A fully automatic geometric parameters determining method for electron tomography

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

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Electron tomography (ET) is a promising technique for investigating in situ three-dimensional (3D) structure of proteins and protein complexes. To obtain a high-resolution 3D ET reconstruction, alignment and geometric parameters determination of ET tilt series are necessary. However, the common geometric parameters determining methods depend on human intervention, which are not only fairly subjective and easily introduce errors but also labor intensive for high-throughput tomographic reconstructions. To overcome these problems, in this paper, we presented a fully automatic geometric parameters determining method. Taking advantage of the high-contrast reprojections of ICON and a series of image processing and edge recognition techniques, our method achieves a high-precision full automation for geometric parameters determining. Experimental results on the resin embedded dataset show that our method has a high accuracy comparable to the common ‘manual positioning’ method.

源语言英语
主期刊名Bioinformatics Research and Applications - 13th International Symposium, ISBRA 2017, Proceedings
编辑Zhipeng Cai, Ovidiu Daescu, Min Li
出版商Springer Verlag
385-389
页数5
ISBN(印刷版)9783319595740
DOI
出版状态已出版 - 2017
已对外发布
活动13th International Symposium on Bioinformatics Research and Applications, ISBRA 2017 - Honolulu, 美国
期限: 29 5月 20172 6月 2017

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10330 LNBI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议13th International Symposium on Bioinformatics Research and Applications, ISBRA 2017
国家/地区美国
Honolulu
时期29/05/172/06/17

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