Feature Adaptive Sampling for Scanning Electron MicroscopyScientific Reports, 6
Abstract: A new method for the image acquisition in scanning electron microscopy (SEM) was introduced. The method used adaptively increased pixel-dwell times to improve the signal-to-noise ratio (SNR) in areas of high detail. In areas of low detail, the electron dose was reduced on a per pixel basis, and a-posteriori image processing techniques were applied to remove the resulting noise. The technique was realized by scanning the sample twice. The first, quick scan used small pixel-dwell times to generate a first, noisy image using a low electron dose. This image was analyzed automatically, and a software algorithm generated a sparse pattern of regions of the image that require additional sampling. A second scan generated a sparse image of only these regions, but using a highly increased electron dose. By applying a selective low-pass filter and combining both datasets, a single image was generated. The resulting image exhibited a factor of ≈3 better SNR than an image acquired with uniform sampling on a Cartesian grid and the same total acquisition time. This result implies that the required electron dose (or acquisition time) for the adaptive scanning method is a factor of ten lower than for uniform scanning.
Combined Tilt- and Focal-Series Tomography for HAADF-STEMMicroscopy Today, 24(3):26-30
Abstract: A new aid to tomography in the scanning transmission electron microscope (STEM) is called combined tilt- and focal-series (CTFS). This software controls the recording of a tilt series where for each specimen tilt an entire focal series is recorded. This approach is particularly useful for thick specimens where the tilt range may be limited. Use of CTFS leads to a significant reduction of the missing wedge effect and a better representation of the 3D shapes of features in the specimen.
On geometric artifacts in cryo electron tomographyUltramicroscopy, 163:48-61
Abstract: Single-tilt scheme is nowadays the prevalent acquisition geometry in electron tomography and subtomogram averaging experiments. Being an incomplete scheme that induces ill-posedness in the sense of the X-ray or Radon transform inverse problem, it introduces a number of artifacts that directly influence the quality of tomographic reconstructions. Though individually described by different authors before, a systematic study of these acquisition geometry-related artifacts in one place and across representative set of reconstruction methods has not been, to our knowledge, performed before. Moreover, the effects of these artifacts on the reconstructed density are sometimes misinterpreted, attributing them to the wrong cause, especially if their effects accumulate. In this work, we systematically study the major artifacts of single-tilt geometry known as the missing wedge (incomplete projection set problem), the missing information and the specimen-level interior problem (long-object problem). First, we illustratively describe, using a unified terminology, how and why these artifacts arise and when they can be avoided. Next, we describe the effects of these artifacts on the reconstructions across all major classes of reconstruction methods, including newly-appeared methods like the Iterative Nonuniform fast Fourier transform based Reconstruction method (INFR) and the Progressive Stochastic Reconstruction Technique (PSRT). Finally, we draw conclusions and recommendations on numerous points, especially regarding the mutual influence of the geometric artifacts, ability of different reconstruction methods to suppress them as well as implications to the interpretation of both electron tomography and subtomogram averaging experiments.