Segmentation of Dense 2D Bacilli Populations

Bacteria outnumber all other known organisms by far so there is considerable interest in characterizing them in detail and in measuring their diversity, evolution, and dynamics. Here, we present a system capable of identifying rod-like bacteria (bacilli) correctly in high resolution phase contrast i...

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Bibliographic Details
Published in:	2010 International Conference on Digital Image Computing: Techniques and Applications pp. 82 - 86
Main Authors:	Vallotton, P, Turnbull, L, Whitchurch, C, Mililli, L
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-12-2010
Subjects:	Bacteria Bayesian Detectors image analysis Image edge detection Image segmentation Microorganisms Microscopy motility phenotype probability segmentation Shape Skeleton
Online Access:	Get full text
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Summary:	Bacteria outnumber all other known organisms by far so there is considerable interest in characterizing them in detail and in measuring their diversity, evolution, and dynamics. Here, we present a system capable of identifying rod-like bacteria (bacilli) correctly in high resolution phase contrast images. We use a probabilistic model together with several purpose-designed image features in order to split bacteria at the septum consistently. Our method commits less than 1% error on test images. Our method should also be applicable to study dense 2D systems composed of elongated elements, such as some viruses, molecules, parasites (plasmodium, euglena), diatoms, and crystals.
ISBN:	9781424488162 1424488168
DOI:	10.1109/DICTA.2010.23