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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.01097 |
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| _version_ | 1866914627036643328 |
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| author | Zhang, Jing Zhao, Tengfei Hu, ShiYu Zhao, Xin |
| author_facet | Zhang, Jing Zhao, Tengfei Hu, ShiYu Zhao, Xin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_01097 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robust single-particle cryo-EM image denoising and restoration Zhang, Jing Zhao, Tengfei Hu, ShiYu Zhao, Xin Computer Vision and Pattern Recognition 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. |
| title | Robust single-particle cryo-EM image denoising and restoration |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2401.01097 |