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Recognition and analysis of cell nuclear phases for high-content screening based on morphological features
School of Design, Communication and Information Technology, The University of Newcastle, Callaghan, NSW 2308, Australia.
School of Information Technology and Electrical Engineering, ADFA, The University of New South Wales, Canberra, ACT 2600, Australia.ORCID iD: 0000-0002-4255-5130
HCNR Centre for Bioinformatics, Harvard Medical School, Boston, MA 02215, USA.
HCNR Centre for Bioinformatics, Harvard Medical School, Boston, MA 02215, USA.
2009 (English)In: NOVA. The University of Newcastle’s Digital Repository, ISSN 0031-3203, Vol. 42, no 4, 498-508 p.Article in journal (Refereed) Published
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Abstract [en]

Automated analysis of molecular images has increasingly become an important research in computational life science. In this paper some new and efficient algorithms for recognizing and analyzing cell phases of high-content screening are presented. The conceptual frameworks are based on the morphological features of cell nuclei. The useful preprocessing includes: smooth following and linearization; extraction of morphological structural points; shape recognition based morphological structure; issue of touching cells for cell separation and reconstruction. Furthermore, the novel detecting and analyzing strategies of feed-forward and feed-back of cell phases are proposed based on gray feature, cell shape, geometrical features and difference information of corresponding neighbor frames. Experiment results tested the efficiency of the new method.

Place, publisher, year, edition, pages
2009. Vol. 42, no 4, 498-508 p.
Keyword [en]
Nuclei phases;Cell screening;Feature extraction;Morphological feature;Feed-forward detection;Feed-back detection;Shape recognition;
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-125045DOI: 10.1016/j.patcog.2008.08.003OAI: oai:DiVA.org:liu-125045DiVA: diva2:902719
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-02-24

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Pham, Tuan D
Medical Image Processing

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Citation style
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