EE Seminar: Mor Cohen

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Mor Cohen, 
M.Sc. student under the supervision of Prof. Yoel Shkonisky and Prof. Arie Yeredor

Monday, February 16, 2015 at 15:30
Room 011, Kitot Bldg., Faculty of Engineering

Detecting Common Lines In Cryo-EM Images Using Maximum Likelihood

Abstract

The reconstruction of three dimensional structures from Cryo-EM images is often based on the “Angular Reconstitution” method in which a coordinate system is established from three projections, and the orientation of the particle in each image is deduced from common lines shared among the images. Detecting these common lines is usually performed by first denoising the images, which takes advantage of the large number of available images to improve their SNR, followed by computing correlations between radial lines in the images. This work presents a maximum likelihood (ML) algorithm for detecting common lines that takes advantage of the highly redundant data in a different way. The algorithm is based on a global iterative detector in which we jointly estimate and classify common lines using the data from all projection images. We demonstrate by simulations that the algorithm improves the detection rate of common lines compared to state of the art methods, and operates well even with non-white imaging noise.