Compressed sensing improved iterative reconstruction-reprojection algorithm for electron tomography.
Compressed sensing improved iterative reconstruction-reprojection algorithm for electron tomography.
复制标题
压缩感知改进的电子断层扫描迭代重建-重投影算法
DOI：
10.1186/s12859-020-3529-3
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发表时间：
2020-11-18
影响因子：
3
通讯作者：
Zhang F
中科院分区：
文献类型：
--
作者：
Li L;Han R;Zhang Z;Guo T;Liu Z;Zhang F
背景电子断层成像（electrontomography，ET）是研究复杂生物结构及其功能的重要技术。电子断层摄影术从不同方向的投影重建三维物体的内部。然而，由于仪器的限制，投影的角度倾斜范围被限制在+70 ° C到-70 ° C之间。丢失的角度范围被称为丢失的楔形，将导致artifaction.ResultsIn本文中，我们提出了一种新的算法，压缩感知改进的迭代重建-再投影（CSIIRR），它遵循改进的迭代重建-再投影的时间表，但进一步考虑了标本中的生物超微结构内容的稀疏性。该算法结合了改进的迭代重建-重投影（IIRR）算法和压缩感知算法的优点，使电子层析成像的估计具有更快的执行速度和更好的重建效果。一个全面的实验已经进行，CSIIRR的挑战，模拟和真实世界的数据集，以及与一些经典的方法进行了比较。实验结果证明了CSIIRR的有效性和效率，并进一步显示了其相对于其他方法的优势。ConclusionsThe算法在抑制缺失楔形效应和恢复缺失信息方面具有明显的优势，为结构生物学家提供了一种清晰准确的断层重建选择。
BackgroundElectron tomography (ET) is an important technique for the study of complex biological structures and their functions. Electron tomography reconstructs the interior of a three-dimensional object from its projections at different orientations. However, due to the instrument limitation, the angular tilt range of the projections is limited within +70∘to −70∘. The missing angle range is known as the missing wedge and will cause artifacts.ResultsIn this paper, we proposed a novel algorithm, compressed sensing improved iterative reconstruction-reprojection (CSIIRR), which follows the schedule of improved iterative reconstruction-reprojection but further considers the sparsity of the biological ultra-structural content in specimen. The proposed algorithm keeps both the merits of the improved iterative reconstruction-reprojection (IIRR) and compressed sensing, resulting in an estimation of the electron tomography with faster execution speed and better reconstruction result. A comprehensive experiment has been carried out, in which CSIIRR was challenged on both simulated and real-world datasets as well as compared with a number of classical methods. The experimental results prove the effectiveness and efficiency of CSIIRR, and further show its advantages over the other methods.ConclusionsThe proposed algorithm has an obvious advance in the suppression of missing wedge effects and the restoration of missing information, which provides an option to the structural biologist for clear and accurate tomographic reconstruction.
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