Abstract

In most dual-band OCT systems, there is a spectral gap between both bands. This might be as large as one third of the total spectral region. Therefore, a simple Fourier transformation of the data does not give the resolution that could be possible considering the overall spectral width. Instead, the full width of the peak is comparable to the width resulting from a single band and is additionally modulated. We compare several methods to achieve a high resolution in spite of the missing data. Because in a dual-band system the image quality resulting from the full information is not known we test and optimize different algorithms by using the data from a single band system and excluding an equal part of the spectrum. While methods using non-equidistant sample points like Vandermonde and Lomb transformation work well with small spectral gaps, they result in large image artifacts for broader gaps, which are typical for dual-band OCT systems. Simulations show that fitting the available data with a limited set of sine and cosines functions might give good results but for larger gaps and appropriate amount of basis-functions this method fails, too. Dividing both bands into overlapping smaller bands and looking at the phase of short-time Fourier transformations (STFT) resulting from a single scatterer, it becomes clear that the amplitude of all Fourier coefficients for the total band can be estimated by the change of the phase of the STFTs in and between both bands. Therefore, we developed an algorithm of weighting the data based on the phase distribution of the STFT data. As a single value specifying the phase distribution we choose the absolute sum of the STFTs divided by the sum of the amplitudes of the STFTs. Because typical OCT data are not caused by single scatterers, we adapted this algorithm with a cluster analysis to predict the appropriate amplitude expected for a full spectrum from the phase distribution of the STFTs inside both bands and between both bands. Although the image is noisier and fainter compared to an image from the full spectrum, the resulting image has the best resolution from all methods investigated.

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