Viewing angle classification of cryo-electron microscopy images using eigenvectors

A. Singer, Z. Zhao, Y. Shkolnisky, R. Hadani

Research output: Contribution to journalArticle

Abstract

The cryo-electron microscopy (cryo-EM) reconstruction problem is to find the three-dimensional structure of a macromolecule given noisy versions of its two-dimensional projection images at unknown random directions. We introduce a new algorithm for identifying noisy cryo-EM images of nearby viewing angles. This identification is an important first step in three-dimensional structure determination of macromolecules from cryo-EM, because once identified, these images can be rotationally aligned and averaged to produce “class averages” of better quality. The main advantage of our algorithm is its extreme robustness to noise. The algorithm is also very efficient in terms of running time and memory requirements, because it is based on the computation of the top few eigenvectors of a specially designed sparse Hermitian matrix. These advantages are demonstrated in numerous numerical experiments.
Original languageEnglish (US)
Pages (from-to)723-759
Number of pages37
JournalSIAM Journal on Imaging Sciences
Volume4
Issue number2
DOIs
StatePublished - 2011
Externally publishedYes

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