Light Microscopic Images Reconstructed by Maximum Likelihood Deconvolution

  • Timothy J. Holmes
  • Santosh Bhattacharyya
  • Joshua A. Cooper
  • David Hanzel
  • Vijaykumar Krishnamurthi
  • Wen-chieh Lin
  • Badrinath Roysam
  • Donald H. Szarowski
  • James N. Turner

Abstract

The main purpose of this chapter is to introduce the reader to the methodology of maximum likelihood (ML)-based deblurring algorithms. It is aimed at the interdisciplinary scientist, who may not be concerned about the underlying mathematical foundations of the methodology but who needs to understand the main principles behind the algorithms used. Some mathematical principles are explained, but the interested reader may find more details in the numerous publications cited in Holmes (1989, 1992), Krishnamurthi et al (1992), and Shaw and Rawlins (1991). A sample image reconstruction is presented from each of three microscope modalities, including the wide-field epifluorescence (WFF) microscope, the confocal pinhole laser-scanned epifluorescence microscope (CLSM), and the transmitted light brightfleld (BF) microscope.

Keywords

Blind Deconvolution Optical Transfer Function Lagrange Multiplier Approach Biomedical Engineer Department General Flowchart 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • Timothy J. Holmes
    • 1
    • 2
  • Santosh Bhattacharyya
    • 1
  • Joshua A. Cooper
    • 1
  • David Hanzel
    • 3
  • Vijaykumar Krishnamurthi
    • 1
  • Wen-chieh Lin
    • 1
    • 2
  • Badrinath Roysam
    • 1
    • 2
  • Donald H. Szarowski
    • 2
  • James N. Turner
    • 1
    • 2
  1. 1.Biomedical Engineering Department and Center for Image Processing ResearchRensselaer Polytechnic InstituteTroyUSA
  2. 2.Wadsworth Center for Laboratories and ResearchNew York State Department of HealthAlbanyUSA
  3. 3.Molecular DynamicsSunnyvaleUSA

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