Knowledge Commons of Institute of Automation,CAS
Robust Single-particle Cryo-EM Image Denoising and Restoration | |
Zhang Jing1,2![]() ![]() ![]() | |
2024 | |
会议名称 | 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
会议日期 | 14-19 April 2024 |
会议地点 | Seoul, Korea, |
摘要 | 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. |
收录类别 | EI |
七大方向——子方向分类 | 图像视频处理与分析 |
国重实验室规划方向分类 | AI For Science |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57460 |
专题 | 复杂系统认知与决策实验室_智能系统与工程 |
通讯作者 | Xin Zhao |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Science and Technology Beijing |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhang Jing,Tengfei Zhao,ShiYu Hu,et al. Robust Single-particle Cryo-EM Image Denoising and Restoration[C],2024. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2401.01097v1.pdf(966KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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