English

Robust single-particle cryo-EM image denoising and restoration

Computer Vision and Pattern Recognition 2024-01-03 v1

Abstract

Cryo-electron microscopy (cryo-EM) has achieved near-atomic level resolution of biomolecules by reconstructing 2D micrographs. However, the resolution and accuracy of the reconstructed particles are significantly reduced due to the extremely low signal-to-noise ratio (SNR) and complex noise structure of cryo-EM images. In this paper, we introduce a diffusion model with post-processing framework to effectively denoise and restore single particle cryo-EM images. Our method outperforms the state-of-the-art (SOTA) denoising methods by effectively removing structural noise that has not been addressed before. Additionally, more accurate and high-resolution three-dimensional reconstruction structures can be obtained from denoised cryo-EM images.

Keywords

Cite

@article{arxiv.2401.01097,
  title  = {Robust single-particle cryo-EM image denoising and restoration},
  author = {Jing Zhang and Tengfei Zhao and ShiYu Hu and Xin Zhao},
  journal= {arXiv preprint arXiv:2401.01097},
  year   = {2024}
}

Comments

This paper is accepted to ICASSP 2024

R2 v1 2026-06-28T14:06:41.963Z