Monte Carlo-based realistic modeling of speckles in Fourier-domain optical coherence tomography

In the measurement of tissues using Fourier-domain optical coherence tomography (FD-OCT), speckle patterns from dynamic and static components often exhibit distinct characteristics: the former can be reduced through incoherent averaging, while the latter cannot. However, in the conventional Monte Carlo (MC) based simulations of FD-OCT, the speckle patterns of dynamic medium and static regions cannot be distinguished due to the random spatial distribution of scattering events across the entire simulated phantom. To tackle this issue, we propose a hybrid phantom model for MC-based realistic simulation of speckles in FD-OCT. In the simulation using the proposed model, static tissue within the 3D structure is modeled as a swarm of fixed particles loosely packed in the background medium. Once a photon is emitted into the static tissue model, it keeps moving until encountering a fixed particle and undergoing scattering. On the other hand, the spatial distribution of scattering points in the dynamic medium is still assumed random, which makes the photon's step size sampled based on the wavelength-dependent scattering coefficient. Compared to conventional MC simulations, speckles simulated with the proposed model at different time points exhibit a higher spatial correlation in the static structures, which allows them to remain after incoherent averaging. In contrast, speckles in the dynamic component manifest de-correlation across multiple simulations. Future works involve leveraging this method to simulate dynamic OCT and linking structural information with speckle patterns to solve inverse problems.