In vitro dynamics of chromatin organization and migration

Characterization of cell deformation and migration using a parametric estimation of image motion

This paper deals with the spatio-temporal analysis of two-dimensional deformation and motion of cells from time series of digitized video images. A parametric motion approach based on an affine model has been proposed for the quantitative characterization of cellular movements in different experimental areas of cellular biology including spontaneous cell deformation, cell mitosis, individual cell migration and collective migration of cell populations as cell monolayer. The accuracy and robustness of the affine model parameter estimation, which is based on a multiresolution algorithm, has been established from synthesized image sequences. A major interest of our approach is to follow with time the evolution of a few number of parameters characteristic of cellular motion and deformation. From the time-varying eigenvalues of the affine model square matrix, a precise quantification of the cell pseudopodial activity, as well as of cell division has been performed. For migrating cells, the motion quantification confirms that cell body deformation has a leading role in controlling nucleus displacement, the nucleus itself undergoing a larger rotational motion. At the cell population level, image motion analysis of in vitro wound healing experiments quantifies the heterogeneous cell populations dynamics.

Image cytometry in early graft-versus-host disease

Image cytometry was used to measure the size, shape, and texture of lymphocyte nuclei in 24 skin biopsy specimens retrospectively selected from patients with early, nonspecific, graft-versus-host disease (GVHD)-like eruptions. Half of these patients had progressed to overt GVHD, whereas half had never developed more than a mild nonspecific eruption. Significant differences were detected in the nuclear texture of the eruptions of the two groups, but the differences were not consistent enough to suggest that image cytometry might play a significant role in recognition of early GVHD.

A society of goal-oriented agents for the analysis of living cells

This paper presents a new model for the segmentation and analysis of living cells. A multi-agent model has been developed for this application. It is based on a generic agent model, which is composed of different behaviors: perception, interaction and reproduction. The agent is further specialized to accomplish a specific goal. Different goals are defined from the different components of the cell images. The specialization specifies the parameters of the behaviors for the achievement of the agent's goal. From these goal-oriented agents, a society is defined, and it evolves dynamically as the agents are created and deleted. An internal manager is integrated in the agent to control the behavior's execution. It makes use of an event-driven scheme to manage the behavior priorities. The present design is mainly oriented toward image segmentation, however, it includes some features on tracking and motion analysis.