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Multistage spatial property based segmentation for quantification of fluorescence distribution in cells
The University of New South Wales, Campbell, ACT 2600, Australia .
The University of New South Wales, Campbell, ACT 2600, Australia .
The University of New South Wales, Campbell, ACT 2600, Australia .ORCID iD: 0000-0002-4255-5130
Eskitis Institute for Cell and Molecular Therapies, and School of Biomolecular and Physical Sciences, Griffith University, Nathan Campus, QLD 4111, Australia .
2010 (English)Conference paper (Refereed)Text
Abstract [en]

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 offluorescence 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.

Place, publisher, year, edition, pages
2010. Vol. 1210, 3-12 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-127913DOI: 10.1063/1.3314268 OAI: oai:DiVA.org:liu-127913DiVA: diva2:928900
Conference
2009 INTERNATIONAL CONFERNECE ON COMPUTATIONAL MODELS FOR LIFE SCIENCES (CMLS-09). 28–29 July 2009 Sofia (Bulgaria)
Available from: 2016-05-17 Created: 2016-05-13 Last updated: 2016-06-02

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Pham, Tuan D
Computer Vision and Robotics (Autonomous Systems)

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ReferencesLink to record
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