NDLI: Watershed deconvolution for cell segmentation

Content Provider	IEEE Xplore Digital Library
Author	Kachouie, Nezamoddin N. Fieguth, Paul Jervis, Eric
Copyright Year	2008
Description	Author affiliation: Department of Chemical Engineering, University of Waterloo, Canada (Jervis, Eric) \|\| Department of Systems Design Engineering, University of Waterloo, Canada (Kachouie, Nezamoddin N.; Fieguth, Paul)
Abstract	Cell segmentation and/or localization is the first stage of a (semi)automatic tracking system. We addressed the cell localization problem in our previous work where we characterized a typical blood stem cell in a microscopic image as an approximately circular object with dark interior and bright boundary. We also addressed the modelling of adjacent and dividing cells in our previous work as a deconvolution method to model individual blood stem cell as well as adjacent and dividing blood stem cells where an optimization algorithm was combined with a template matching method to segment cell regions and locate the cell centers. Our previous cell deconvolution method is capable of modelling different cell types with changes in the model parameters. However in cases where either a complex parameterized shape is needed to model a specific cell type, or in place of cell center localization, an exact cell segmentation is needed, this method will not be effective. In this paper we propose a method to achieve cell boundary segmentation. Considering cell segmentation as an inverse problem, we assume that cell centers are located in advance. Then, the cell segmentation will be solved by finding cell regions for optimal representation of cell centers while a template matching method is effectively employed to localize cell
Starting Page	375
Ending Page	378
File Size	576834
Page Count	4
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4649168
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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