The intravital microscopy is an important tool for the study of cellular and molecular mechanisms of leukocyte-endothelial interactions in the microcirculation of various tissues and in various inflammatory conditions. The analysis of the images, usually visually done, allows the counting and assessment of rolling and adherent to blood vessel walls leukocytes. However, visual analysis is a repetitive and time consuming task, and depending on the inflammatory response degree, the measurements accuracy can be significantly affected due to the observer's visual fatigue. One of the greatest challenges in the development of automatic methods for intravital microscopy is the stabilization and removal of motion artifacts from video movements, caused mainly by the animal's breathing. Such movement leads to momentary changes in the microscope's focal plane and, consequently, generate blurring and distortions in the images. It is believed that, by stabilizing the intravital microscopy video images, the automatic tracking of leukocytes will become more robust and it will allow the assessment of the movements of these cells. Therefore, the main objective of this research is the study of deconvolution techniques applied to the restoration of intravital microscopy video images corrupted by motion artifacts.
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