Electrical and Computer Engineering Department, University of Utah, Utah, USA.
J Neurosci Methods. 2010 Oct 30;193(1):132-44. doi: 10.1016/j.jneumeth.2010.08.001. Epub 2010 Aug 14.
We describe a computationally efficient and robust, fully-automatic method for large-scale electron microscopy image registration. The proposed method is able to construct large image mosaics from thousands of smaller, overlapping tiles with unknown or uncertain positions, and to align sections from a serial section capture into a common coordinate system. The method also accounts for nonlinear deformations both in constructing sections and in aligning sections to each other. The underlying algorithms are based on the Fourier shift property which allows for a computationally efficient and robust method. We demonstrate results on two electron microscopy datasets. We also quantify the accuracy of the algorithm through a simulated image capture experiment. The publicly available software tools include the algorithms and a Graphical User Interface for easy access to the algorithms.
我们描述了一种计算效率高且稳健的全自动方法，用于大规模电子显微镜图像配准。所提出的方法能够从数千个具有未知或不确定位置的较小重叠瓦片构建大型图像拼接，并将来自连续切片捕获的切片对齐到公共坐标系中。该方法还考虑了在构建切片和相互对齐切片时的非线性变形。基础算法基于傅里叶频移特性，允许使用计算效率高且稳健的方法。我们在两个电子显微镜数据集上展示了结果。我们还通过模拟图像捕获实验来量化算法的准确性。可公开获取的软件工具包括算法和图形用户界面，可方便地访问算法。
