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Thefluorescence microscope is routinely used to study cellular structure in many biomedical research laboratories and is increasingly used as a quantitative assay system for cellular dynamics. One of the major causes of image degradation in the fluorescence microscope is blurring. Deconvolution algorithms use a model of the microscope imaging process to either subtract or reassign out-of-focus blur. A variety of algorithms are now commercially available, each with its own characteristic advantages and disadvantages. In this article, we review the imaging process in the fluorescence microscope and then discuss how the various deconvolution methods work. Finally, we provide a summary of practical tips for using deconvolution and discuss imaging artifacts and how to minimize them.
Wallace et al. (Thu,) studied this question.