Noise Analysis and Removal in 3D Electron Microscopy

Recent research in several fields such as Biotechnology and Healthcare has uncovered a vast number of applications where 3D Electron Microscopy (EM) is useful. However, images produced by 3D EM are in most cases severely degraded. These degradations arise due to a multitude of reasons, e.g. the complex electronics in the system, magnetic lens aberration, heating and motion stability, charging, etc. Although the raw, degraded images are currently used for analysis, their usefulness is limited because the degradations make visual distinction and automated analysis of biological features very difficult. In this work, we give an analysis of noise, as one of the most important degradations in 3D EM imaging. Next, we propose a Non-Local Means image restoration algorithm that exploits the derived noise characteristics. The proposed algorithm yields significant improvements compared to other state-of-the-art image restoration algorithms

X-ray tomography as a tool for detailed anatomical analysis

Wood identification, anatomical examination and retrieval of quantitative information arc important aspects of many research disciplines. Conventional light microscopy with a camera and (semi)automatic image analysis software is an often used methodology for these purposes. Morc advanced techniques such as fluorescence, scanning electron, transmission electron, confocal laser scanning and atomic force microscopy arc also part of the toolset answering to the need for detailed imaging. Fast, non-destructive visualization in three dimensions with high resolution combined with a broad field of view is sought-after, especially in combination with flexible software. A highly advanced supplement to the existing techniques, namely X-ray sub-micron tomography, meets these requirements. It enables the researcher to visualize the material with a voxel size approaching <1 mu m for small samples (<1 mm). Furthermore, with tailor-made processing software quantitative data about the wood in two and three dimensions can be obtained. Examples of visualization and analysis of four wood species arc given in this paper, focusing on the opportunities of tomography at micron and sub-micron resolution. X-ray computed tomography offers many possibilities for material research in general and wood science in specific, as a qualitative as well as a quantitative technique

Electron tomography at 2.4 {\AA} resolution

Transmission electron microscopy (TEM) is a powerful imaging tool that has found broad application in materials science, nanoscience and biology(1-3). With the introduction of aberration-corrected electron lenses, both the spatial resolution and image quality in TEM have been significantly improved(4,5) and resolution below 0.5 {\AA} has been demonstrated(6). To reveal the 3D structure of thin samples, electron tomography is the method of choice(7-11), with resolutions of ~1 nm^3 currently achievable(10,11). Recently, discrete tomography has been used to generate a 3D atomic reconstruction of a silver nanoparticle 2-3 nm in diameter(12), but this statistical method assumes prior knowledge of the particle's lattice structure and requires that the atoms fit rigidly on that lattice. Here we report the experimental demonstration of a general electron tomography method that achieves atomic scale resolution without initial assumptions about the sample structure. By combining a novel projection alignment and tomographic reconstruction method with scanning transmission electron microscopy, we have determined the 3D structure of a ~10 nm gold nanoparticle at 2.4 {\AA} resolution. While we cannot definitively locate all of the atoms inside the nanoparticle, individual atoms are observed in some regions of the particle and several grains are identified at three dimensions. The 3D surface morphology and internal lattice structure revealed are consistent with a distorted icosahedral multiply-twinned particle. We anticipate that this general method can be applied not only to determine the 3D structure of nanomaterials at atomic scale resolution(13-15), but also to improve the spatial resolution and image quality in other tomography fields(7,9,16-20).Comment: 27 pages, 17 figure

GENFIRE: A generalized Fourier iterative reconstruction algorithm for high-resolution 3D imaging

Tomography has made a radical impact on diverse fields ranging from the study of 3D atomic arrangements in matter to the study of human health in medicine. Despite its very diverse applications, the core of tomography remains the same, that is, a mathematical method must be implemented to reconstruct the 3D structure of an object from a number of 2D projections. In many scientific applications, however, the number of projections that can be measured is limited due to geometric constraints, tolerable radiation dose and/or acquisition speed. Thus it becomes an important problem to obtain the best-possible reconstruction from a limited number of projections. Here, we present the mathematical implementation of a tomographic algorithm, termed GENeralized Fourier Iterative REconstruction (GENFIRE). By iterating between real and reciprocal space, GENFIRE searches for a global solution that is concurrently consistent with the measured data and general physical constraints. The algorithm requires minimal human intervention and also incorporates angular refinement to reduce the tilt angle error. We demonstrate that GENFIRE can produce superior results relative to several other popular tomographic reconstruction techniques by numerical simulations, and by experimentally by reconstructing the 3D structure of a porous material and a frozen-hydrated marine cyanobacterium. Equipped with a graphical user interface, GENFIRE is freely available from our website and is expected to find broad applications across different disciplines.Comment: 18 pages, 6 figure