Abstract
A unique feature of polarization-sensitive Mueller optical coherence tomography (Mueller-OCT) is that it can reveal various polarization properties of biological samples that are not observable using conventional OCT. One of the most important polarization parameters is birefringence, which can be measured in its integrated form using existing Mueller-OCT systems. We present a new method that uses the least squares algorithm to differentiate measured integrated Jones matrices so that the samples can be observed layer-by-layer. We tested the algorithm using simulated data with variable additive white Gaussian noise (AWGN) levels. We further verified the algorithm using in vitro measurements of the porcine tendon and the septum of the rat heart. This least squares-based algorithm has the potential to reveal structures previously hidden by the inherent masking properties of the integrated images and provide localized phase retardation and orientation information.
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