Impact of velocity gradient in Poiseuille flow on the statistics of coherent radiation scattered by flowing Brownian particles in optical coherence tomography

Noise and bias in optical coherence tomography intensity signal decorrelation

Functional optical coherence tomography (OCT) imaging based on the decorrelation of the intensity signal has been used extensively in angiography and is finding use in flowmetry and therapy monitoring. In this work, we present a rigorous analysis of the autocorrelation function, introduce the concepts of contrast bias, statistical bias and variability, and identify the optimal definition of the second-order autocorrelation function (ACF) g ⁽²⁾ to improve its estimation from limited data. We benchmark different averaging strategies in reducing statistical bias and variability. We also developed an analytical correction for the noise contributions to the decorrelation of the ACF in OCT that extends the signal-to-noise ratio range in which ACF analysis can be used. We demonstrate the use of all the tools developed in the experimental determination of the lateral speckle size depth dependence in a rotational endoscopic probe with low NA, and we show the ability to more accurately determine the rotational speed of an endoscopic probe to implement NURD detection. We finally present g ⁽²⁾-based angiography of the finger nailbed, demonstrating the improved results from noise correction and the optimal bias mitigation strategies.