Segmentation of Dense 2D Bacilli Populations

Publisher:
IEEE xplore
Publication Type:
Conference Proceeding
Citation:
2010 International Conference on Digital Image Computing: Techniques and Applications, 2010, pp. 82 - 86
Issue Date:
2010-01
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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.
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