Autogdeterm: Automatic geometry determination for electron tomography

Yu Chen, Zihao Wang, Lun Li, Jingrong Zhang, Xiaohua Wan, Fei Sun*, Fa Zhang

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

Electron Tomography (ET) is an important method for studying cell ultrastructure in three-dimensional (3D) space. By combining cryo-electron tomography of frozen-hydrated samples (cryo-ET) and a sub-tomogram averaging approach, ET has recently reached sub-nanometer resolution, thereby realizing the capability for gaining direct insights into function and mechanism. To obtain a high-resolution 3D ET reconstruction, alignment and geometry determination of the ET tilt series are necessary. However, typical methods for determining geometry require human intervention, which is not only subjective and easily introduces errors, but is also labor intensive for high-throughput tomographic reconstructions. To overcome these problems, we have developed an automatic geometry-determination method, called AutoGDeterm. By taking advantage of the high-contrast re-projections of the Iterative Compressed-sensing Optimized Non-Uniform Fast Fourier Transform (NUFFT) reconstruction (ICON) and a series of numerical analysis methods, AutoGDeterm achieves high-precision fully automated geometry determination. Experimental results on simulated and resin-embedded datasets show that the accuracy of AutoGDeterm is high and comparable to that of the typical manual positioning method. We have made AutoGDeterm available as software, which can be freely downloaded from our website http://ear.ict.ac.cn.

源语言英语
文章编号8421546
页(从-至)369-376
页数8
期刊Tsinghua Science and Technology
23
4
DOI
出版状态已出版 - 8月 2018
已对外发布

指纹

探究 'Autogdeterm: Automatic geometry determination for electron tomography' 的科研主题。它们共同构成独一无二的指纹。

引用此