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
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.
Current events
SECOND ANNUAL MEETING FOR THE DUTCH INVERSE PROBLEMS COMMUNITY
- 2022-11-10T09:30:00+01:00
- 2022-11-11T18:00:00+01:00
SECOND ANNUAL MEETING FOR THE DUTCH INVERSE PROBLEMS COMMUNITY
Start: 2022-11-10 09:30:00+01:00 End: 2022-11-11 18:00:00+01:00
The second annual meeting of the Dutch Inverse Problems Community will take place on 10-11 November 2022 in conference center de Werelt, Lunteren. A summary of last year’s event can be read here.
Registration
The registration is now open. Registration fees are expected to be around EUR 225 for 2-day attendance (including lunch, diner, and hotel), and EUR 50 for 1-day attendance for EUR 50 (including lunch). You will receive additional confirmation about the exact fees and payment details in september.
Preliminary program
Thursday November 10
Masterclasses on High Performance Computing and Inverse Problem Theory (preliminary abstracts are included below). The masterclasses will take in place in parallel and aim to give an in-depth overview and hands-on experience on the topic.
Friday November 11
Scientific talks, highlighting recent developments in Inverse Problems from a mathematical and practical point of view. The talks are by invitation, and selected to give a balanced perspective on theory and applications of inverse problems from both junior and senior researchers.
- Email: Tristan van Leeuwen
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iCal
Members
Associated Members
Publications
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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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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
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Out, F, Cortés-Ortuño, D, Fabian, K, van Leeuwen, T, & de Groot, L.V. (2022). A first-order statistical exploration of the mathematical limits of Micromagnetic Tomography. Geochemistry, Geophysics, Geosystems, 23(4), e2021GC010184.1–e2021GC010184.18. doi:10.1029/2021GC010184
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Schut, D.E. (2022). Trajectory with Overlapping Projections x-ray Computed Tomography (TOP-CT) dataset of 23 mandarins moving over a circular trajectory. doi:10.5281/zenodo.6351647
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Lucka, F, Pérez-Liva, M, Treeby, B.E, & Cox, B.T. (2022). High resolution 3D ultrasonic breast imaging by time-domain full waveform inversion. Inverse Problems, 38(2), 025008.1–025008.39. doi:10.1088/1361-6420/ac3b64
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Longo, E, Alj, D, Batenburg, K.J, de la Rochefoucauld, O, Herzog, C, Greving, I, … Zeitoun, P. (2022). Flexible plenoptic X-ray microscopy. Photonics, 9(2), 98.1–98.13. doi:10.3390/photonics9020098
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Tataris, A, & van Leeuwen, T. (2022). A regularised total least squares approach for 1D inverse scattering. Mathematics, 10(2), 216.1–216.24. doi:10.3390/math10020216
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Bührer, M, Xu, H, Hendriksen, A.A, Büchi, F.N, Eller, J, Stampanoni, M, & Marone, F. (2021). Deep learning based classification of dynamic processes in time-resolved X-ray tomographic microscopy. Nature Scientific Reports, 11. doi:10.1038/s41598-021-03546-8
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Sero, D, Garachon, I, Hermens, E, van Liere, R, & Batenburg, K.J. (2021). The study of three-dimensional fingerprint recognition in cultural heritage: Trends and challenges. ACM Journal on Computing and Cultural Heritage, 14(4). doi:10.1145/3461341
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