Accumulative Difference Image Protocol for Particle Tracking in Fluorescence Microscopy Tested in Mouse Lymphonodes

Carlo E Villa, Michele Caccia, Laura Sironi, Laura D'Alfonso, Maddalena Collini, Ilaria Rivolta, Giuseppe Miserocchi, Tatiana Gorletta, Ivan Zanoni, Francesca Granucci and Giuseppe Chirico

PLOS ONE, 2010, vol. 5, issue 8, 1-13

Abstract: The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done.

Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0012216

DOI: 10.1371/journal.pone.0012216

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