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.
Vacancies
No vacancies currently.
News
NWO Team Science Award for CWI together with research partners UvA and Rijksmuseum
‘Hugo de Groot’s bookchest Team’ consisting of researchers from CWI, Universiteit van Amsterdam (UvA), Rijksmuseum and Universiteit Leiden (UL).
Scanning volcanic rocks in our FleX-Ray lab
The FleX-ray CT-scanner located at the CWI, is a flexible system that can scan a large range of different objects. Even volcanic rocks!
Second release ASTRA toolbox
The new version of ASTRA, co-developed at CWI, offers improvements in compatibility and interoperability with other toolboxes.
CWI podcast: How the FleX-ray scanner reveals art secrets
The science podcast "How CWI's FleX-ray scanner reveals art secrets" is now online. CWI PhD candidate Francien Bossema (CI) and Rijksmuseum professor Erma Hermens talk to science journalist Bennie Mols about our special scanner.
Members
Associated Members
Publications
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Hendriksen, A.A, Schut, D, Palenstijn, W.J, Viganò, N.R, Kim, J, Pelt, D.M, … Batenburg, K.J. (2021). Tomosipo: fast, flexible, and convenient 3D tomography for complex scanning geometries in Python. doi:10.1364/OE.439909
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Ganguly, P.S, Pelt, D.M, Gürsoy, D, De Carlo, F, & Batenburg, K.J. (2021). Improving reproducibility in synchrotron tomography using implementation-adapted filters. In Journal of Synchrotron Radiation (Vol. 28, pp. 1583–1597). doi:10.1107/S1600577521007153
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Domínguez-Delmás, M, Bossema, F.G, Dorscheid, J, Coban, S.B, Hall-Aquitania, M, Batenburg, K.J, & Hermens, E. (2021). X-ray computed tomography for non-invasive dendrochronology reveals a concealed double panelling on a painting from Rubens’ studio. PLoS ONE, 16(8). doi:10.1371/journal.pone.0255792
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Pan, B, Arridge, S, Lucka, F, Cox, B.T, Huynh, N, Beard, P, … Betcke, M. (2021). Photoacoustic reconstruction using sparsity in Curvelet frame: Image versus data domain. IEEE Transactions on Computational Imaging, 7, 879–893. doi:10.1109/TCI.2021.3103606
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Minnema, J, van Eijnatten, M.A.J.M, Der Sarkissian, H.H, Doyle, S, Koivisto, J, Wolff, J, … Batenburg, K.J. (2021). Efficient high cone-angle artifact reduction in circular cone-beam CT using deep learning with geometry-aware dimension reduction. Physics in Medicine and Biology, 66(13). doi:10.1088/1361-6560/ac09a1
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Andriiashen, V, & Kozhevnikov, D. (2021). Development of the projection-based material decomposition algorithm for Multienergy CT. IEEE Transactions on Radiation and Plasma Medical Sciences, 5(4), 517–527. doi:10.1109/TRPMS.2020.3022479
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Andriiashen, V, van Liere, R, van Leeuwen, T, & Batenburg, K.J. (2021). Unsupervised foreign object detection based on dual-energy absorptiometry in the food industry. Journal of Imaging, 7(7). doi:10.3390/jimaging7070104
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van Leeuwen, T, & Aravkin, A.Y. (2021). Variable projection for non-smooth problems. SIAM Journal on Scientific Computing, S249–S268. doi:10.1137/20M1348650
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Bossema, F.G. (2021). Three line trajectory X-ray tomography datasets of a small wooden block. doi:10.5281/zenodo.4541555
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Bossema, F.G. (2021). A CT dataset of a small wooden block. doi:10.5281/zenodo.4533882
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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Cervical Disease Maps
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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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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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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