Macromolecule Particle Picking and Segmentation of a KLH Database by Unsupervised Cryo-EM Image Processing.

ABSTRACT: Segmentation is one of the most important stages in the 3D reconstruction of macromolecule structures in cryo-electron microscopy. Due to the variability of macromolecules and the low signal-to-noise ratio of the structures present, there is no generally satisfactory solution to this process. This work proposes a new unsupervised particle picking and segmentation algorithm based on the composition of two well-known image filters: Anisotropic (Perona-Malik) diffusion and non-negative matrix factorization. This study focused on keyhole limpet hemocyanin (KLH) macromolecules which offer both a top view and a side view. Our proposal was able to detect both types of views and separate them automatically. In our experiments, we used 30 images from the KLH dataset of 680 positive classified regio

SUBMITTER: Carrasco M 

PROVIDER: S-EPMC6995569 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature