A Sharper Fluorescent Image

Accurate fluorescence microscopic imaging of three-dimensional specimens is often impaired by the signal distortion that occurs as specimen light travels through the optical system to the observing camera. Thornwood, NY-based Carl Zeiss Microimaging Inc.'s powerful 3D Deconvolution software reassigns out-of-focus light back to its original location utilizing a generic mathematical algorithm, which greatly improves the image's resolution and signal-to-noise ratio.1 How a particular optical syst

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How a particular optical system distorts, or convolves, emitted light from a subresolution-sized point object is referred to as the system's point-spread function (PSF). The software calculates the optical system's theoretical PSF based on the microscope's optical parameters. This value is then used to deconvolve the highest-quality image for the specimen being examined. To improve the accuracy of the results, users can base the deconvolution algorithm on a measured, rather than theoretical PSF. To determine the optical system's measured PSF, the software analyzes the collected image of a fluorescent calibration bead with known dimensions.

According to Norbert Schuster, Zeiss product-marketing manager, users can further optimize results by choosing from one of three available algorithm methods: Nearest Neighbor, Regularized Inverse Filter, or Iterative Maximum Likelihood. Scientists can determine the best algorithm empirically by using the software's Region-of-Interest function. This function lets the user choose a field within a captured image, apply ...

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