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
No vacancies currently.
News
Faster computation of high-quality 3D images
PhD student Daniël Pelt of CWI has developed new algorithms for computer tomography (CT) for fast computation of high-quality three-dimensional images. This increases the practical use of this technology in areas such as material sciences and biomedical research.
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.
Members
- Vladyslav Andriiashen
- Joost Batenburg
- Francien Bossema
- Sophia Coban
- Viviane Desgrange
- Shannon Doyle
- Poulami Ganguly
- Adriaan Graas
- Allard Hendriksen
- Ajinkya Kadu
- Maximilian Kiss
- Tristan van Leeuwen
- Robert van Liere
- Felix Lucka
- Willem Jan Palenstijn
- Georgios Pilikos
- Richard Schoonhoven
- Dirk Schut
- Dzemila Sero
- Mathé Zeegers
Associated Members
Publications
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Kadu, A.A, Mansour, H, & Boufounos, P.T. (2020). High-contrast reflection tomography with total-variation constraints. IEEE Transactions on Computational Imaging, 6, 1523–1536. doi:10.1109/TCI.2020.3038171
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Schoonhoven, R.A, Buurlage, J, Pelt, D.M, & Batenburg, K.J. (2020). Real-time segmentation for tomographic imaging. In IEEE 30th International Workshop on Machine Learning for Signal Processing (pp. 1–6). doi:10.1109/MLSP49062.2020.9231642
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Pilikos, G, Horchens, L, Batenburg, K.J, van Leeuwen, T, & Lucka, F. (2020). Deep data compression for approximate ultrasonic image formation. In 2020 IEEE International Ultrasonics Symposium. doi:10.1109/IUS46767.2020.9251753
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Ganguly, P.S, Lucka, F, Hupkes, H.J, & Batenburg, K.J. (2020). Atomic super-resolution tomography. In Lecture Notes in Computer Science. doi:10.1007/978-3-030-51002-2_4
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Sero, D, Hermens, E, Garachon, I, Scholten, F, van Liere, R, & Batenburg, K.J. (2020). The study of three-dimensional fingerprints in cultural heritage: Current trends and challenges.
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Vanrompay, H, Buurlage, J, Pelt, D.M, Kumar, V, Zhuo, X, Liz-Marzán, L.M, … Batenburg, K.J. (2020). Real-Time Reconstruction of Arbitrary Slices for Quantitative and In Situ 3D Characterization of Nanoparticles. Particle and Particle Systems Characterization, 37(7). doi:10.1002/ppsc.202000073
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Bals, S, Albrecht, W, Vanrompay, H, Bladt, E, Skorikov, A, De Oliveira, T.M, … van Aert, S. (2020). Novel approaches for electron tomography to investigate the structure and stability of nanomaterials in 3 dimensions. Microscopy and Microanalysis. doi:10.1017/S1431927620017031
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Hendriksen, A.A, Pelt, D.M, & Batenburg, K.J. (2020). Noise2Inverse: Self-Supervised Deep Convolutional Denoising for Tomography. IEEE Transactions on Computational Imaging, 6, 1320–1335. doi:10.1109/TCI.2020.3019647
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Buurlage, J, Marone, F, Pelt, D.M, Palenstijn, W.J, Stampanoni, M, Batenburg, K.J, & Schlepütz, C.M. (2019). Real-time reconstruction and visualisation towards dynamic feedback control during time-resolved tomography experiments at TOMCAT. Nature Scientific Reports, 9(1). doi:10.1038/s41598-019-54647-4
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Der Sarkissian, H.H, Lucka, F, van Eijnatten, M.A.J.M, Colacicco, G, Coban, S.B, & Batenburg, K.J. (2019). A cone-beam X-ray computed tomography data collection designed for machine learning. Scientific Data, 6(1). doi:10.1038/s41597-019-0235-y
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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Cervical Disease Maps
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CT for Art: from Images to Patterns (IMPACT4Art)
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MUltiscale, Multimodal and Multidimensional imaging for EngineeRING (MUMMERING)
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Translation-Driven Development of Deep Learning for Simultaneous Tomographic Image Reconstruction and Segmentation (None)
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Deep learning and compressed sensing for ultrasonic nondestructive testin (PPS Applus RTD)
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Universal Three-dimensiOnal Passport for process Individualization in Agriculture (UTOPIA)
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Enabling X-ray CT based Industry 4.0 process chains by training Next Generation research experts (xCTing)
Related partners
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Fraunhofer Gesellschaft
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Naturalis
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Rijksmuseum Amsterdam
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Universiteit Wageningen
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University of Cambridge
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GREEFA
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Katholieke Universiteit Leuven
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Rheinisch-Westfaelische Technische Hochschule Aachen
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Universiteit Utrecht