  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.
