Automatic TEM image alignment by trifocal geometry

被引:32
作者
Brandt, S. S.
Ziese, U.
机构
[1] Aalto Univ, Lab Computat Engn, FI-02015 Helsinki, Finland
[2] Univ Utrecht, Dept Inorgan Chem & Catalysis, NL-3584 CA Utrecht, Netherlands
关键词
automatic alignment; computer vision; electron tomography; trifocal geometry;
D O I
10.1111/j.1365-2818.2006.01545.x
中图分类号
TH742 [显微镜];
学科分类号
摘要
Here we propose a novel method for automatic, markerless, feature-based alignment of TEM images suitable for electron tomography. The proposed method, termed trifocal alignment, is more accurate than the previous markerless methods. The key components developed are: (1) a reliable multi-resolution algorithm for matching feature points between images; (2) a robust, maximum-likelihood-based estimator for determining the geometry of three views-the trifocal constraint-required for validating the correctness of the matches; and (3) a robust, large-scale optimization framework to compute the alignment parameters from hundreds of thousands of feature point measurements from a few hundred images. The ability to utilize such a large number of measurements successfully compensates for point localization errors. The method was experimentally confirmed with electron tomography tilt series of biological and material sciences samples, consisting of from 40 to 150 images. The results show that, with this feature-based alignment approach, a level of accuracy comparable with fiducial marker alignment can be achieved.
引用
收藏
页码:1 / 14
页数:14
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