TY - JOUR
T1 - Accumulative Difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes
AU - Villa, Carlo E.
AU - Caccia, Michele
AU - Sironi, Laura
AU - D'Alfonso, Laura
AU - Collini, Maddalena
AU - Rivolta, Ilaria
AU - Miserocchi, Giuseppe
AU - Gorletta, Tatiana
AU - Zanoni, Ivan
AU - Granucci, Francesca
AU - Chirico, Giuseppe
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
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U2 - 10.1371/journal.pone.0012216
DO - 10.1371/journal.pone.0012216
M3 - Article
C2 - 20808918
AN - SCOPUS:77957870093
VL - 5
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 8
M1 - e12216
ER -