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.
| Original language | English |
|---|---|
| Article number | e12216 |
| Journal | PLoS One |
| Volume | 5 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2010 |
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ASJC Scopus subject areas
- Agricultural and Biological Sciences(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Medicine(all)
Cite this
Accumulative Difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes. / Villa, Carlo E.; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe.
In: PLoS One, Vol. 5, No. 8, e12216, 2010.Research output: Contribution to journal › Article
}
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
VL - 5
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 8
M1 - e12216
ER -