2010
DOI: 10.1002/0471142956.cy1219s52
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3D Deconvolution Microscopy

Abstract: 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… Show more

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Cited by 78 publications
(70 citation statements)
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“…Computer algorithms are used to compensate the absence of interplane detail and to reconstruct a three-dimensional image from a rendered z-stack [18]. This method is commonly employed to study the dynamics of IS formation in lateral T-cell-APC conjugates [8,19], and can be used to rapidly acquire threedimensional information of the IS morphology and structure.…”
Section: Introductionmentioning
confidence: 99%
“…Computer algorithms are used to compensate the absence of interplane detail and to reconstruct a three-dimensional image from a rendered z-stack [18]. This method is commonly employed to study the dynamics of IS formation in lateral T-cell-APC conjugates [8,19], and can be used to rapidly acquire threedimensional information of the IS morphology and structure.…”
Section: Introductionmentioning
confidence: 99%
“…The noise model for wide-field microscopy with its larger photon fluxes approaches Gaussian noise, but wide-field images can still be deconvolved using R-L [13]. With an appropriate PSF, this algorithm can thus be applied to multiple modes of microscopy.…”
Section: Deconvolution Resultsmentioning
confidence: 99%
“…For very light-sensitive sparsely-labeled samples like our electroporated spinal cord slices, therefore, wide-field microscopy performs better than confocal microscopy. When combined with image restoration by deconvolution, which removes out of focus information and improves contrast, wide-field is then particularly good for detection of small, dim objects 11 . While not appropriate for every tissue imaging experiment, this approach has been very effective for our live cell imaging application.…”
Section: Discussionmentioning
confidence: 99%