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
Vici grant for Joost Batenburg
Researcher Joost Batenburg of CWI has been awarded a Vici grant from the Netherlands Organisation for Scientific Research (NWO) for his proposal 'Real-Time 3D Tomography'. With the 1.5 million euro grant, Batenburg can develop his own research line in the next five years.
CWI reduces perturbations in tomography
Researcher Folkert Bleichrodt of CWI has developed new methods to improve the applicability of tomography. These methods reduce unwanted perturbations. This allows for applying tomography on a very small scale or based on a small number of measurements.
CWI on Belgian TV
CWI could be seen on the national Belgian TV, in the programme 'Iedereen beroemd' - 'Everybody Famous'. The item was broadcasted on Tuesday 3 February 2015 on channel Eén at 19.40h - and again after the late news. Broadcaster VRT visited CWI on 22 January.
Quality guarantee for tomographic images developed
CWI researcher Wagner Fortes has developed new methods to determine the quality of tomographic images. Tomography is an imaging technique used in for instance medical CT scanners and electron microscopes that uses penetrating beams to record a series of two-dimensional images from a range of angles.
Members
Associated Members
Publications
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Berkeley Lab 'minimalist machine learning' algorithms analyze images from very little data - Spacedaily.com - 28-02-18. (2018). Berkeley Lab 'minimalist machine learning' algorithms analyze images from very little data - Spacedaily.com - 28-02-18.
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Viganò, N.R, & Solé, V.A. (2018). Physically corrected forward operators for induced emission tomography: A simulation study. Measurement Science and Technology, 29(3). doi:10.1088/1361-6501/aa9d54
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van Leeuwen, T, Maretzke, S.C, & Batenburg, K.J. (2018). Automatic alignment for three-dimensional tomographic reconstruction. Inverse Problems, 34(2). doi:10.1088/1361-6420/aaa0f8
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Batenburg wint prijs voor algoritmes - Computable - 07-12-2017. (2017). Batenburg wint prijs voor algoritmes - Computable - 07-12-2017.
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Prijs voor hoogleraar Batenburg - Leidsch Dagblad - 06-12-2017. (2017). Prijs voor hoogleraar Batenburg - Leidsch Dagblad - 06-12-2017.
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ICT-prijs naar geavanceerde tomografie-algoritmes - Bits&Chips - 05-12-2017. (2017). ICT-prijs naar geavanceerde tomografie-algoritmes - Bits&Chips - 05-12-2017.
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Pelt, D.M, & Parkinson, D.Y. (2017). Ring artifact reduction in synchrotron X-ray tomography through helical acquisition. Measurement Science and Technology, 29. doi:10.1088/1361-6501/aa9dd9
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Kostenko, A. (2017, November). See-Through Museum Project: computational methods in the service of cultural heritage.
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Sentosun, K, Lobato, I, Bladt, E, Zhang, Y, Palenstijn, W.J, Batenburg, K.J, … Bals, S. (2017). Artifact reduction based on sinogram interpolation for the 3D reconstruction of nanoparticles using electron tomography. Particle & Particle Systems Characterization, 34(12). doi:10.1002/ppsc.201700287
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Lucka, F. (2017, October 20). Sparse Bayesian Inference & Uncertainty Quantification for Inverse Imaging Problems.
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