## 4. Methods: OCT Image Processing Algorithm |

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A schematic of our extraction algorithm is shown in Fig. 2 below. Briefly summarizing the algorithm, first, an OCT image is laterally divided into regions of interest (ROIs). In each ROI, we fit the laterally averaged OCT signal to a theoretical model and iterate the scattering coefficient μ_{s} and root mean square scattering angle θ_{rms} which characterize optical scattering in that ROI. The effective anisotropy parameter g_{eff} is then calculated using the relationship g_{eff} = cos θ_{rms}. The algorithm returns the OCT image with ROIs delineated and labelled with their respective optical properties.

Fig. 2: Our extraction algorithm. (1) The user delineates an ROI in an OCT image. (2) The signal is averaged, fit, and local μ _{s} and θ_{rms} are iterated. (3) The user delineates successive ROIs across the image. (4) Processed image and numerical output are returned. |

Our extraction algorithm utilizes a general theoretical model that takes into account multiple scattering effects and considers sample arm geometries under realistic focusing conditions. In this experiment, a time domain OCT system operating at 1310 nm was used, with light focused on the proximal glass-collagen interface. The fitting equations in the algorithm are shown in Fig. 3. Details on our algorithm and theoretical model are found in Refs. [1] and [2], respectively.

Fig. 3: Equations governing the extraction algorithm. |

References:

1. D. Levitz, L. Thrane, M. H. Frosz, P. E. Andersen, C. B. Andersen, J. Valanciunaite, J. Swartling, S. Andersson-Engels, and P.R. Hansen, "Determination of optical scattering properties of highly-scattering media in optical coherence tomography images,"

2. L. Thrane, H. T. Yura, and P. E. Andersen, "Analysis of optical coherence tomography systems based on the extended Huygens-Fresnel principle,"