Cryo-electron microscopy image analysis using multi-frequency vector diffusion maps
Fan, Yifeng
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https://hdl.handle.net/2142/107837
Description
Title
Cryo-electron microscopy image analysis using multi-frequency vector diffusion maps
Author(s)
Fan, Yifeng
Issue Date
2019-12-09
Director of Research (if dissertation) or Advisor (if thesis)
Zhao, Zhizhen
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(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.
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