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Spline-based image-to-volume registratio ... dimensional electron microscopy
Spline-based image-to-volume registration for three-dimensional electron microscopy
7335
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.
Jonić S, Sorzano CO, Thévenaz P, El-Bez C, De Carlo S, Unser M
Ultramicroscopy
2005-07-01 00:00
103
4
303-17
Algorithms,Bacteriorhodopsins,Image Processing, Computer-Assisted,Microscopy, Electron,Models, Molecular,Bacteriorhodopsins
Biomedical Imaging Group, Ecole polytechnique fédérale de Lausanne (EPFL), CH-1015 Lausanne VD, Switzerland. Slavika.Jonic@lmcp.jussieu.fr
0304-3991
10.1016/j.ultramic.2005.02.002
S0304-3991(05)00017-3
0
False
15885434
