived from neighborhood profile were included. Mathematical Morphological operations were implemented for cell boundary extraction and a window based contrast measure was developed for fluorescence puncta identification. All of these operations were applied in the proposed multistage processing scheme. The testing results show that the spatial measures effectively enhance the target separability.
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    Conference Title
    2009 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL MODELS FOR LIFE SCIENCES (CMLS '09)
    Volume
    1210
    Issue
    4
    DOI
    https://doi.org/10.1063/1.3314268
    Subject
    Image processing
    Publication URI
    http://hdl.handle.net/10072/31022
    Collection
    • Conference outputs

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