A fast fiducial marker tracking model for fully automatic alignment in electron tomography
R. Han, F. Zhang, X. Gao
Bioinformatics, btx653, (2017)
Fast fiducial, Marker tracking model, Automatic alignment, Electron, Tomography
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.
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.
See all publications 2017