Jonić S, Sorzano C O S, Thévenaz P, El-Bez C, De Carlo S, Unser M
Biomedical Imaging Group, Ecole polytechnique fédérale de Lausanne (EPFL), CH-1015 Lausanne VD, Switzerland.
Ultramicroscopy. 2005 Jul;103(4):303-17. doi: 10.1016/j.ultramic.2005.02.002. Epub 2005 Mar 11.
This paper presents an algorithm based on a continuous framework for a posteriori angular and translational assignment in three-dimensional electron microscopy (3DEM) of single particles. Our algorithm can be used advantageously to refine the assignment of standard quantized-parameter methods by registering the images to a reference 3D particle model. We achieve the registration by employing a gradient-based iterative minimization of a least-squares measure of dissimilarity between an image and a projection of the volume in the Fourier transform (FT) domain. We compute the FT of the projection using the central-slice theorem (CST). To compute the gradient accurately, we take advantage of a cubic B-spline model of the data in the frequency domain. To improve the robustness of the algorithm, we weight the cost function in the FT domain and apply a "mixed" strategy for the assignment based on the minimum value of the cost function at registration for several different initializations. We validate our algorithm in a fully controlled simulation environment. We show that the mixed strategy improves the assignment accuracy; on our data, the quality of the angular and translational assignment was better than 2 voxel (i.e., 6.54 angstroms). We also test the performance of our algorithm on real EM data. We conclude that our algorithm outperforms a standard projection-matching refinement in terms of both consistency of 3D reconstructions and speed.
本文提出了一种基于连续框架的算法,用于单颗粒三维电子显微镜(3DEM)中的后验角度和平移分配。我们的算法可通过将图像配准到参考三维颗粒模型,有效地用于改进标准量化参数方法的分配。我们通过在傅里叶变换(FT)域中采用基于梯度的迭代最小化来实现图像与体积投影之间差异的最小二乘度量,从而实现配准。我们使用中心切片定理(CST)计算投影的FT。为了准确计算梯度,我们利用频域中数据的三次B样条模型。为了提高算法的鲁棒性,我们在FT域中对代价函数进行加权,并基于几种不同初始化在配准时代价函数的最小值应用“混合”分配策略。我们在完全受控的模拟环境中验证了我们的算法。我们表明混合策略提高了分配精度;在我们的数据上,角度和平移分配的质量优于2体素(即6.54埃)。我们还在真实的电子显微镜数据上测试了我们算法的性能。我们得出结论,我们的算法在三维重建的一致性和速度方面均优于标准投影匹配细化方法。