Literature DB >> 17280944

Fast automatic segmentation of nuclei in microscopy images of tissue sections.

V Laurain1, H Ramoser, C Nowak, G Steiner, R Ecker.   

Abstract

In this paper, we present a segmentation method for nuclei in microscopy images of tissue sections. The proposed method is completely automatic and performs well in the conflicting aims of speed efficiency, detection accuracy and shape fitting. It proposes an efficient alternative to existing methods ([1], [4]), in achieving the three main usual segmentation steps: (i) background extraction, (ii) seed finding and (iii) seed growing. Eventually, some significant results are depicted and discussed.

Year:  2005        PMID: 17280944     DOI: 10.1109/IEMBS.2005.1617199

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Automatic nuclei segmentation and spatial FISH analysis for cancer detection.

Authors:  Kaustav Nandy; Prabhakar R Gudla; Karen J Meaburn; Tom Misteli; Stephen J Lockett
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2009

2.  Immune Cell and Cell Cluster Phenotyping, Quantitation, and Visualization Using In Silico Multiplexed Images and Tissue Cytometry.

Authors:  Kim R M Blenman; Marcus W Bosenberg
Journal:  Cytometry A       Date:  2018-11-23       Impact factor: 4.355

  2 in total

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