Noise-Transfer2Clean: denoising cryo-EM images based on noise modeling and transfer.

ABSTRACT:

Motivation

Cryo-electron microscopy (cryo-EM) is a widely used technology for ultrastructure determination, which constructs the 3D structures of protein and macromolecular complex from a set of 2D micrographs. However, limited by the electron beam dose, the micrographs in cryo-EM generally suffer from the extremely low signal-to-noise ratio (SNR), which hampers the efficiency and effectiveness of downstream analysis. Especially, the noise in cryo-EM is not simple additive or multiplicative noise whose statistical characteristics are quite different from the ones in natural image, extremely shackling the performance of conventional denoising methods.

Results

Here, we introduce the Noise-Transfer2Clean (NT2C), a denoising deep neural network (DNN) for cryo-EM to enhance image

SUBMITTER: Li H 

PROVIDER: S-EPMC8963287 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature