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Accumulative difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes.


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.

SUBMITTER: Villa CE 

PROVIDER: S-EPMC2923183 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Accumulative difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes.

Villa Carlo E CE   Caccia Michele M   Sironi Laura L   D'Alfonso Laura L   Collini Maddalena M   Rivolta Ilaria I   Miserocchi Giuseppe G   Gorletta Tatiana T   Zanoni Ivan I   Granucci Francesca F   Chirico Giuseppe G  

PloS one 20100817 8


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 segment  ...[more]

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