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Guides and Tutorials

Image Analysis

How should I save my images?

It can be difficult to observe specimens with very weak fluorescence or those that photobleach easily using a confocal microscope. Standard epifluorescence imaging is often a method of choice for these objects. Deconvolution is a computational image restoration technique that can remove the out-of-focus blur typical for epifluorescence images and improve both lateral and axial resolution. Deconvolution is best suited for relatively thin specimens (microorganisms, single cells, tissue sections) where it can bring significant improvement in resolution and contrast.

The MIC offers AutoQuant X software with several processing algorithm including the iterative blind deconvolution for wide-field fluorescence images. This software can be used in our computer lab free of charge.

For more information on deconvolution and for help with image acquisition for deconvolution

please contact Dr. Stanislav Vitha, vitha@tamu.edu.

Histone-GFP fusion protein in Neurospora crassa hyphae.
 Specimen courtesy of Dr. Bell-Pedersen (Department of Biology).

The Zeiss Axiophot microscope equipped with a Plan Neofluoar 100x/1.3 oil-immersion objective and a Coolsnap cf camera was used to create a z-stack of GFP fluorescence images with z-step of 0.2 um. The raw image stack was processed with AutoDeblur X software (Media Cybernetics) using 100 iterations of blind deconvolution algorithm, taking into account spherical aberration due to refractive index mismatch.  The raw and deconvolved image stacks were then opened in ImageJ software to generate orthogonal views of the image stacks. Note: the large amount of out-of-focus blur in the raw image as well as the improvement in contrast and resolvable detail in the deconvolved dataset. Image data was acquired by Laura Short (Department of Anthropology) during the Spring 2009 Light Microscopy course offered by the MIC. Image processing by Stanislav Vitha, MIC.