Comparative study of iterative reconstruction algorithms for missing cone problems in optical diffraction tomography
Comparative study of iterative reconstruction algorithms for missing cone problems in optical diffraction tomography
复制标题
DOI：
10.1364/oe.23.016933
复制
发表时间：
2015-06-29
期刊：
影响因子：
3.8
通讯作者：
Ye, Jong Chul
中科院分区：
文献类型：
--
作者：
Lim, JooWon;Lee, KyeoReh;Ye, Jong Chul
在光学层析成像中，由于物镜数值孔径所施加的投影角度有限，存在一些无法测量的空间频率分量。这种限制通常被称为缺失锥问题，它会导致层析成像中折射率（RI）值的低估，并导致沿光轴的RI分布严重拉长。为了解决这个缺失锥体的问题，已经引入了几种迭代重建算法，利用先验知识，如RI差或样本边缘的正性。本文系统地比较了现有的各种迭代重建算法，以减轻光学衍射层析成像中的缺锥问题。利用球珠和真实生物样本，对边缘保持、全变分正则化和Gerchberg-Papoulis算法三种具有代表性的正则化方案进行了数值和实验评价；人体红细胞和肝细胞。我们的工作将为在ODT中选择适当的正则化提供重要的指导。(C) 2015美国光学学会
In optical tomography, there exist certain spatial frequency components that cannot be measured due to the limited projection angles imposed by the numerical aperture of objective lenses. This limitation, often called as the missing cone problem, causes the under-estimation of refractive index (RI) values in tomograms and results in severe elongations of RI distributions along the optical axis. To address this missing cone problem, several iterative reconstruction algorithms have been introduced exploiting prior knowledge such as positivity in RI differences or edges of samples. In this paper, various existing iterative reconstruction algorithms are systematically compared for mitigating the missing cone problem in optical diffraction tomography. In particular, three representative regularization schemes, edge preserving, total variation regularization, and the Gerchberg-Papoulis algorithm, were numerically and experimentally evaluated using spherical beads as well as real biological samples; human red blood cells and hepatocyte cells. Our work will provide important guidelines for choosing the appropriate regularization in ODT. (C) 2015 Optical Society of America