Developing a denoising filter for electron microscopy and tomography data in the cloud.

ABSTRACT: The low radiation conditions and the predominantly phase-object image formation of cryo-electron microscopy (cryo-EM) result in extremely high noise levels and low contrast in the recorded micrographs. The process of single particle or tomographic 3D reconstruction does not completely eliminate this noise and is even capable of introducing new sources of noise during alignment or when correcting for instrument parameters. The recently developed Digital Paths Supervised Variance (DPSV) denoising filter uses local variance information to control regional noise in a robust and adaptive manner. The performance of the DPSV filter was evaluated in this review qualitatively and quantitatively using simulated and experimental data from cryo-EM and tomography in two and three dimensions. We also as

SUBMITTER: Starosolski Z 

PROVIDER: S-EPMC3467108 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature