A binary segmentation approach for boxing ribosome particles in cryo EM micrographs.

TitleA binary segmentation approach for boxing ribosome particles in cryo EM micrographs.
Publication TypeJournal Article
Year of Publication2004
AuthorsAdiga, U, Malladi, R, Baxter, B, Glaeser, RM
JournalJ Struct Biol
Date Published01/2004
KeywordsAlgorithms, Anisotropy, Automatic Data Processing, Cryoelectron Microscopy, Image Enhancement, Image Processing, Computer-Assisted, Particle Size, Pattern Recognition, Automated, Ribosomes, Software Design

Three-dimensional reconstruction of ribosome particles from electron micrographs requires selection of many single-particle images. Roughly 100,000 particles are required to achieve approximately 10 A resolution. Manual selection of particles, by visual observation of the micrographs on a computer screen, is recognized as a bottleneck in automated single-particle reconstruction. This paper describes an efficient approach for automated boxing of ribosome particles in micrographs. Use of a fast, anisotropic non-linear reaction-diffusion method to pre-process micrographs and rank-leveling to enhance the contrast between particles and the background, followed by binary and morphological segmentation constitute the core of this technique. Modifying the shape of the particles to facilitate segmentation of individual particles within clusters and boxing the isolated particles is successfully attempted. Tests on a limited number of micrographs have shown that over 80% success is achieved in automatic particle picking.

Alternate JournalJ. Struct. Biol.
PubMed ID15065681

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