Reference spectrum extraction and fixed-pattern noise removal in optical coherence tomography

We present a new signal processing method that extracts the reference spectrum information from an acquired optical coherence tomography (OCT) image without a separate calibration step of reference spectrum measurement. The reference spectrum is used to remove the fixed-pattern noise that is a characteristic artifact of Fourier-domain OCT schemes. It was found that the conventional approach based on an averaged spectrum, or mean spectrum, is prone to be influenced by the high-amplitude data points whose statistical distribution is hardly randomized. Thus, the conventional mean-spectrum subtraction method cannot completely eliminate the artifact but may leave residual horizontal lines in the final image. This problem was avoided by utilizing an advanced statistical analysis tool of the median A-line. The reference A-line was obtained by taking a complex median of each horizontal-line data. As an optional method of high-speed calculation, we also propose a minimum-variance mean A-line that can be calculated from an image by a collection of mean A-line values taken from a horizontal segment whose complex variance of the data points is the minimum. By comparing the images processed by those methods, it was found that our new processing schemes of the median-line subtraction and the minimum-variance mean-line subtraction successfully suppressed the fixed-pattern noise. The inverse Fourier transform of the obtained reference A-line well matched the reference spectrum obtained by a physical measurement as well.