Computational adaptive optics for optical coherence tomography using multiple randomized subaperture correlations
Computational adaptive optics for optical coherence tomography using multiple randomized subaperture correlations
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DOI：
10.1364/ol.44.003905
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发表时间：
2019-08-01
期刊：
影响因子：
3.6
通讯作者：
Huettmann, Gereon
中科院分区：
文献类型：
--
作者：
Hillmann, Dierck;Pfaeffle, Clara;Huettmann, Gereon
计算自适应光学(CAO)正在成为基于硬件的自适应光学的一种可行的替代方案--特别是当应用于视网膜的光学相干断层扫描时。对于这种技术，需要能够准确而快速地检测波前误差的算法。在这里，我们提出了一种扩展的常用的子孔径图像相关。通过迭代应用该算法，更重要的是，通过将每个子孔径不与中心子孔径而是与几个随机选择的孔径进行比较，我们改进了像差校正。由于这些修改只略微增加了校正的运行时间，我们相信该方法可以成为许多CAO应用程序的选择算法。(C)2019年美国光学学会
Computational adaptive optics (CAO) is emerging as a viable alternative to hardware-based adaptive optics-in particular when applied to optical coherence tomography of the retina. For this technique, algorithms are required that detect wave-front errors precisely and quickly. Here we propose an extension of the frequently used subaperture image correlation. By applying this algorithm iteratively and, more importantly, comparing each subaperture not to the central subaperture but to several randomly selected apertures, we improved aberration correction. Since these modifications only slightly increase the run time of the correction, we believe this method can become the algorithm of choice for many CAO applications. (c) 2019 Optical Society of America