Department of Physics and Astronomy, University of Rochester, Rochester, New York 14627, USA.
Opt Lett. 2013 May 15;38(10):1721-3. doi: 10.1364/OL.38.001721.
In this Letter, we implement a maximum-likelihood estimator to interpret optical coherence tomography (OCT) data for the first time, based on Fourier-domain OCT and a two-interface tear film model. We use the root mean square error as a figure of merit to quantify the system performance of estimating the tear film thickness. With the methodology of task-based assessment, we study the trade-off between system imaging speed (temporal resolution of the dynamics) and the precision of the estimation. Finally, the estimator is validated with a digital tear-film dynamics phantom.
在这封信件中，我们首次基于傅里叶域光学相干断层扫描（OCT）和双界面泪膜模型实现了最大似然估计器来解释 OCT 数据。我们使用均方根误差作为衡量标准来量化估计泪膜厚度的系统性能。通过基于任务的评估方法，我们研究了系统成像速度（动态的时间分辨率）和估计精度之间的权衡。最后，我们使用数字泪膜动力学模型对估计器进行了验证。
