CRYO-ELECTRON MICROSCOPY IMAGE DENOISING USING MULTI-FREQUENCY VECTOR DIFFUSION MAPS

Yifeng Fan, Zhizhen Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cryo-electron microscopy (EM) single particle reconstruction is a general technique for 3D structure determination of macromolecules. 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 paper, we propose a novel framework for cryo-EM single particle image denoising, which incorporates the recently developed multi-frequency vector diffusion maps [1] for improving the identification and alignment of images with similar viewing directions. In addition, we propose a novel filtering scheme combining graph signal processing and truncated Fourier-Bessel expansion of the projection images. 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 algorithms.

Original languageEnglish (US)
Title of host publication2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings
PublisherIEEE Computer Society
Pages3463-3467
Number of pages5
ISBN (Electronic)9781665441155
DOIs
StatePublished - 2021
Externally publishedYes
Event2021 IEEE International Conference on Image Processing, ICIP 2021 - Anchorage, United States
Duration: Sep 19 2021Sep 22 2021

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2021-September
ISSN (Print)1522-4880

Conference

Conference2021 IEEE International Conference on Image Processing, ICIP 2021
Country/TerritoryUnited States
CityAnchorage
Period9/19/219/22/21

Keywords

  • Cryo-electron microscopy
  • Image denoising
  • Multi-frequency vector diffusion maps

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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