title: Robust estimation for class averaging in cryo-EM Single Particle Reconstruction.
abstract: Single Particle Reconstruction (SPR) for Cryogenic Electron Microscopy (cryo-EM) aligns and averages the images extracted from micrographs to improve the Signal-to-Noise ratio (SNR). Outliers compromise the fidelity of the averaging. We propose a robust cross-correlation-like w-estimator for combating the effect of outliers on the average images in cryo-EM. The estimator accounts for the natural variation of signal contrast among the images and eliminates the need for a threshold for outlier rejection. We show that the influence function of our estimator is asymptotically bounded. Evaluations of the estimator on simulated and real cryo-EM images show good performance in the presence of outliers.
authors.forename: Chenxi
authors.initials: C
authors.lastname: Huang
authors.forename: Hemant D
authors.initials: HD
authors.lastname: Tagare
mesh_terms: D003198:Computer Simulation; D020285:Cryoelectron Microscopy / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D054657:Ribosome Subunits / Q000737:chemistry; D059629:Signal-To-Noise Ratio