用于改进光学相干断层扫描的自动干涉合成孔径显微镜和计算自适应光学技术。
Automated interferometric synthetic aperture microscopy and computational adaptive optics for improved optical coherence tomography.
作者信息
Xu Yang, Liu Yuan-Zhi, Boppart Stephen A, Carney P Scott
出版信息
Appl Opt. 2016 Mar 10;55(8):2034-41. doi: 10.1364/AO.55.002034.
Abstract
In this paper, we introduce an algorithm framework for the automation of interferometric synthetic aperture microscopy (ISAM). Under this framework, common processing steps such as dispersion correction, Fourier domain resampling, and computational adaptive optics aberration correction are carried out as metrics-assisted parameter search problems. We further present the results of this algorithm applied to phantom and biological tissue samples and compare with manually adjusted results. With the automated algorithm, near-optimal ISAM reconstruction can be achieved without manual adjustment. At the same time, the technical barrier for the nonexpert using ISAM imaging is also significantly lowered.
摘要
在本文中，我们介绍了一种用于干涉合成孔径显微镜（ISAM）自动化的算法框架。在此框架下，诸如色散校正、傅里叶域重采样和计算自适应光学像差校正等常见处理步骤被作为度量辅助参数搜索问题来执行。我们还展示了该算法应用于体模和生物组织样本的结果，并与手动调整的结果进行比较。使用该自动化算法，可以在无需手动调整的情况下实现接近最优的ISAM重建。同时，非专业人员使用ISAM成像的技术障碍也显著降低。
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