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Data Analysis and Signal Postprocessing for Optical Coherence Tomography

  • D. L. Marks
  • T. S. Ralston
  • S. A. Boppart
Part of the Biological and Medical Physics, Biomedical Engineering book series (BIOMEDICAL)

The quality of images obtained with Optical Coherence Tomography (OCT), like many other imaging modalities, can be enhanced by using signal processing to numerically infer properties of the object being studied. While a great deal of insight can be gained by understanding OCT intuitively as a range-finding mechanism, more sophisticated analysis can reveal additional detail and features to the extent data quality allows. To maximize the utility of the data, signal processing is used to reject noise and to ensure the resulting image conforms to known properties of the object. We briefly summarize concepts of inference in signal processing. These ideas are applied when reviewing and examining methods of reducing noise, improving resolution through deconvolution, reducing speckle, correcting for material dispersion and OCT system imperfections, and deblurring the defocusing effects outside of the depth-of-field of the OCT instrument.

Keywords

Optical Coherence Tomography Speckle Pattern Optical Coherence Tomography Image Optical Coherence Tomography System Anterior Chamber Angle 
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-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • D. L. Marks
  • T. S. Ralston
  • S. A. Boppart

There are no affiliations available

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