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Measurement of a multi-layered tear film phantom using optical coherence tomography and statistical decision theory

机译:使用光学相干断层扫描和统计决策理论测量多层泪膜体模

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To extend our understanding of tear film dynamics for the management of dry eye disease, we propose a method to optically sense the tear film and estimate simultaneously the thicknesses of the lipid and aqueous layers. The proposed method, SDT-OCT, combines ultra-high axial resolution optical coherence tomography (OCT) and a robust estimator based on statistical decision theory (SDT) to achieve thickness measurements at the nanometer scale. Unlike conventional Fourier-domain OCT where peak detection of layers occurs in Fourier space, in SDT-OCT thickness is estimated using statistical decision theory directly on the raw spectra acquired with the OCT system. In this paper, we demonstrate in simulation that a customized OCT system tailored to ~1 µm axial point spread function (FWHM) in the corneal tissue, combined with the maximum-likelihood estimator, can estimate thicknesses of the nanometer-scale lipid and micron-scale aqueous layers of the tear film, simultaneously, with nanometer precision. This capability was validated in experiments using a physical phantom that consists of two layers of optical coatings that mimic the lipid and aqueous layers of the tear film.
机译:为了扩展我们对用于干眼病治疗的泪膜动力学的理解,我们提出了一种光学感测泪膜并同时估计脂质层和水层厚度的方法。所提出的方法SDT-OCT将超高轴向分辨率光学相干断层扫描(OCT)与基于统计决策理论(SDT)的鲁棒估计器相结合,以实现纳米级的厚度测量。不同于传统的傅立叶域OCT,其中层的峰值检测发生在傅立叶空间中,SDT-OCT厚度是使用统计决策理论直接在OCT系统获取的原始光谱上估算的。在本文中,我们在仿真中证明,针对角膜组织中〜1 µm轴点扩展函数(FWHM)量身定制的定制OCT系统,结合最大似然估计器,可以估计纳米级脂质和微米级厚度。同时以纳米精度对水膜的水层进行缩放。此功能已在使用物理模型的实验中得到验证,该模型由两层光学涂层组成,可模拟泪膜的脂质层和水层。

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