GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging.
GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging.
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DOI：
10.1038/s41598-017-09847-1
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发表时间：
2017-09-05
影响因子：
4.6
通讯作者：
Miao J
中科院分区：
文献类型：
--
作者：
Pryor A Jr;Yang Y;Rana A;Gallagher-Jones M;Zhou J;Lo YH;Melinte G;Chiu W;Rodriguez JA;Miao J
层析成像已经在不同的领域产生了根本性的影响，从研究物质中的3D原子排列到医学上的人类健康研究。尽管层析成像的应用非常广泛，但其核心仍然是相同的，即必须实现一种数学方法来从多个2D投影重建对象的3D结构。在这里，我们提出了一种称为广义傅立叶迭代重建(GENFIRE)的层析算法的数学实现，用于从有限数量的2D投影进行高分辨率3D重建。GENFIRE首先组装一个具有过采样的3D傅立叶网格，然后在实空间和倒数空间之间迭代，以寻找同时符合测量数据和一般物理约束的全局解。该算法需要最少的人工干预，并且还结合了角度精化以减少倾角误差。我们通过数值模拟和实验重建多孔材料和冷冻水合海洋蓝藻的3D结构，证明了GENFIRE可以产生比其他几种流行的层析重建技术更好的结果。配备了图形用户界面的GENFIRE可以从我们的网站上免费获得，并有望在不同学科中找到广泛的应用。
Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE), for high-resolution 3D reconstruction from a limited number of 2D projections. GENFIRE first assembles a 3D Fourier grid with oversampling and then iterates between real and reciprocal space to search for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques through numerical simulations and by experimentally reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
10.8
作者：
Goris B;De Beenhouwer J;De Backer A;Zanaga D;Batenburg KJ;Sánchez-Iglesias A;Liz-Marzán LM;Van Aert S;Bals S;Sijbers J;Van Tendeloo G
通讯作者：
Van Tendeloo G
影响因子：
2.3
作者：
ANDERSEN, AH;KAK, AC
通讯作者：
KAK, AC
影响因子：
2
作者：
GORDON, R;BENDER, R;HERMAN, GT
通讯作者：
HERMAN, GT
影响因子：
3
作者：
Agulleiro, Jose-Ignacio;Fernandez, Jose-Jesus
通讯作者：
Fernandez, Jose-Jesus