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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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“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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“Artifact Reduction Based on Sinogram Interpolation for the 3D Reconstruction of Nanoparticles Using Electron Tomography”. Sentosun K, Lobato I, Bladt E, Zhang Y, Palenstijn WJ, Batenburg KJ, Van Dyck D, Bals S, Particle and particle systems characterization 34, 1700287 (2017). http://doi.org/10.1002/ppsc.201700287
Abstract: Electron tomography is a well-known technique providing a 3D characterization of the morphology and chemical composition of nanoparticles. However, several reasons hamper the acquisition of tilt series with a large number of projection images, which deteriorate the quality of the 3D reconstruction. Here, an inpainting method that is based on sinogram interpolation is proposed, which enables one to reduce artifacts in the reconstruction related to a limited tilt series of projection images. The advantages of the approach will be demonstrated for the 3D characterization of nanoparticles using phantoms and several case studies.
Keywords: A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT); Vision lab
Times cited: 2
DOI: 10.1002/ppsc.201700287
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“Automatic correction of nonlinear damping effects in HAADF-STEM tomography for nanomaterials of discrete compositions”. Zhong Z, Aveyard R, Rieger B, Bals S, Palenstijn WJ, Batenburg KJ, Ultramicroscopy 184, 57 (2018). http://doi.org/10.1016/J.ULTRAMIC.2017.10.013
Abstract: <script type='text/javascript'>document.write(unpmarked('HAADF-STEM tomography is a common technique for characterizing the three-dimensional morphology of nanomaterials. In conventional tomographic reconstruction algorithms, the image intensity is assumed to be a linear projection of a physical property of the specimen. However, this assumption of linearity is not completely valid due to the nonlinear damping of signal intensities. The nonlinear damping effects increase w.r.t the specimen thickness and lead to so-called \u0022cupping artifacts\u0022, due to a mismatch with the linear model used in the reconstruction algorithm. Moreover, nonlinear damping effects can strongly limit the applicability of advanced reconstruction approaches such as Total Variation Minimization and discrete tomography. In this paper, we propose an algorithm for automatically correcting the nonlinear effects and the subsequent cupping artifacts. It is applicable to samples in which chemical compositions can be segmented based on image gray levels. The correction is realized by iteratively estimating the nonlinear relationship between projection intensity and sample thickness, based on which the projections are linearized. The correction and reconstruction algorithms are tested on simulated and experimental data. (C) 2017 Elsevier B.V. All rights reserved.'));
Keywords: A1 Journal article; Electron microscopy for materials research (EMAT)
Impact Factor: 2.843
Times cited: 8
DOI: 10.1016/J.ULTRAMIC.2017.10.013
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