Showing papers on "Contrast transfer function published in 2019"

Design for a 10 KeV Multi-Pass Transmission Electron Microscope

Abstract: Multi-pass transmission electron microscopy (MPTEM) has been proposed as a way to reduce damage to radiation-sensitive materials. For the field of cryo-electron microscopy (cryo-EM), this would significantly reduce the number of projections needed to create a 3D model and would allow the imaging of lower-contrast, more heterogeneous samples. We have designed a 10 keV proof-of-concept MPTEM. The column features fast-switching gated electron mirrors which cause each electron to interrogate the sample multiple times. A linear approximation for the multi-pass contrast transfer function (CTF) is developed to explain how the resolution depends on the number of passes through the sample.

2.7 Å cryo-EM structure of vitrified M. musculus H-chain apoferritin from 200 keV “screening microscope”

Abstract: Here we present the structure of mouse H-chain apoferritin at 2.7 A (FSC=0.143) solved by single particle cryogenic electron microscopy (cryo-EM) using a 200 kV device. Data were collected using a compact, two-lens illumination system with a constant power objective lens, without the use of energy filters or aberration correctors. Coulomb potential maps reveal clear densities for main chain carbonyl oxygens, residue side chains (including alternative conformations) and bound solvent molecules. We argue that the advantages offered by (a) the high electronic and mechanical stability of the microscope, (b) the high emission stability and low beam energy spread of the high brightness Field Emission Gun (x-FEG), (c) direct electron detection technology and (d) particle-based Contrast Transfer Function (CTF) refinement have contributed to achieving resolution close to the Rayleigh limit. Overall, we show that basic electron optical settings for automated cryo-electron microscopy imaging, widely thought of as a "screening cryo-microscope", can be used to determine structures approaching atomic resolution.

Contrast transfer function of de-noising algorithms.

Abstract: This paper presents a comprehensive study on the contrast transfer function of de-noising algorithms. In order to cover a broad variety of methods, 45 de-noising algorithms are chosen considering their recognized efficiency in the different application domains of image processing. Advanced methods are targeted: wavelet transform-based algorithms with Daubechies, symlets, curvelets, contourlets, patch-based methods such as BM3D, NL-means algorithms and deep learning approaches; in addition, classical spatial filtering methods are considered, such as Wiener, median, Gauss filtering, and adaptive filtering approaches such as anisotropic diffusion and synthetic aperture radar filtering. The contrast transfer function is provided for each algorithm. Ranking of the set of de-noising algorithms is established according to proposed metrics. The paper provides practical methodology and novel results dedicated to the evaluation of the contrast transfer function of de-noising approaches from literature.

Transmission point spread function of a turbid slab.

Abstract: A transmission point spread function characterizes the spatial distribution of light transmitted through a turbid slab. Because of scatter due to turbidity, light diffuses and the distribution of photons on exiting the slab may be very different from that upon entering the slab. Using the multiple-path model of reflection and transmission, the transmission point spread function and related modulation transfer function are derived. The analytic expression for the point spread function is compared to a Monte Carlo simulation of photon transmission. The transmission modulation transfer function is used to define a measure of visibility through the turbid slab-a contrast transfer function.

Hough Based Evolutions for Enhancing Structures in 3D Electron Microscopy

Abstract: Connecting interrupted line-like structures is a frequent problem in image processing. Here we focus on the specific needs that occur in 3D biophysical data analysis in electron microscopy (EM). We introduce a powerful framework for connecting line-like structures in 3D data sets by combining a specific semilocal Hough transform with a directional evolution equation. The Hough transform allows to find the principal orientations of the local structures in a robust way, and the evolution equation is designed as a partial differential equation that smoothes along these principal orientations. We evaluate the performance of our method for enhancing structures in both synthetic and real-world EM data. In contrast to traditional structure tensor based methods such as coherence-enhancing diffusion, our method can handle the missing wedge problem in EM, also known as limited angle tomography problem. A modified version of our approach is also able to tackle the discontinuities created due to the contrast transfer function correction of EM images.

Nanoscale x-ray holo-tomography of human brain tissue with phase retrieval based on multiphoton energy recordings

Abstract: X-ray cone-beam holo-tomography of unstained tissue from the human central nervous system reveals details down to sub-cellular length scales.1 This visualization of variations in the electron density of the sample is based on phase contrast techniques using intensities formed by self-interference of the beam between object and detector. Phase retrieval inverts diffraction and overcomes the phase problem by constraints such as several measurements at different Fresnel numbers for a single projection. Therefore, the object-to-detector distance (defocus) can be varied. However, for cone beam geometry, changing defocus changes magnification, which can be problematic in view of image processing and resolution. Alternatively, the photon energy can be altered (multi-E). Far from absorption edges, multi-E data yield the wavelength independent electron density. In this contribution we present multi-E holo-tomography at the GINIX setup of the P10 beamline at DESY. The instrument is based on a combined optics of elliptical mirrors and an x-ray waveguide positioned in the focal plane for further coherence, spatial Filtering and high numerical aperture.2 Previous results showed the suitability of this instrument for nanoscale tomography of unstained brain tissue.1 We demonstrate that upon energy variation, the focal spot is stable enough for imaging. To this end, a double crystal monochromator and automated alignment routines are required. Three tomograms of human brain tissue were recorded and jointly analyzed using phase retrieval based on the contrast transfer function formalism generalized to multiple photon energies. Variations of the electron density of the sample are successfully reconstructed.

Robust contrast-transfer-function phase retrieval via flexible deep learning networks: publisher’s note

Abstract: This publisher’s note contains corrections to Opt. Lett.44, 5141 (2019)OPLEDP0146-959210.1364/OL.44.005141.