Description
Leader of the group Computational Imaging: Joost Batenburg.
Our research group is developing the next generation of 3D imaging – enabling scientists to look further into objects of all kinds. Based on mathematics, algorithms and numerical solution techniques, our approach is interdisciplinary, combining aspects of mathematics, computer science and physics. We pride ourselves on the versatility of our solutions, and our algorithms can be applied to a wide range of imaging in science, medicine and industry. In Computational Imaging, it’s our goal to constantly push the boundaries of research. By combining advanced image acquisition, parameter estimation, and discrete tomography algorithms for example, we are able to develop workflows for 3D electron microscopy at atomic resolution.
Vacancies
PhD Student on the subject of CT imaging for Technical Art History: Algorithms and Techniques
Many objects in cultural heritage collections have a rich 3D internal structure. While the visible outer surface has been crafted with a focus on aesthetics, many of the secrets about the process of crafting the object are hidden beneath the surface, invisible to the naked eye. X-Ray CT is a powerful tool for creating detailed 3D images of the interior of such objects. However, its application to the study of cultural heritage collections is not straightforward, as the objects cover many length scales and have widely varying compositions.
PhD Student on the subject of novel reconstruction algorithms for dynamic tomography
While obtaining high quality images of static objects is feasible with many tomography modalities nowadays, imaging fast dynamic processes with both high spatial and temporal resolution remains very challenging but is of high interest in various clinical and scientific applications. Often, a high temporal resolution is achieved by a sub-sampled data acquisition (compressed sensing) and images reconstructed from the noisy, incomplete data by conventional algorithms are heavily impaired by artifacts and noise. Novel reconstruction approaches that incorporate mathematical models of the image dynamics demonstrated great potential to improve upon this in proof-of-concept studies but their formulation and implementation for high resolution 3D applications with complex dynamics pose severe mathematical and computational challenges.
PhD Student on the subject of Ultra-Fast 3D Reconstruction
Centrum Wiskunde & Informatica (CWI) and the Mathematical Institute of Leiden University seek a dedicated candidate for a PhD position in the interdisciplinary field of Mathematical Analysis, Algorithms and Computation for Tomography. As a PhD student, you will be part-time embedded in the Computational Imaging group at CWI, and part-time in the Analysis and Dynamical Systems group of the Mathematical Institute of Leiden University. As a team, we develop cutting-edge techniques for advanced tomographic reconstruction, combining expertise from Mathematics (Inverse Problems and Dynamical Systems), Computer Science (Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Our goal is to develop novel computational methods for 3D and 4D imaging.
News
CWI leads European network of imaging specialists
Centrum Wiskunde & Informatica (CWI) will lead the research network EXTREMA, which was officially launched yesterday with a kick-off meeting in Brussels. EXTREMA aims to create an interdisciplinary research community consisting of both X-ray specialists and mathematicians. Together they will work on the next generation of imaging techniques to advance both science and industrial R&D.
Solar cells imaged at the nanoscale in 3D
Researchers of Centrum Wiskunde & Informatica (CWI) in Amsterdam succeeded in imaging the three-dimensional structure of solar cells with unprecedented accuracy. The results of this joint research with colleagues from the University of California in Davis and the Pacific Northwest National Laboratory are published today in the journal Advanced Functional Materials.
Joost Batenburg professor Discrete Mathematics and Tomography at Leiden University
As of October 1, 2012, Joost Batenburg of Centrum Wiskunde & Informatica (CWI) has been appointed Professor of Discrete Mathematics and Tomography at the Mathematical Institute of Leiden University.
Members
Associated Members
Publications
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Hauptmann, A, Lucka, F, Betcke, M, Huynh, N, Adler, J, Cox, B, … Arridge, S. (2018). Model based learning for accelerated, limited-view 3D photoacoustic tomography. IEEE Transactions on Medical Imaging. doi:10.1109/TMI.2018.2820382
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Boink, Y.E, Lagerwerf, M.J, Steenbergen, W, van Gils, S.A, Manohar, S, & Brune, C. (2018). A framework for directional and higher-order reconstruction in photoacoustic tomography. Physics in Medicine and Biology, 63(4). doi:10.1088/1361-6560/aaaa4a
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De Carlo, F, Gürsoy, D, Ching, D.J, Batenburg, K.J, Ludwig, W, Mancini, L, … Rivers, M. (2018). TomoBank: A tomographic data repository for computational x-ray science. Measurement Science and Technology, 29(3). doi:10.1088/1361-6501/aa9c19
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der Sarkissian, H.H. (2018, January 11). Tomographic imaging in CWI: Algorithms and applications.
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Zhong, Z, Aveyard, R, Rieger, B, Bals, S, Palenstijn, W.J, & Batenburg, K.J. (2018). Automatic correction of nonlinear damping effects in HAADF–STEM tomography for nanomaterials of discrete compositions. Ultramicroscopy, 184, 57–65. doi:10.1016/j.ultramic.2017.10.013
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Kazantsev, D, Bleichrodt, F, van Leeuwen, T, Withers, P.J, Batenburg, K.J, & Lee, P.D. (2017). A novel tomographic reconstruction method based on the robust Student's t function for suppressing data outliers. IEEE Transactions on Computational Imaging, 3(4), 682–693. doi:10.1109/TCI.2017.2694607
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Joost Batenburg ontvangt Nederlandse prijs voor ICT-onderzoek 2018 - Nationale Onderwijsgids - 04-12-2017. (2017). Joost Batenburg ontvangt Nederlandse prijs voor ICT-onderzoek 2018 - Nationale Onderwijsgids - 04-12-2017.
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Kus, M, Altantzis, T, Vercauteren, S, Caretti, I, Leenaerts, O, Batenburg, K.J, … Cool, P. (2017). Mechanistic insight into the photocatalytic working of fluorinated anatase {001} nanosheets. Journal of Physical Chemistry C, 121(47), 26275–26286. doi:10.1021/acs.jpcc.7b05586
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Jørgensen, J.S, Coban, S.B, Lionheart, W.R.B, McDonald, S.A, & Withers, P.J. (2017). SparseBeads data: Benchmarking sparsity-regularized computed tomography. Measurement Science and Technology, 28. doi:10.1088/1361-6501/aa8c29
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Yousra, Y. B, Lucka, F, Salmon, J, & Gramfort, A. (2017). A hierarchical Bayesian perspective on majorization-minimization for non-convex sparse regression: Application to M/EEG source imaging. arXiv.org e-Print archive.
Software
Current projects with external funding
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Mathematics and Algorithms for 3D Imaging of Dynamic Processes
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Non-destructive 3D spectral imaging: applications in the poultry industry
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Real-Time 3D Tomography
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The See-Through Museum
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Automated multi-modal tomography for sub-22nm IC nodes (AMTIC)
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MUltiscale, Multimodal and Multidimensional imaging for EngineeRING (MUMMERING)
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Volumetric medical x-ray imaging at extremely low dose (VOXEL)
Related partners
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Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France
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CNR Pisa
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COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
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IMAGINE OPTIC
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Meyn Food Processing Technology B.V.
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Universidad Politécnica de Madrid
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FEI
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IMEC
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Technische Universiteit Delft