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Spectral analysis and spectroscopic metrics in Spectroscopic Optical Coherence Tomography

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Abstract

In Spectroscopic Optical Coherence Tomography the spectral information that is inherent in the detected broad band signal is analyzed to obtain additional contrast in tomographic images. The most important signal processing steps are the spectral analysis and the spectroscopic metric. While the former calculates the spectra from the raw OCT data set the latter reduces the information content of the spectra to a characterizing number that is used for a meaningful colorization of the OCT image. We compare the standard approach that uses the short time Fourier transform for spectral analysis combined with a simple spectroscopic metric, like a center of mass calculation, with more sophisticated methods. These methods include pattern recognition in combination with feature reduction to generate the spectroscopic metric. Our results indicate that the analysis of the spectra by pattern recognition is superior to other standard approaches.

© 2013 Optical Society of America

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