Accurate Monte Carlo simulation of frequency-domain optical coherence tomography

Wang, Yan; Bai, Li

Abstract

Optical coherence Tomography (OCT) relies on optical interferometry to provide non‐invasive imaging of living tissues. In addition to its 3D imaging capacity for medical diagnosis, its potential use for recovering optical parameters of biological tissues for biological and pathological analyses has also been explored by researchers, as pathological changes in tissue alter the micro‐structure of the tissue and therefore its optical properties. We aim to develop a new approach to OCT data analysis by estimating optical properties of tissues from OCT scans which are invisible in the scans. This is an inverse problem. Solving an inverse problem involves a forward modelling step to simulate OCT scans of the tissues with hypothesized optical parameter values, and an inverse step to estimate the real optical parameters values by matching the simulated scans to real scans. In this paper, we present a Monte Carlo (MC) based approach for simulating the frequency‐domain OCT. We incorporated a focusing Gaussian light beam rather than an infinitesimally thin light beam for accurate simulations. A new and more accurate photon detection scheme is also implemented. We compare our MC model to an analytical OCT model based on the extended Huygens‐Fresnel principle (EHF) to demonstrate the consistency between the two models. We show that the two models are in good agreement for tissues with high scattering and high anisotropy factors.

Citation

Wang, Y., & Bai, L. (2019). Accurate Monte Carlo simulation of frequency-domain optical coherence tomography. International Journal for Numerical Methods in Biomedical Engineering, 35(4), Article e3177. https://doi.org/10.1002/cnm.3177

• Journal Article Type: Article
• Acceptance Date: Dec 19, 2018
• Online Publication Date: Jan 28, 2019
• Publication Date: Apr 30, 2019
• Deposit Date: Feb 8, 2019
• Publicly Available Date: Jan 29, 2020
• Journal: International Journal for Numerical Methods in Biomedical Engineering
• Print ISSN: 2040-7939
• Electronic ISSN: 2040-7947
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 35
• Issue: 4
• Article Number: e3177
• DOI: https://doi.org/10.1002/cnm.3177
• Keywords: Modelling and Simulation; Computational theory and mathematics; Software; Applied mathematics; Molecular biology; Biomedical engineering
• Public URL: https://nottingham-repository.worktribe.com/output/1529420
• Publisher URL: https://onlinelibrary.wiley.com/doi/full/10.1002/cnm.3177
• Contract Date: Feb 8, 2019