Abstract
To understand the dynamics of a living system, the analysis of particular and/or cellular dynamics has been performed based on shape-based center point detection. After collecting sequential time-lapse images of cellular dynamics, the trajectory of a moving object is determined from the set of center points of the cell analyzed from each image. The accuracy of trajectory is significant in understanding the stochastic nature of the dynamics of biological objects. In this study, to localize a cellular object in time-lapse images, three different localization methods, namely radial symmetry, circular Hough transform, and modified active contour, were considered. To analyze the accuracy of cellular dynamics, several statistical parameters such as mean square displacement and velocity autocorrelation function were employed, and localization error derived from these was reported for each localization method. In particular, through denoising using a Poisson noise filter, improved localization characteristics could be achieved. The modified active contour with denoising reduced localization error significantly, and thus allowed for accurate estimation of the statistical parameters of cellular dynamics.
Highlights
It has become an essential theme of biology to understand the dynamics of living systems, such as cell migration [1,2], embryogenesis [3,4], and transport of organelles within a cell [5].Characterization of living organisms can be performed by measuring their biochemical properties, and by analyzing their dynamic properties including trajectories, velocities, and diffusion coefficients
The random dynamics of a cPMS particle and MCF-7 cell recorded at a frame rate of 25 hz were measured, and sub-pixel resolution analyses were performed using three localization methods, the radial symmetric method, circular Hough transform method, and modified active contour method
To understand the effects of different image analysis methods in localizing the position of a cell in an image for random dynamics analysis, the trajectory, mean square displacement (MSD), and velocity autocorrelation function (VACF) of the measured objects were compared, and we found that the modified active contour method presented the smallest localization error compared to the other two methods considered
Summary
It has become an essential theme of biology to understand the dynamics of living systems, such as cell migration [1,2], embryogenesis [3,4], and transport of organelles within a cell [5]. Characterization of living organisms can be performed by measuring their biochemical properties, and by analyzing their dynamic properties including trajectories, velocities, and diffusion coefficients. A highly sensitive method must be developed to remove unnecessary signals such as noise through advanced filtering or an advanced device to capture a spatiotemporally high-resolution image [6,7,8]. The spatiotemporal resolution of a dynamic target object is determined by its photo-physical properties, the signal to noise ratio, and the speeds of the moving objects [9]
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