“Accurate segmentation of dense nanoparticles by partially discrete electron tomography”. Roelandts T, Batenburg KJ, Biermans E, Kübel C, Bals S, Sijbers J, Ultramicroscopy 114, 96 (2012). http://doi.org/10.1016/j.ultramic.2011.12.003
Abstract: Accurate segmentation of nanoparticles within various matrix materials is a difficult problem in electron tomography. Due to artifacts related to image series acquisition and reconstruction, global thresholding of reconstructions computed by established algorithms, such as weighted backprojection or SIRT, may result in unreliable and subjective segmentations. In this paper, we introduce the Partially Discrete Algebraic Reconstruction Technique (PDART) for computing accurate segmentations of dense nanoparticles of constant composition. The particles are segmented directly by the reconstruction algorithm, while the surrounding regions are reconstructed using continuously varying gray levels. As no properties are assumed for the other compositions of the sample, the technique can be applied to any sample where dense nanoparticles must be segmented, regardless of the surrounding compositions. For both experimental and simulated data, it is shown that PDART yields significantly more accurate segmentations than those obtained by optimal global thresholding of the SIRT reconstruction.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 34
DOI: 10.1016/j.ultramic.2011.12.003
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“Ultra-high resolution electron tomography for materials science : a roadmap”. Batenburg KJ, Bals S, Van Aert S, Roelandts T, Sijbers J, Microscopy and microanalysis 17, 934 (2011). http://doi.org/10.1017/S143192761100554X
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 1.891
DOI: 10.1017/S143192761100554X
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“3D imaging of nanomaterials by discrete tomography”. Batenburg KJ, Bals S, Sijbers J, Kübel C, Midgley PA, Hernandez JC, Kaiser U, Encina ER, Coronado EA, Van Tendeloo G, Ultramicroscopy 109, 730 (2009). http://doi.org/10.1016/j.ultramic.2009.01.009
Abstract: The field of discrete tomography focuses on the reconstruction of samples that consist of only a few different materials. Ideally, a three-dimensional (3D) reconstruction of such a sample should contain only one grey level for each of the compositions in the sample. By exploiting this property in the reconstruction algorithm, either the quality of the reconstruction can be improved significantly, or the number of required projection images can be reduced. The discrete reconstruction typically contains fewer artifacts and does not have to be segmented, as it already contains one grey level for each composition. Recently, a new algorithm, called discrete algebraic reconstruction technique (DART), has been proposed that can be used effectively on experimental electron tomography datasets. In this paper, we propose discrete tomography as a general reconstruction method for electron tomography in materials science. We describe the basic principles of DART and show that it can be applied successfully to three different types of samples, consisting of embedded ErSi2 nanocrystals, a carbon nanotube grown from a catalyst particle and a single gold nanoparticle, respectively.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 220
DOI: 10.1016/j.ultramic.2009.01.009
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“Quantitative three-dimensional reconstruction of catalyst particles for bamboo-like carbon nanotubes”. Bals S, Batenburg J, Verbeeck J, Sijbers J, Van Tendeloo G, Nano letters 7, 3669 (2007). http://doi.org/10.1021/nl071899m
Abstract: The three-dimensional (3D) structure and chemical composition of bamboo-like carbon nanotubes including the catalyst particles that are. used during their growth are studied by discrete electron tomography in combination with energy-filtered transmission electron microscopy. It is found that cavities are present in the catalyst particles. Furthermore, only a small percentage of the catalyst particles consist of pure Cu, since a large volume fraction of the particles is oxidized to CU(2)0. These volume fractions are determined quantitatively from 3D reconstructions obtained by discrete tomography.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 12.712
Times cited: 78
DOI: 10.1021/nl071899m
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“StatSTEM: An efficient program for accurate and precise model-based quantification of atomic resolution electron microscopy images”. De Backer A, van den Bos KHW, Van den Broek W, Sijbers J, Van Aert S, Journal of physics : conference series
T2 –, Electron Microscopy and Analysis Group Conference 2017 (EMAG2017), 3-6 July 2017, Manchester, UK 902, 012013 (2017). http://doi.org/10.1088/1742-6596/902/1/012013
Abstract: An efficient model-based estimation algorithm is introduced in order to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for the overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, is investigated. The highest attainable precision is reached even for low dose images. Furthermore, advantages of the model- based approach taking into account overlap between neighbouring columns are highlighted. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.
Keywords: P1 Proceeding; Electron microscopy for materials research (EMAT); Vision lab
Times cited: 1
DOI: 10.1088/1742-6596/902/1/012013
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“Investigating lattice strain in Au nanodecahedrons”. Goris B, De Beenhouwer J, de Backer A, Zanaga D, Batenburg J, Sanchez-Iglesias A, Liz-Marzan L, Van Aert S, Sijbers J, Van Tendeloo G, Bals S, , 11 (2016). http://doi.org/10.1002/9783527808465.EMC2016.5519
Keywords: P1 Proceeding; Electron microscopy for materials research (EMAT); Vision lab
DOI: 10.1002/9783527808465.EMC2016.5519
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“Atom-counting in High Resolution Electron Microscopy: TEM or STEM –, that's the question”. Gonnissen J, De Backer A, den Dekker AJ, Sijbers J, Van Aert S, Ultramicroscopy 174, 112 (2016). http://doi.org/10.1016/j.ultramic.2016.10.011
Abstract: In this work, a recently developed quantitative approach based on the principles of detection theory is used in order to determine the possibilities and limitations of High Resolution Scanning Transmission Electron Microscopy (HR STEM) and HR TEM for atom-counting. So far, HR STEM has been shown to be an appropriate imaging mode to count the number of atoms in a projected atomic column. Recently, it has been demonstrated that HR TEM, when using negative spherical aberration imaging, is suitable for atom-counting as well. The capabilities of both imaging techniques are investigated and compared using the probability of error as a criterion. It is shown that for the same incoming electron dose, HR STEM outperforms HR TEM under common practice standards, i.e. when the decision is based on the probability function of the peak intensities in HR TEM and of the scattering cross-sections in HR STEM. If the atom-counting decision is based on the joint probability function of the image pixel values, the dependence of all image pixel intensities as a function of thickness should be known accurately. Under this assumption, the probability of error may decrease significantly for atom-counting in HR TEM and may, in theory, become lower as compared to HR STEM under the predicted optimal experimental settings. However, the commonly used standard for atom-counting in HR STEM leads to a high performance and has been shown to work in practice.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 2
DOI: 10.1016/j.ultramic.2016.10.011
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“StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images”. De Backer A, van den Bos KHW, Van den Broek W, Sijbers J, Van Aert S, Ultramicroscopy 171, 104 (2016). http://doi.org/10.1016/j.ultramic.2016.08.018
Abstract: An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 43
DOI: 10.1016/j.ultramic.2016.08.018
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“Detecting and locating light atoms from high-resolution STEM images: The quest for a single optimal design”. Gonnissen J, De Backer A, den Dekker AJ, Sijbers J, Van Aert S, Ultramicroscopy 170, 128 (2016). http://doi.org/10.1016/j.ultramic.2016.07.014
Abstract: In the present paper, the optimal detector design is investigated for both detecting and locating light atoms from high resolution scanning transmission electron microscopy (HR STEM) images. The principles of detection theory are used to quantify the probability of error for the detection of light atoms from HR STEM images. To determine the optimal experiment design for locating light atoms, use is made of the so-called Cramer-Rao Lower Bound (CRLB). It is investigated if a single optimal design can be found for both the detection and location problem of light atoms. Furthermore, the incoming electron dose is optimised for both research goals and it is shown that picometre range precision is feasible for the estimation of the atom positions when using an appropriate incoming electron dose under the optimal detector settings to detect light atoms.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 6
DOI: 10.1016/j.ultramic.2016.07.014
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“Quantitative 3D analysis of huge nanoparticle assemblies”. Zanaga D, Bleichrodt F, Altantzis T, Winckelmans N, Palenstijn WJ, Sijbers J, de Nijs B, van Huis MA, Sanchez-Iglesias A, Liz-Marzan LM, van Blaaderen A, Joost Batenburg K, Bals S, Van Tendeloo G, Nanoscale 8, 292 (2016). http://doi.org/10.1039/c5nr06962a
Abstract: Nanoparticle assemblies can be investigated in 3 dimensions using electron tomography. However, it is not straightforward to obtain quantitative information such as the number of particles or their relative position. This becomes particularly difficult when the number of particles increases. We propose a novel approach in which prior information on the shape of the individual particles is exploited. It improves the quality of the reconstruction of these complex assemblies significantly. Moreover, this quantitative Sparse Sphere Reconstruction approach yields directly the number of particles and their position as an output of the reconstruction technique, enabling a detailed 3D analysis of assemblies with as many as 10 000 particles. The approach can also be used to reconstruct objects based on a very limited number of projections, which opens up possibilities to investigate beam sensitive assemblies where previous reconstructions with the available electron tomography techniques failed.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 7.367
Times cited: 34
DOI: 10.1039/c5nr06962a
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“The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography”. van Aarle W, Palenstijn WJ, De Beenhouwer J, Altantzis T, Bals S, Batenburg KJ, Sijbers J, Ultramicroscopy 157, 35 (2015). http://doi.org/10.1016/j.ultramic.2015.05.002
Abstract: We present the ASTRA Toolbox as an open platform for 3D image reconstruction in tomography. Most of the software tools that are currently used in electron tomography offer limited flexibility with respect to the geometrical parameters of the acquisition model and the algorithms used for reconstruction. The ASTRA Toolbox provides an extensive set of fast and flexible building blocks that can be used to develop advanced reconstruction algorithms, effectively removing these limitations. We demonstrate this flexibility, the resulting reconstruction quality, and the computational efficiency of this toolbox by a series of experiments, based on experimental dual-axis tilt series.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 562
DOI: 10.1016/j.ultramic.2015.05.002
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“Measuring lattice strain in three dimensions through electron microscopy”. Goris B, de Beenhouwer J, de Backer A, Zanaga D, Batenburg KJ, Sánchez-Iglesias A, Liz-Marzán LM, Van Aert S, Bals S, Sijbers J, Van Tendeloo G, Nano letters 15, 6996 (2015). http://doi.org/10.1021/acs.nanolett.5b03008
Abstract: The three-dimensional (3D) atomic structure of nanomaterials, including strain, is crucial to understand their properties. Here, we investigate lattice strain in Au nanodecahedra using electron tomography. Although different electron tomography techniques enabled 3D characterizations of nanostructures at the atomic level, a reliable determination of lattice strain is not straightforward. We therefore propose a novel model-based approach from which atomic coordinates are measured. Our findings demonstrate the importance of investigating lattice strain in 3D.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 12.712
Times cited: 87
DOI: 10.1021/acs.nanolett.5b03008
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“Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials”. Van Eyndhoven G, Kurttepeli M, van Oers CJ, Cool P, Bals S, Batenburg KJ, Sijbers J, Ultramicroscopy 148, 10 (2015). http://doi.org/10.1016/j.ultramic.2014.08.008
Abstract: Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm POre REconstruction and Segmentation is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab; Laboratory of adsorption and catalysis (LADCA)
Impact Factor: 2.843
Times cited: 7
DOI: 10.1016/j.ultramic.2014.08.008
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“Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images”. Gonnissen J, de Backer A, den Dekker AJ, Martinez GT, Rosenauer A, Sijbers J, Van Aert S, Applied physics letters 105, 063116 (2014). http://doi.org/10.1063/1.4892884
Abstract: We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 3.411
Times cited: 12
DOI: 10.1063/1.4892884
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“A memory efficient method for fully three-dimensional object reconstruction with HAADF STEM”. Van den Broek W, Rosenauer A, Van Aert S, Sijbers J, van Dyck D, Ultramicroscopy 141, 22 (2014). http://doi.org/10.1016/j.ultramic.2014.03.008
Abstract: The conventional approach to object reconstruction through electron tomography is to reduce the three-dimensional problem to a series of independent two-dimensional slice-by-slice reconstructions. However, at atomic resolution the image of a single atom extends over many such slices and incorporating this image as prior knowledge in tomography or depth sectioning therefore requires a fully three-dimensional treatment. Unfortunately, the size of the three-dimensional projection operator scales highly unfavorably with object size and readily exceeds the available computer memory. In this paper, it is shown that for incoherent image formation the memory requirement can be reduced to the fundamental lower limit of the object size, both for tomography and depth sectioning. Furthermore, it is shown through multislice calculations that high angle annular dark field scanning transmission electron microscopy can be sufficiently incoherent for the reconstruction of single element nanocrystals, but that dynamical diffraction effects can cause classification problems if more than one element is present. (C) 2014 Elsevier B.V. All rights reserved.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 6
DOI: 10.1016/j.ultramic.2014.03.008
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“Estimation of unknown structure parameters from high-resolution (S)TEM images : what are the limits?”.den Dekker AJ, Gonnissen J, de Backer A, Sijbers J, Van Aert S, Ultramicroscopy 134, 34 (2013). http://doi.org/10.1016/j.ultramic.2013.05.017
Abstract: Statistical parameter estimation theory is proposed as a quantitative method to measure unknown structure parameters from electron microscopy images. Images are then purely considered as data planes from which structure parameters have to be determined as accurately and precisely as possible using a parametric statistical model of the observations. For this purpose, an efficient algorithm is proposed for the estimation of atomic column positions and intensities from high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images. Furthermore, the so-called CramérRao lower bound (CRLB) is reviewed to determine the limits to the precision with which continuous parameters such as atomic column positions and intensities can be estimated. Since this lower bound can only be derived for continuous parameters, alternative measures using the principles of detection theory are introduced for problems concerning the estimation of discrete parameters such as atomic numbers. An experimental case study is presented to show the practical use of these measures for the optimization of the experiment design if the purpose is to decide between the presence of specific atom types using STEM images.
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT); Vision lab
Impact Factor: 2.843
Times cited: 31
DOI: 10.1016/j.ultramic.2013.05.017
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“DART explained: how to carry out a discrete tomography reconstruction”. Batenburg KJ, Bals S, Sijbers J, Van Tendeloo G, , 295 (2008)
Keywords: P1 Proceeding; Electron microscopy for materials research (EMAT); Vision lab
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“An interactive curvature based rigid-body image registartion technique: an application of EFTEM”. Leemans A, Sijbers J, van den Broek W, Yang Z, (2004)
Keywords: P3 Proceeding; Vision lab; Electron microscopy for materials research (EMAT)
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“Reliable pore-size measurements based on a procedure specifically designed for electron tomography measurements of nanoporous samples”. Van Eyndhoven G, Batenburg KJ, van Oers C, Kurttepeli M, Bals S, Cool P, Sijbers J, (2014)
Keywords: P3 Proceeding; Electron microscopy for materials research (EMAT); Vision lab; Laboratory of adsorption and catalysis (LADCA)
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