The understanding about cells behavior and its interaction with the medium has become fundamental in order to design therapies and drugs to maintain health of living. Endothelial cells cover the inner surface of blood vessels and cardiac cavities and they achieve a wide variety of functions as the vascular tone regulation, inflammatory reactions, fibrinolysis and coagulation. Proliferation and migration of endothelial cells are strongly regulated by its intracellular calcium ([Ca]2+i ) concentration. Those essential functions are altered when the endothelium is damaged by some diseases as diabetes mellitus which is a public health problem that is increasing at alarming rate not only in Mexico but also worldwide. Hence the importance of modeling the endothelial cells behavior under different stimuli. In this thesis a proposal to automate the intracellular calcium profiles extraction from fluorescence image sequences of endothelial tissue is presented. Digital image processing techniques, as adaptive binarization, were joined with a multi-target tracking scheme supported by Kalman state estimation. Each component of the proposed system is explained below. The system was tested with image sequences from two different stimuli. Results showed consistency in the extracted data and validated the need of the tracking scheme. Two important contributions of this work are the automatic relocation of the regions of interest assigned to the cells and the possibility of a massive data extraction.