A parallel algorithm for automatic particle identification in electron micrographs
RANDOM-FIELD MODEL; EXPECTATION-MAXIMIZATION; IMAGE SEGMENTATION; RECONSTRUCTION; MICROSCOPY; SELECTION; CRYOMICROSCOPY; Computer Science, Theory & Methods
Three dimensional reconstruction of large macromolecules like viruses at resolutions below 10 A requires a large set of projection images. Several automatic and semi-automatic particle detection algorithms have been developed along the years. We have developed a general technique designed to automatically identify the projection images of particles. The method is based on Markov random field modelling of the projected images and involves a preprocessing of electron micrographs followed by image segmentation and post processing. In this paper we discuss the basic ideas of the sequential algorithm and outline a parallel implementation of it.
High Performance Computing for Computational Science - Vecpar 2004
"A parallel algorithm for automatic particle identification in electron micrographs" (2005). Faculty Bibliography 2000s. 5677.