Abstract
A versatile and automated image processing technique and data extraction procedure from videomicroscopic data is presented. The motivation is a detailed quantification of blood platelet adhesion from laminar flow onto a surface. The characteristics of the system under observation (type of cells, their speed of movement, and the quality of the optical image to analyze) provided the criteria for developing a new procedure enabling tracking for long image sequences. Specific features of the novel method include: automatic segmentation methodology which removes operator bias; platelet recognition across the series of images based on a probability density function (two-dimensional, Gaussian-like) tailored to the physics of platelet motion on the surface; options to automatically tune the procedure parameters to explore different applications; integrated analysis of the results (platelet trajectories) to obtain relevant information, such as deposition and removal rates, displacement distributions, pause times and rolling velocities. Synthetic images, providing known reference conditions, are used to test the method. The algorithm operation is illustrated by application to images obtained by fluorescence microscopy of the interaction between platelets and von Willebrand factor-coated surfaces in parallel-plate flow chambers. Potentials and limits are discussed, together with evaluation of errors resulting from an inaccurate tracking.
| Original language | English |
|---|---|
| Pages (from-to) | 833-846 |
| Number of pages | 14 |
| Journal | Annals of Biomedical Engineering |
| Volume | 34 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - May 2006 |
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Keywords
- Fluorescence microscopy
- Gaussian distribution
- Image analysis
- Image simulation
- Perfusion chamber
- Platelets
ASJC Scopus subject areas
- Biomedical Engineering
Cite this
Single particle tracking across sequences of microscopical images : Application to platelet adhesion under flow. / MacHin, Marianna; Santomaso, Andrea; Mazzucato, Mario; Cozzi, Maria Rita; Battiston, Monica; De Marco, Luigi; Canu, Paolo.
In: Annals of Biomedical Engineering, Vol. 34, No. 5, 05.2006, p. 833-846.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Single particle tracking across sequences of microscopical images
T2 - Application to platelet adhesion under flow
AU - MacHin, Marianna
AU - Santomaso, Andrea
AU - Mazzucato, Mario
AU - Cozzi, Maria Rita
AU - Battiston, Monica
AU - De Marco, Luigi
AU - Canu, Paolo
PY - 2006/5
Y1 - 2006/5
N2 - A versatile and automated image processing technique and data extraction procedure from videomicroscopic data is presented. The motivation is a detailed quantification of blood platelet adhesion from laminar flow onto a surface. The characteristics of the system under observation (type of cells, their speed of movement, and the quality of the optical image to analyze) provided the criteria for developing a new procedure enabling tracking for long image sequences. Specific features of the novel method include: automatic segmentation methodology which removes operator bias; platelet recognition across the series of images based on a probability density function (two-dimensional, Gaussian-like) tailored to the physics of platelet motion on the surface; options to automatically tune the procedure parameters to explore different applications; integrated analysis of the results (platelet trajectories) to obtain relevant information, such as deposition and removal rates, displacement distributions, pause times and rolling velocities. Synthetic images, providing known reference conditions, are used to test the method. The algorithm operation is illustrated by application to images obtained by fluorescence microscopy of the interaction between platelets and von Willebrand factor-coated surfaces in parallel-plate flow chambers. Potentials and limits are discussed, together with evaluation of errors resulting from an inaccurate tracking.
AB - A versatile and automated image processing technique and data extraction procedure from videomicroscopic data is presented. The motivation is a detailed quantification of blood platelet adhesion from laminar flow onto a surface. The characteristics of the system under observation (type of cells, their speed of movement, and the quality of the optical image to analyze) provided the criteria for developing a new procedure enabling tracking for long image sequences. Specific features of the novel method include: automatic segmentation methodology which removes operator bias; platelet recognition across the series of images based on a probability density function (two-dimensional, Gaussian-like) tailored to the physics of platelet motion on the surface; options to automatically tune the procedure parameters to explore different applications; integrated analysis of the results (platelet trajectories) to obtain relevant information, such as deposition and removal rates, displacement distributions, pause times and rolling velocities. Synthetic images, providing known reference conditions, are used to test the method. The algorithm operation is illustrated by application to images obtained by fluorescence microscopy of the interaction between platelets and von Willebrand factor-coated surfaces in parallel-plate flow chambers. Potentials and limits are discussed, together with evaluation of errors resulting from an inaccurate tracking.
KW - Fluorescence microscopy
KW - Gaussian distribution
KW - Image analysis
KW - Image simulation
KW - Perfusion chamber
KW - Platelets
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UR - http://www.scopus.com/inward/citedby.url?scp=33744768636&partnerID=8YFLogxK
U2 - 10.1007/s10439-006-9086-8
DO - 10.1007/s10439-006-9086-8
M3 - Article
C2 - 16708268
AN - SCOPUS:33744768636
VL - 34
SP - 833
EP - 846
JO - Annals of Biomedical Engineering
JF - Annals of Biomedical Engineering
SN - 0090-6964
IS - 5
ER -