02034nas a2200361 4500008004100000022001400041245010100055210006900156260001200225300001100237490000800248520093900256653001501195653002001210653002801230653005301258653004001311653003101351653001301382653001801395653001401413653002601427653001301453653002401466100001701490700001701507700002101524700001801545700001901563700001901582700002301601856004801624 2005 eng d a1047-847700aParticle picking by segmentation: a comparative study with SPIDER-based manual particle picking.0 aParticle picking by segmentation a comparative study with SPIDER c12/2005 a211-200 v1523 a
Boxing hundreds of thousands of particles in low-dose electron micrographs is one of the major bottle-necks in advancing toward achieving atomic resolution reconstructions of biological macromolecules. We have shown that a combination of pre-processing operations and segmentation can be used as an effective, automatic tool for identifying and boxing single-particle images. This paper provides a brief description of how this method has been applied to a large data set of micrographs of ice-embedded ribosomes, including a comparative analysis of the efficiency of the method. Some results on processing micrographs of tripeptidyl peptidase II particles are also shown. In both cases, we have achieved our goal of selecting at least 80% of the particles that an expert would select with less than 10% false positives.
10aAlgorithms10aAminopeptidases10aCryoelectron Microscopy10aDipeptidyl-Peptidases and Tripeptidyl-Peptidases10aImage Processing, Computer-Assisted10aImaging, Three-Dimensional10aInternet10aParticle Size10aRibosomes10aSerine Endopeptidases10aSoftware10aSoftware Validation1 aAdiga, Umesh1 aBaxter, Bill1 aHall, Richard, J1 aRockel, Beate1 aRath, Bimal, K1 aFrank, Joachim1 aGlaeser, Robert, M uhttp://www.ncbi.nlm.nih.gov/pubmed/1633022902292nas a2200301 4500008004100000022001400041245008900055210006900144260001200213300001100225490000800236520138600244653001501630653001501645653003001660653002801690653002201718653004001740653001801780653003501798653001401833653002001847100001701867700001801884700001701902700002301919856004801942 2004 eng d a1047-847700aA binary segmentation approach for boxing ribosome particles in cryo EM micrographs.0 abinary segmentation approach for boxing ribosome particles in cr c01/2004 a142-510 v1453 aThree-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.
10aAlgorithms10aAnisotropy10aAutomatic Data Processing10aCryoelectron Microscopy10aImage Enhancement10aImage Processing, Computer-Assisted10aParticle Size10aPattern Recognition, Automated10aRibosomes10aSoftware Design1 aAdiga, Umesh1 aMalladi, Ravi1 aBaxter, Bill1 aGlaeser, Robert, M uhttp://www.ncbi.nlm.nih.gov/pubmed/15065681