Robust single-particle cryo-EM image denoising and restoration
- Resource Type
- Working Paper
- Authors
- Zhang, Jing; Zhao, Tengfei; Hu, ShiYu; Zhao, Xin
- Source
- Subject
- Computer Science - Computer Vision and Pattern Recognition
- Language
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.
Comment: This paper is accepted to ICASSP 2024