Abstract
The high acquisition speed of state-of-the-art optical coherence tomography (OCT) enables massive signal-to-noise ratio (SNR) improvements by signal averaging. Here, we investigate the performance of two commonly used approaches for OCT signal averaging. We present the theoretical SNR performance of (a) computing the average of OCT magnitude data and (b) averaging the complex phasors, and substantiate our findings with simulations and experimentally acquired OCT data. We show that the achieved SNR performance strongly depends on both the SNR of the input signals and the number of averaged signals when the signal bias caused by the noise floor is not accounted for. Therefore we also explore the SNR for the two averaging approaches after correcting for the noise bias and, provided that the phases of the phasors are accurately aligned prior to averaging, then find that complex phasor averaging always leads to higher SNR than magnitude averaging.
Highlights
Optical coherence tomography (OCT) [1] performs biomedical imaging at high speed and with high sensitivity
The high acquisition speeds of modern OCT systems enable the improvement of the signal-to-noise ratio by averaging multiple signals, for instance by fusing OCT frames or even volumes quickly repeated at the same sample position
The SNR1 dependence of complex averaging has a considerable impact on its performance: While for stro√ng signals with SNR1 1, complex averaging outperforms magnitude averaging by a factor N, the signal-to-noise improvement becomes much less for weaker input signals
Summary
Optical coherence tomography (OCT) [1] performs biomedical imaging at high speed and with high sensitivity. The high acquisition speeds of modern OCT systems enable the improvement of the signal-to-noise ratio by averaging multiple signals, for instance by fusing OCT frames or even volumes quickly repeated at the same sample position. In 2013, Szkulmowski and Wojtkowski published a thorough analysis of signals and noise subject to different averaging approaches [21]. In their analysis, the authors found a much stronger reduction of the noise floor by complex averaging as compared to magnitude averaging and observed a heterogeneous outcome in terms of signal-to-noise performance for different imaging scenarios. An overview of the terminology as well as a brief section on phase correction required for complex phasor averaging is provided in the appendix
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