Compressed sensing electron tomography of needle-shaped biological specimens--Potential for improved reconstruction fidelity with reduced dose.

Electron tomography is an invaluable method for 3D cellular imaging. The technique is, however, limited by the specimen geometry, with a loss of resolution due to a restricted tilt range, an increase in specimen thickness with tilt, and a resultant need for subjective and time-consuming manual segmentation. Here we show that 3D reconstructions of needle-shaped biological samples exhibit isotropic resolution, facilitating improved automated segmentation and feature detection. By using scanning transmission electron tomography, with small probe convergence angles, high spatial resolution is maintained over large depths of field and across the tilt range. Moreover, the application of compressed sensing methods to the needle data demonstrates how high fidelity reconstructions may be achieved with far fewer images (and thus greatly reduced dose) than needed by conventional methods. These findings open the door to high fidelity electron tomography over critically relevant length-scales, filling an important gap between existing 3D cellular imaging techniques.The research leading to these results has received funding from the European Union Seventh Framework Programme under Grant Agreement 312483 - ESTEEM2 (Integrated Infrastructure Initiative–I3), as well as from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC grant agreement 291522 - 3DIMAGE. B.W. and E.S. acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG) within the framework of the SPP 1570 as well as through the Cluster of Excellence “Engineering of Advanced Materials” at the Friedrich-Alexander-Universität ErlangenNürnberg. G.D. and C.D. acknowledge funding from the ERC under grant number 259619 PHOTO EM. B.W. acknowledges the Research Training Group “Disperse Systems for Electronic Applications” (DFG GEPRIS GRK 1161). R.L. acknowledges a Junior Research Fellowship from Clare College.This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ultramic.2015.10.02

Stabilization and Imaging of Cohesionless Soil Specimens

abstract: This dissertation describes development of a procedure for obtaining high quality, optical grade sand coupons from frozen sand specimens of Ottawa 20/30 sand for image processing and analysis to quantify soil structure along with a methodology for quantifying the microstructure from the images. A technique for thawing and stabilizing frozen core samples was developed using optical grade Buehler® Epo-Tek® epoxy resin, a modified triaxial cell, a vacuum/reservoir chamber, a desiccator, and a moisture gauge. The uniform epoxy resin impregnation required proper drying of the soil specimen, application of appropriate confining pressure and vacuum levels, and epoxy mixing, de-airing and curing. The resulting stabilized sand specimen was sectioned into 10 mm thick coupons that were planed, ground, and polished with progressively finer diamond abrasive grit levels using the modified Allied HTP Inc. polishing method so that the soil structure could be accurately quantified using images obtained with the use of an optical microscopy technique. Illumination via Bright Field Microscopy was used to capture the images for subsequent image processing and sand microstructure analysis. The quality of resulting images and the validity of the subsequent image morphology analysis hinged largely on employment of a polishing and grinding technique that resulted in a flat, scratch free, reflective coupon surface characterized by minimal microstructure relief and good contrast between the sand particles and the surrounding epoxy resin. Subsequent image processing involved conversion of the color images first to gray scale images and then to binary images with the use of contrast and image adjustments, removal of noise and image artifacts, image filtering, and image segmentation. Mathematical morphology algorithms were used on the resulting binary images to further enhance image quality. The binary images were then used to calculate soil structure parameters that included particle roundness and sphericity, particle orientation variability represented by rose diagrams, statistics on the local void ratio variability as a function of the sample size, and the local void ratio distribution histograms using Oda's method and Voronoi tessellation method, including the skewness, kurtosis, and entropy of a gamma cumulative probability distribution fit to the local void ratio distribution.Dissertation/ThesisM.S. Civil Engineering 201

New Algorithms in Computational Microscopy

Microscopy plays an important role in providing tools to microscopically observe objects and their surrounding areas with much higher resolution ranging from the scale between molecular machineries (angstrom) and individual cells (micrometer). Under microscopes, illumination, such as visible light and electron-magnetic radiation/electron beam, interacts with samples, then they are scattered to a plane and are recorded. Computational microscopy corresponds to image reconstruction from these measurements as well as improving quality of the images. Along with the evolution of microscopy, new studies are discovered and algorithms need development not only to provide high-resolution imaging but also to decipher new and advanced research. In this dissertation, we focus on algorithm development for inverse problems in microscopy, specifically phase retrieval and tomography, and the application of these techniques to machine learning. The four studies in this dissertation demonstrates the use of optimization and calculus of variation in imaging science and other different disciplines.Study 1 focuses on coherent diffractive imaging (CDI) or phase retrieval, a non-linear inverse problem that aims to recover 2D image from it Fourier transforms in modulus taking into account that extra information provided by oversampling as a second constraint. To solve this two-constraint minimization, we proceed from Hamilton-Jacobi partial differential equation (HJ-PDE) and its Hopf-Lax formula. Introducing generalized Bregman distance to the HJ-PDE and applying Legendre transform, we derive our generalized proximal smoothing (GPS) algorithm under the form of primal-dual hybrid gradient (PDHG). While the reflection operator, known as extrapolating momentum, helps overcome local minima, the smoothing by the generalized Bregman distance is adjusted to improve convergence and consistency of phase retrieval.Study 2 focuses on electron tomography, 3D image reconstruction from a set of 2D projections obtained from a transmission electron microscope (TEM) or X-ray microscope. Notice that current tomography algorithms limit to a single tilt axis and fail to work with fully or partially missing data. In the light of calculus of variations and Fourier slice theorem (FST), we develop a highly accurate tomography iterative algorithm that can provide higher resolution imaging and work with missing data as well as has capability to perform multiple-tilt-axis tomography. The algorithm is further developed to work with non-isolated objects and partially-blocked projections which have become more popular in experiment. The success of real space iterative reconstruction engine (RESIRE) opens a new era to the study of tomography in material science and magnetic structures (vector Tomography).Study 3 and 4 are applications of our algorithms to machine learning. Study 3 develops a backward Euler method in a stochastic manner to solve K-mean clustering, a well-known non-convex optimization problem. The algorithm has been shown to improve minimums and consistency, providing a new powerful tool to the class of classification techniques. Study 4 is a direct application of GPS to deep learning gradient descent algorithms. Linearizing the Hopf-Lax formula derived in GPS, we derive our method Laplacian smoothing gradient descent (LSGD), simply known as gradient smoothing. Our experiment shows that LSGD has the ability to search for better and flatter minimums, reduce variation, and obtain higher accuracy and consistency

Early stage phase separation of AlCoCr_0.75Cu_0.5FeNi high-entropy powder at the nanoscale

High entropy alloys are generally considered to be single phase material. This state is, however, typically a non-equilibrium state after fabrication at high cooling rates. Phase constitution after fabrication or heat treatment is mostly known for isothermal annealing only and for casts as well as rapidly quenched alloys. Knowledge on early phase separation stages of high entropy alloys and their mechanisms are missing so far. Here, we present results on phase separation at intermediate cooling rates, by characterization of gas atomized powder of the AlCoCr0.75Cu0.5FeNi alloy. Although investigation by X-ray diffraction and Electron Backscatter Diffraction indicates a single-phase nature of the powder particles, aberration-corrected scanning transmission electron microscopy and atom probe tomography reveal a nanoscale phase separation into Ni-Al-rich B2 and Fe-Cr-rich A2 regions as well as a high number density of 3.1x1024 Cu-rich clusters per m3 in the B2 matrix. The observed phase separation and cluster formation are linked to spinodal decomposition and nucleation processes, respectively. The study highlights that adequate characterization techniques need to be chosen when making statements about phase stability and structural evolution in compositionally complex alloys.Comment: 33 pages, 12 figure

Tomography applied to Lamb wave contact scanning nondestructive evaluation

The aging world-wide aviation fleet requires methods for accurately predicting the presence of structural flaws that compromise airworthiness in aircraft structures. Nondestructive Evaluation (NDE) provides the means to assess these structures quickly, quantitatively, and noninvasively. Ultrasonic guided waves, Lamb waves, are useful for evaluating the plate and shell structures common in aerospace applications. The amplitude and time-of-flight of Lamb waves depend on the material properties and thickness of a medium, and so they can be used to detect any areas of differing thickness or material properties which indicate flaws. By scanning sending and receiving transducers over an aircraft, large sections can be evaluated after a single pass. However, while this technique enables the detection of areas of structural deterioration, it does not allow for the quantification of the extent of that deterioration. Tomographic reconstruction with Lamb waves allows for the accurate reconstruction of the variation of quantities of interest, such as thickness, throughout the investigated region, and it presents the data as a quantitative map. The location, shape, and extent of any flaw region can then be easily extracted from this Tomographic image. Two Lamb wave tomography techniques using Parallel Projection tomography (PPT) and Cross Borehole tomography (CBT), are shown to accurately reconstruct flaws of interest to the aircraft industry. A comparison of the quality of reconstruction and practicality is then made between these two methods, and their limitations are discussed and shown experimentally. Higher order plate theory is used to derive analytical solutions for the scattering of the lowest order symmetric Lamb wave from a circular inclusion, and these solutions are used to explain the scattering effects seen in the Tomographic reconstructions. Finally, the means by which this scattering theory can be used to develop Lamb wave Tomographic algorithms that are more generally applicable in-the-field, is presented

Bioimage informatics in STED super-resolution microscopy

Optical microscopy is living its renaissance. The diffraction limit, although still physically true, plays a minor role in the achievable resolution in far-field fluorescence microscopy. Super-resolution techniques enable fluorescence microscopy at nearly molecular resolution. Modern (super-resolution) microscopy methods rely strongly on software. Software tools are needed all the way from data acquisition, data storage, image reconstruction, restoration and alignment, to quantitative image analysis and image visualization. These tools play a key role in all aspects of microscopy today – and their importance in the coming years is certainly going to increase, when microscopy little-by-little transitions from single cells into more complex and even living model systems. In this thesis, a series of bioimage informatics software tools are introduced for STED super-resolution microscopy. Tomographic reconstruction software, coupled with a novel image acquisition method STED< is shown to enable axial (3D) super-resolution imaging in a standard 2D-STED microscope. Software tools are introduced for STED super-resolution correlative imaging with transmission electron microscopes or atomic force microscopes. A novel method for automatically ranking image quality within microscope image datasets is introduced, and it is utilized to for example select the best images in a STED microscope image dataset.Siirretty Doriast