A fast fiducial marker tracking model for fully automatic alignment in electron tomography.
A fast fiducial marker tracking model for fully automatic alignment in electron tomography.
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用于电子断层扫描全自动对准的快速基准标记跟踪模型
DOI：
10.1093/bioinformatics/btx653
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发表时间：
2018-03-01
期刊：
影响因子：
--
通讯作者：
Gao X
中科院分区：
文献类型：
--
作者：
Han R;Zhang F;Gao X
由于亚层析图平均技术的高要求和大视场电子显微镜的快速发展，自动对准，特别是基于基准标记的对准变得越来越重要。在对准步骤中，基准标记跟踪是决定最终对准质量的关键步骤。然而，如何以全自动的方式准确有效地跟踪基准标记仍然是一个具有挑战性的问题。本文提出了一种鲁棒高效的基准标记跟踪方案。首先，从理论上证明了仿射变换对准两个显微图上基准标记点位置的变换偏差的上界；其次，设计了一种基于高斯混合模型的自动跟踪算法，加快了基准标记的跟踪速度。第三，我们提出了一种针对透镜畸变的分而治之策略，以确保方案的可靠性。据我们所知，这是第一次在理论上将投影模型与跟踪模型联系起来的尝试。实际实验结果进一步支持了我们的理论边界，证明了算法的有效性。这项工作有助于对具有大量基准标记的数据集进行全自动跟踪。实现快速基准标记跟踪的C/ c++源代码可从https://github.com/icthrm/gmm-marker-tracking获得。Markerauto 1.6或更高版本（也集成在http://ear.ict.ac.cn/上的AuTom平台中）提供了快速校准的完整实现，其中通过‘ -t ’选项可实现快速基准标记跟踪。补充数据可在生物信息学网站获得。
Automatic alignment, especially fiducial marker-based alignment, has become increasingly important due to the high demand of subtomogram averaging and the rapid development of large-field electron microscopy. Among the alignment steps, fiducial marker tracking is a crucial one that determines the quality of the final alignment. Yet, it is still a challenging problem to track the fiducial markers accurately and effectively in a fully automatic manner. In this paper, we propose a robust and efficient scheme for fiducial marker tracking. Firstly, we theoretically prove the upper bound of the transformation deviation of aligning the positions of fiducial markers on two micrographs by affine transformation. Secondly, we design an automatic algorithm based on the Gaussian mixture model to accelerate the procedure of fiducial marker tracking. Thirdly, we propose a divide-and-conquer strategy against lens distortions to ensure the reliability of our scheme. To our knowledge, this is the first attempt that theoretically relates the projection model with the tracking model. The real-world experimental results further support our theoretical bound and demonstrate the effectiveness of our algorithm. This work facilitates the fully automatic tracking for datasets with a massive number of fiducial markers. The C/C ++ source code that implements the fast fiducial marker tracking is available at https://github.com/icthrm/gmm-marker-tracking. Markerauto 1.6 version or later (also integrated in the AuTom platform at http://ear.ict.ac.cn/) offers a complete implementation for fast alignment, in which fast fiducial marker tracking is available by the ‘-t’ option. Supplementary data are available at Bioinformatics online.
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