A marker-free automatic alignment method based on scale-invariant features
A marker-free automatic alignment method based on scale-invariant features
复制标题
一种基于尺度不变特征的无标记自动对齐方法
DOI：
10.1016/j.jsb.2014.02.011
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发表时间：
2014-04-01
影响因子：
3
通讯作者：
Liu, Zhiyong
中科院分区：
文献类型：
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作者：
Han, Renmin;Zhang, Fa;Liu, Zhiyong
在电子层析成像中，对准精度对于高分辨率重建至关重要。然而，没有基准标记的倾斜系列的自动对准仍然是一个挑战。在这里，我们提出了一种新的对齐方法的基础上尺度不变特征变换（SIFT）的无标记对齐。该方法包括兴趣点（特征）的检测和定位、特征匹配、特征跟踪和投影参数优化。该方法实现了一个高度可靠的匹配策略和跟踪模型，以检测大量的特征轨迹。此外，设计了一种增量光束法平差方法，以容忍噪声数据，并确保投影参数的准确估计。我们的方法进行了评估与一些实验数据，结果显示出改进的对准精度与当前的基准标记对准和随后的更高分辨率的断层扫描。(C)由Elsevier Inc.出版。
In electron tomography, alignment accuracy is critical for high-resolution reconstruction. However, the automatic alignment of a tilt series without fiducial markers remains a challenge. Here, we propose a new alignment method based on Scale-Invariant Feature Transform (SIFT) for marker-free alignment. The method covers the detection and localization of interest points (features), feature matching, feature tracking and optimization of projection parameters. The proposed method implements a highly reliable matching strategy and tracking model to detect a huge number of feature tracks. Furthermore, an incremental bundle adjustment method is devised to tolerate noise data and ensure the accurate estimation of projection parameters. Our method was evaluated with a number of experimental data, and the results exhibit an improved alignment accuracy comparable with current fiducial marker alignment and subsequent higher resolution of tomography. (C) 2014 Published by Elsevier Inc.