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Probabilistic Principal Component Analysis using Expectation Maximization (PPCA-EM) for Analyzing 3D Volumes with Missing Data
2010
Microscopy and Microanalysis
There are different techniques to obtain 3D structures of macromolecular assemblies from electron micrographs: electron tomography with either single-axis, dual-axes or conical tilting [1,2], random conical reconstruction [3, 4] , angular reconstitution [5] , and orthogonal tilting reconstruction [6] . The techniques including tilting are the most suitable for investigating structures of heterogeneous samples. However, most tilting techniques leave out areas of missing data in the 3D
doi:10.1017/s143192761005734x
fatcat:c5i4q7cswzdqjjty7lxr3go7iq