Institute for Electronic Structure and Laser, Foundation for Research and Technology-Hellas, P.O. Box 1527, Heraklion 71110, Greece.
Opt Lett. 2010 Mar 1;35(5):688-90. doi: 10.1364/OL.35.000688.
Optical tomography has recently witnessed a substantial increase in the size of the data sets used, mainly owing to the use of CCD cameras. Larger data sets render 3D reconstructions more robust, quantitative, and reproducible, but also significantly increase the computing time needed to generate the reconstructed data. Approaches working with spatial-frequencies instead of real space variables seem to be the method of choice in this case, and a direct inversion method that can produce three-dimensional images from very large detector numbers (>10(5)) using either very large source numbers (>10(3)) [Phys. Rev. E 64, 035601 (2001)] or structured illumination [Opt. Lett. 34, 983 (2009)] has been presented. However, most small animal imaging setups typically incur a practical upper limit of only approximately 10(2) sources mainly due to imaging time constraints, and currently all relying on point source illumination. In this Letter, what we believe to be a new approach, which combines Fourier and real space functions, is shown, which fills the gap between traditional fiber-based small data sets that are solved in real space and the very large data sets solved entirely in spatial-frequency domain.
光学层析成像技术最近见证了所使用数据集规模的大幅增加，这主要归因于 CCD 相机的使用。更大的数据集使 3D 重建更加稳健、定量和可重复，但也大大增加了生成重建数据所需的计算时间。在这种情况下，使用空间频率而不是实空间变量的方法似乎是首选方法，并且已经提出了一种直接反演方法，该方法可以使用大量源（>10^3）[Phys. Rev. E 64, 035601 (2001)]或结构照明[Opt. Lett. 34, 983 (2009)]从非常大的探测器数量（>10^5）产生三维图像。然而，由于成像时间的限制，大多数小动物成像设置通常仅具有约 10^2 的实际上限，并且目前都依赖于点源照明。在这封信中，我们展示了一种结合傅里叶和实空间函数的新方法，该方法填补了传统基于纤维的小数据集（在实空间中求解）和完全在空间频域中求解的非常大数据集之间的空白。
