Automated particle correspondence and accurate tilt-axis detection in tilted-image pairs.

Tilted electron microscope images are routinely collected for an ab initio structure reconstruction as a part of the Random Conical Tilt (RCT) or Orthogonal Tilt Reconstruction (OTR) methods, as well as for various applications using the "free-hand" procedure. These procedures all require identification of particle pairs in two corresponding images as well as accurate estimation of the tilt-axis used to rotate the electron microscope (EM) grid. Here we present a computational approach, PCT (particle correspondence from tilted pairs), based on tilt-invariant context and projection matching that addresses both problems.

Minimizing electrostatic charging of an aperture used to produce in-focus phase contrast in the TEM.

Microfabricated devices designed to provide phase contrast in the transmission electron microscope must be free of phase distortions caused by unexpected electrostatic effects. We find that such phase distortions occur even when a device is heated to 300 °C during use in order to avoid the formation of polymerized, carbonaceous contamination. Remaining factors that could cause unwanted phase distortions include patchy variations in the work function of a clean metal surface, radiation-induced formation of a localized oxide layer, and creation of a contact potential between an irradiated area and the surround due to radiation-induced structural changes.

Ranking TEM cameras by their response to electron shot noise.

We demonstrate two ways in which the Fourier transforms of images that consist solely of randomly distributed electrons (shot noise) can be used to compare the relative performance of different electronic cameras. The principle is to determine how closely the Fourier transform of a given image does, or does not, approach that of an image produced by an ideal camera, i.e.

Experimental evaluation of support vector machine-based and correlation-based approaches to automatic particle selection.

The goal of this study is to evaluate the performance of software for automated particle-boxing, and in particular the performance of a new tool (TextonSVM) that recognizes the characteristic texture of particles of interest. As part of a high-throughput protocol, we use human editing that is based solely on class-average images to create final data sets that are enriched in what the investigator considers to be true-positive particles. The Fourier shell correlation (FSC) function is then used to characterize the homogeneity of different single-particle data sets that are derived from the same micrographs by two or more alternative methods.

Precise beam-tilt alignment and collimation are required to minimize the phase error associated with coma in high-resolution cryo-EM.

Electron microscopy at a resolution of 0.4nm or better requires more careful adjustment of the illumination than is the case at a resolution of 0.8nm.