%0 Journal Article %J J Struct Biol %D 2007 %T SPIRE: the SPIDER reconstruction engine. %A Baxter, Bill %A Leith, ArDean %A Frank, Joachim %K Computational Biology %K Image Processing, Computer-Assisted %K Software %K Software Design %X

SPIRE is a Python program written to modernize the user interaction with SPIDER, the image processing system for electron microscopical reconstruction projects. SPIRE provides a graphical user interface (GUI) to SPIDER for executing batch files of SPIDER commands. It also lets users quickly view the status of a project by showing the last batch files that were run, as well as the data files that were generated. SPIRE handles the flexibility of the SPIDER programming environment through configuration files: XML-tagged documents that describe the batch files, directory trees, and presentation of the GUI for a given type of reconstruction project. It also provides the capability to connect to a laboratory database, for downloading parameters required by batch files at the start of a project, and uploading reconstruction results at the end of a project.

%B J Struct Biol %V 157 %P 56-63 %8 01/2007 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/17055743 %N 1 %R 10.1016/j.jsb.2006.07.019 %0 Journal Article %J J Struct Biol %D 2004 %T A binary segmentation approach for boxing ribosome particles in cryo EM micrographs. %A Adiga, Umesh %A Malladi, Ravi %A Baxter, Bill %A Glaeser, Robert M %K Algorithms %K Anisotropy %K Automatic Data Processing %K Cryoelectron Microscopy %K Image Enhancement %K Image Processing, Computer-Assisted %K Particle Size %K Pattern Recognition, Automated %K Ribosomes %K Software Design %X

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.

%B J Struct Biol %V 145 %P 142-51 %8 01/2004 %G eng %U http://www.ncbi.nlm.nih.gov/pubmed/15065681 %N 1-2 %R 10.1016/j.jsb.2003.10.026