26 June 1992 Algorithms for 3-D brightfield microscopy
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Byron H. Willis, Byron H. Willis, Badrinath Roysam, Badrinath Roysam, James N. Turner, James N. Turner, Timothy J. Holmes, Timothy J. Holmes, } "Algorithms for 3-D brightfield microscopy", Proc. SPIE 1660, Biomedical Image Processing and Three-Dimensional Microscopy, (26 June 1992); doi: 10.1117/12.59545; https://doi.org/10.1117/12.59545

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