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Interactive segmentation of clustered cells via geodesic commute distance and constrained density weighted nystrom method

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Du, Cheng-Jin, Marcello, Marco, Spiller, David G., White, Michael R. H. and Bretschneider, Till (2010) Interactive segmentation of clustered cells via geodesic commute distance and constrained density weighted nystrom method. Cytometry Part A, Vol.77A (No.12). pp. 1137-1147. doi:10.1002/cyto.a.20993

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Official URL: http://dx.doi.org/10.1002/cyto.a.20993

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Abstract

An interactive method is proposed for complex cell segmentation, in particular of clustered cells. This article has two main contributions: First, we explore a hybrid combination of the random walk and the geodesic graph based methods for image segmentation and propose the novel concept of geodesic commute distance to classify pixels. The computation of geodesic commute distance requires an eigenvector decomposition of the weighted Laplacian matrix of a graph constructed from the image to be segmented. Second, by incorporating pairwise constraints from seeds into the algorithm, we present a novel method for eigenvector decomposition, namely a constrained density weighted Nystrom method. Both visual and quantitative comparison with other semiautomatic algorithms including Voronoi-based segmentation, grow cut, graph cuts, random walk, and geodesic method are given to evaluate the performance of the proposed method, which is a powerful tool for quantitative analysis of clustered cell images in live cell imaging. (C) 2010 International Society for Advancement of Cytometry

Item Type: Journal Article
Subjects: Q Science > QD Chemistry
Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science, Engineering and Medicine > Research Centres > Warwick Systems Biology Centre
Journal or Publication Title: Cytometry Part A
Publisher: John Wiley & Sons Ltd.
ISSN: 1552-4922
Official Date: December 2010
Dates:
DateEvent
December 2010Published
Volume: Vol.77A
Number: No.12
Number of Pages: 11
Page Range: pp. 1137-1147
DOI: 10.1002/cyto.a.20993
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: European Union (BioSim Network), Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC)
Grant number: 005137, BBF0059381/BBF0058141

Data sourced from Thomson Reuters' Web of Knowledge

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