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Convolution and Deconvolution For 3D Imaging Of Cell Physiology

Published online by Cambridge University Press:  02 July 2020

Leslie M. Loew ,
Mark Sapia  and
James Schaff
Leslie M. Loew
Affiliation:
Department of Physiology and Center for Biomedical Imaging Technology, University of Connecticut Health Center, Farmington, CT, 06030-1507
Mark Sapia
Affiliation:
Department of Physiology and Center for Biomedical Imaging Technology, University of Connecticut Health Center, Farmington, CT, 06030-1507
James Schaff
Affiliation:
Department of Physiology and Center for Biomedical Imaging Technology, University of Connecticut Health Center, Farmington, CT, 06030-1507
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Extract

Fluorescence intensity in a spectrofluorometer is proportional to the concentration of analyte over a wide dynamic range and is, therefore, an excellent quantitative analytical tool. In this paper we use the techniques of deconvolution and convolution to extend the utility of quantitative fluorescence to the measurement of analyte concentrations inside cells and their organelles. This permits us to assess the physiological state of living cells in situ.

To successfully turn a voxel within a 3D image into a microcuvette, 2 conditions must be met. First, to be sure the voxel is associated with only one fluorescent structure, the object that is being measured must be fully resolved from neighboring objects in all three dimensions. For structures separated by distances larger than about 300nm in the xy plane or 600nm in z (where z is the optical axis), this can be achieved with either digital deconvolution of 3D widefield images or by confocal microscopy.

Type
Deconvolution of Biological Images for 3D Light Microscopy—Confocal & Widefield
Information
Microscopy and Microanalysis , Volume 4 , Issue S2: Proceedings: Microscopy & Microanalysis '98, Microscopy Society of America 56th Annual Meeting, Microbeam Analysis Society 32nd Annual Meeting, Atlanta, Georgia July 12-16, 1998 , July 1998 , pp. 886 - 887
Copyright
Copyright © Microscopy Society of America

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References

Agard, D. A. 1984. Optical Sectioning Microscopy: Cellular Architecture in Three Dimensions. Ann. Rev. Biophys. Bioeng. 13:191-219. 887Google ScholarPubMed

Fay, F. S., Carrington, W., and Fogarty, K. E.. 1989. Threee-dimensional molecular distribution in single cells analyzed using the digital imaging microscope. J. Microsc. 153:133–149.CrossRefGoogle Scholar

Loew, L. M., Tuft, R. A., Carrington, W., and Fay, F. S.. 1993. Imaging in 5 dimensions: Time dependent membrane potentials in individual mitochondria. Biophys. J. 65:2396–2407.CrossRefGoogle Scholar

Sapia, M., Greenshields, I., Fox, M., Loew, L. M., Schaff, J., and Coutu, G.. 1997. Three-dimensional deconvolution of optical microscope images using adaptive inverse modeling.In IEEE Proceedings of the 40th Midwest Conference on Circuits and Systems., Sacramento, CA.Google Scholar