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Proceedings Paper

Algorithms for 3D brightfield microscopy
Author(s): Byron H. Willis; Badrinath Roysam; James N. Turner; Timothy J. Holmes
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Paper Abstract

We have developed image reconstruction algorithms for generating 3-D renderings of biological specimens from brightfield micrographs. The algorithm presented here is founded on the maximum likelihood estimation theory where steepest ascent and conjugate gradient techniques are used to optimize the solution to the multidimensional equation. The estimation problem posed is that of reconstructing the optical density, or linear attenuation coefficients, similar to that of computed tomography, under the simplifying assumption of geometric optics. We assume white Gaussian noise corrupts the signal generating a Gaussian distributed signal according to the modeling of the system impulse response. One of the challenges of the algorithms presented here is in restoring the values within the missing cone region of the system optical transfer function. The algorithm and programming are straightforward and incorporate standard Fourier techniques. The theoretical development of the algorithms is outlined. Simulations of reconstructions using this technique are currently being performed.

Paper Details

Date Published: 26 June 1992
PDF: 5 pages
Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992); doi: 10.1117/12.59545
Show Author Affiliations
Byron H. Willis, Rensselaer Polytechnic Institute (United States)
Badrinath Roysam, Rensselaer Polytechnic Institute (United States)
James N. Turner, Rensselaer Polytechnic Institute and New York State Dept. of Health (United States)
Timothy J. Holmes, Rensselaer Polytechnic Institute (United States)


Published in SPIE Proceedings Vol. 1660:
Biomedical Image Processing and Three-Dimensional Microscopy
Raj S. Acharya; Carol J. Cogswell; Dmitry B. Goldgof, Editor(s)

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