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Detection and Segmentation of Nucleoids Based on Gradient Path Labelling

João Santinha1, André D. Mora1, José Fonseca1, Nádia Gonçalves2 and Andre S. Ribeiro2
1 Computational Intelligence Research Group (CA3), UNINOVA – Centre of Technology and Systems, Caparica, Portugal
2 Laboratory of Biosystem Dynamics – Department of Signal Processing, Tampere University of Technology, Tampere, Finland

Abstract—Cellular aging is one of the topics that live cell imaging can assist. With age, there is an increase of aggregates of misfolded proteins, to which age-related diseases have been linked to. In Escherichia coli, protein aggregates linked to its aging process exhibit a spatial distribution that appears to be caused by the nucleoid at midcell. To correlate the locations of protein aggregates and the nucleoid, it is necessary to detect and segment the nucleoid from microscopy images. We present an adaptation of methods for Drusens’ detection and segmentation to nucleoids in E. coli. The size of the nucleoid, extracted using the method here proposed, was compared with an alternative measure (FWHM-based measure) and with the regions of anisotropies in aggregates motions. These comparisons suggest that our new method is of use, providing more accurate minor axis lengths. Also, it provides additional measures, such as the nucleoid’s center orientation angle, area, and pixel list.

Index Terms—Escherichia coli, cellular aging, nucleoid detection, nucleoid segmentation

Cite: João Santinha, André D. Mora, José Fonseca, Nádia Gonçalves and Andre S. Ribeiro, "Detection and Segmentation of Nucleoids Based on Gradient Path Labelling," International Journal of Pharma Medicine and Biological Sciences, Vol. 4, No. 1, pp. 51-55, January 2015.
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