3D deconvolution microscopy is a combination of optical and computational techniques that are used to maximize the observed resolution and signal from a biological specimen. Mathematical models are used to predict the distribution of out-of-focus light caused by the inherent optical limitations of the instrument, which can then be compensated for using computer algorithms. This unit will review the theory of image formation and characteristics of the point spread function (PSF) based on the instrument modality and objective lens parameters. A variety of commonly used deblurring and deconvolution methods are described, and their applications to sample datasets are illustrated to show the performance of each algorithm. Steps for setting up the image acquisition to acquire data suitable for deconvolution are described, and the challenge of maximizing signal levels while minimizing light exposure addressed. Deconvolution examples from widefield epi-fluorescence and laser scanning confocal are shown, and suitability for other modalities discussed.
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