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
Innovation fund North Holland supports CWI startup Photosynthetic B.V.
Photosynthetic B.V., a new CWI startup, has received a convertible loan of €300.000 from Innovation Fund North Holland. Photosynthetic is a deep-tech startup working on a hardware solution for the microfabrication industry.
Can CT Scans Be Used to Quickly and Accurately Diagnose COVID-19?
CWI’s Computational Imaging group joins research collaboration focusing on improving the accuracy of CT scan diagnosis
Making the invisible visible
CT machines are becoming the standard tool for looking inside objects of all kinds in research and industry. The FleX-ray Lab at CWI is making this type of imaging more accessible to math and computer science researchers. It's also drawing interest from the art, history, and the social sciences community.
Making the invisible visible
CT machines are becoming the standard tool for looking inside objects of all kinds in research and industry. The FleX-ray Lab at CWI is making this type of imaging more accessible to math and computer science researchers. It's also drawing interest from the art, history, and the social sciences community.
Members
- Vladyslav Andriiashen
- Joost Batenburg
- Francien Bossema
- Sophia Coban
- 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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Ganguly, P.S, Lucka, F, Hupkes, H.J, & Batenburg, K.J. (2020). Atomic Super-Resolution Tomography. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence. doi:10.1007/978-3-030-51002-2_4
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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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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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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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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
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Colman, K.L, de Boer, H.H, Dobbe, J.G.G, Liberton, N.P.T.J, Stull, K.E, van Eijnatten, M.A.J.M, … van der Merwe, A.E. (2019). Virtual forensic anthropology: The accuracy of osteometric analysis of 3D bone models derived from clinical computed tomography (CT) scans. Forensic Science International, 304. doi:10.1016/j.forsciint.2019.109963
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Sero, D, Zaidi, A, Li, J, White, J.D, González Zarzar, T.B.G, Marazita, M.L, … Claes, P. (2019). Facial recognition from DNA using face-to-DNA classifiers. Nature Communications, 10(1). doi:10.1038/s41467-019-10617-y
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Hendriksen, A.A, Pelt, D.M, Palenstijn, W.J, Coban, S.B, & Batenburg, K.J. (2019). On-the-fly machine learning for improving image resolution in tomography. Applied Sciences, 9(12). doi:10.3390/app9122445
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Bossema, F.G, Burger, J.P, Bratton, L, Challenger, A, Adams, R.C, Sumner, P, … Smeets, I. (2019). Expert quotes and exaggeration in health news: A retrospective quantitative content analysis. Wellcome Open Research. doi:10.12688/wellcomeopenres.15147.2
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