CASIA OpenIR  > 复杂系统认知与决策实验室  > 智能系统与工程
Robust Single-particle Cryo-EM Image Denoising and Restoration
Zhang Jing1,2; Tengfei Zhao1; ShiYu Hu1; Xin Zhao2
2024
Conference Name2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Conference Date14-19 April 2024
Conference PlaceSeoul, Korea,
Abstract

Cryo-electron microscopy (cryo-EM) has achieved nearatomic 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.

Indexed ByEI
Sub direction classification图像视频处理与分析
planning direction of the national heavy laboratoryAI For Science
Paper associated data
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57460
Collection复杂系统认知与决策实验室_智能系统与工程
Corresponding AuthorXin Zhao
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Science and Technology Beijing
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang Jing,Tengfei Zhao,ShiYu Hu,et al. Robust Single-particle Cryo-EM Image Denoising and Restoration[C],2024.
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