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Title:Cryo-electron microscopy image analysis using multi-frequency vector diffusion maps
Author(s):Fan, Yifeng
Advisor(s):Zhao, Zhizhen
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Cryo-Electron Microscopy
Image denoising.
Abstract:Cryo-electron microscopy (EM) single particle reconstruction is an entirely general technique for 3D structure determination of macromolecular complexes. However, because the images are taken at low electron dose, it is extremely hard to visualize the individual particle with low contrast and high noise level. In this thesis, we propose a novel approach called multi-frequency vector diffusion maps (MFVDM) to improve the efficiency and accuracy of cryo-EM 2D image classification and denoising. This framework incorporates different irreducible representations of the estimated alignment between similar images. In addition, we propose a graph filtering scheme to denoise the images using the eigenvalues and eigenvectors of the MFVDM matrices. Through both simulated and publicly available real data, we demonstrate that our proposed method is efficient and robust to noise compared with the state-of-the-art cryo-EM 2D class averaging and image restoration algorithms.
Issue Date:2019-12-09
Type:Thesis
URI:http://hdl.handle.net/2142/107837
Rights Information:Copyright 2020 Yifeng Fan
Date Available in IDEALS:2020-08-26
Date Deposited:2020-05


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