Description
Leader of the group Computational Imaging: Tristan van Leeuwen.
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.
More information on the Computational Imaging group at CWI and its FleX-ray Lab.
Vacancies
No vacancies currently.
News
EU grant for CWI and UCL to improve X-Ray scanning at lower doses with AI
CWI and UCL received an EU ATTRACT grant to deploy and develop AI techniques to improve X-ray CT scanning in such a way that much lower doses of radiation can be used to obtain high-resolution images. The project started in July 2019.
CWI part of NWA CORTEX consortium
The National Science Agenda has awarded a 5 million euro grant to CORTEX – the Center for Optimal, Real-Time Machine Studies of the Explosive Universe. Self-learning machines will hunt for explosions in the universe and speed up innovations in industry and society.
Veni grant for Daniël Pelt
The Netherlands Organisation for Scientific Research (NWO) has awarded a Veni grant to CWI researcher Daniël Pelt.
Computational Imaging group and Rijksmuseum project awarded with NICAS funding
The Netherlands Institute for Conservation, Art and Science (NICAS) has announced which proposals have been awarded in the call "An Integrated Approach to the Scientific Study and Conservation of Art", organised by NWO.
Current events
PhD Defence Poulami Ganguly (Computational Imaging)
- 2022-12-08T12:30:00+01:00
- 2022-12-08T13:30:00+01:00
PhD Defence Poulami Ganguly (Computational Imaging)
Start: 2022-12-08 12:30:00+01:00 End: 2022-12-08 13:30:00+01:00
Everyone is welcome to attend the public defence of Poulami Ganguly of her thesis entitled 'Sparsity-Based Algorithms for Inverse Problems'.
- Email: Poulami Ganguly
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iCal
Members
Associated Members
Publications
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Ganguly, P.S. (2022, December 8). Sparsity-based algorithms for inverse problems.
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Dorscheid, J, Bossema, F.G, van Duin, P, Coban, S.B, van Liere, R, Batenburg, K.J, & Di Stefano, G.P. (2022). Looking under the skin: multi-scale CT scanning of a peculiarly constructed cornett in the Rijksmuseum. Heritage Science, 10(1), 161.1–161.10. doi:10.1186/s40494-022-00800-8
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Schlossmacher, I, Lucka, F, Peters, A, Bruchmann, M, & Straube, T. (2022). Effects of awareness and task relevance on neurocomputational models of mismatch negativity generation. NeuroImage, 262, 119530.1–119530.10. doi:10.1016/j.neuroimage.2022.119530
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Djurabekova, N, Goldberg, A, Hawkes, D, Long, G, Lucka, F, & Betcke, M. (2022). 2D-3D motion registration of rigid objects within a soft tissue structure. In Proceedings of SPIE - The International Society for Optical Engineering. doi:10.1117/12.2647250
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Schoonhoven, R.A, van Werkhoven, B.J.C, & Batenburg, K.J. (2022). Benchmarking optimization algorithms for auto-tuning GPU kernels. IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2022.3210654
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Minnema, J, Ernst, A, van Eijnatten, M.A.J.M, Pauwels, R, Forouzanfar, T, Batenburg, K.J, & Wolff, J. (2022). A review on the application of deep learning for CT reconstruction, bone segmentation and surgical planning in oral and maxillofacial surgery. Dentomaxillofacial Radiology, 51(7). doi:10.1259/dmfr.20210437
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de Jong, J.H.E, Paulssen, H, van Leeuwen, T, & Trampert, J. (2022). Sensitivity kernels for receiver function misfits in a full waveform inversion workflow. Geophysical Journal International, 230(2), 1065–1079. doi:10.1093/gji/ggac098
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Ganguly, P.S, Lucka, F, Kohr, H, Franken, E, Hupkes, H.J, & Batenburg, K.J. (2022). SparseAlign: A grid-free algorithm for automatic marker localization and deformation estimation in cryo-electron tomography. IEEE Transactions on Computational Imaging, 8, 651–665. doi:10.1109/TCI.2022.3194719
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Schut, D.E, Batenburg, K.J, van Liere, R, & van Leeuwen, T. (2022). TOP-CT: Trajectory with Overlapping Projections X-ray Computed Tomography. IEEE Transactions on Computational Imaging, 8, 598–608. doi:10.1109/TCI.2022.3192125
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Rizzuti, G, Sbrizzi, A, & van Leeuwen, T. (2022). Joint retrospective motion correction and reconstruction for brain MRI with a reference contrast. IEEE Transactions on Computational Imaging, 8, 490–504. doi:10.1109/TCI.2022.3183383
Software
ASTRA Toolbox: Commercial-class software for tomography imaging
The ASTRA Toolbox is a MATLAB and Python platform providing scalable, high-performance GPU primitives for 2D and 3D tomography, including building blocks for advanced reconstruction algorithms.
RECAST3D: a real-time visualization platform for tomographic imaging
RECAST3D provides real-time tomographic reconstruction and visualization of arbitrarily oriented 2D slices in a 3D volume.
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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Cambridge RG99590 AIO cancer imaging optimisation (Cancer Imaging Optimisation)
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the Center for Optimal, Real-Time Machine Studies of the Explosive Universe (CORTEX)
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CT for Art: from Images to Patterns (IMPACT4Art)
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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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Team Science Award
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Universal Three-dimensiOnal Passport for process Individualization in Agriculture (UTOPIA)
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Mathematics and Algorithms for 3D Imaging of Dynamic Processes / OIO positie Graas (Wiskundeclusters)
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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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ABN AMRO Bank
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Fraunhofer Gesellschaft
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IBM
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Katholieke Universiteit Nijmegen
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Naturalis
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Netherlands eScience Center
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NIKHEF
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Rijksmuseum Amsterdam
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Universiteit Wageningen
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University of Cambridge
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Nederland Instituut voor Radio Astronomie
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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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SURFsara B.V.
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Universiteit Utrecht
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Universiteit van Amsterdam