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
Postdoc on the subject of Pattern Recognition and Analysis for Technical Art History
Centrum Wiskunde & Informatica (CWI) has a vacancy in the Computational Imaging research group for a talented Postdoc on the subject of Pattern Recognition and Analysis for Technical Art History
News
Centrum Wiskunde & Informatica launches world-class 3D lab
On Thursday 18 May 2017 demissionary state secretary Sander Dekker opened a new research facility that belongs to the top of the world league at Centrum Wiskunde & Informatica. With the new scanner of this lab, it will be made possible for the first time to look inside objects in 3D during the scanning process and to adjust or zoom in while scanning.
CWI develops new algebraic filter for reconstruction of X-Ray images
CWI PhD student Linda Plantagie of the Computational Imaging research group has introduced a new algebraic filter for the use of reconstructing X-Ray images. Linda Plantagie will defend her thesis 13 April at Leiden University.
The Netherlands’ smallest supercomputer is here
A team of Dutch scientists has built a supercomputer the size of four pizza boxes. The Little Green Machine II has the computing power of 10,000 PCs and will be used by researchers in oceanography, computer science, artificial intelligence, financial modeling and astronomy. CWI researchers Joost Batenburg and Kees Oosterlee, who were part of the development team, will use the machine for computational imaging and machine learning for time series respectively. The computer is based at Leiden University (the Netherlands) and developed with help from IBM.
ERCIM News 108 on Computational Imaging co-coordinated by Joost Batenburg
In January 2017, ERCIM News No. 108 was published: http://ercim-news.ercim.eu/en108. It features a special theme on Computational Imaging, coordinated by guest editors Joost Batenburg (CWI) and Tamas Sziranyi (MTA SZTAKI).
Members
Associated Members
Publications
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Pelt, D.M, Batenburg, K.J, & Sethian, J.A. (2018). Improving tomographic reconstruction from limited data using Mixed-Scale Dense convolutional neural networks. Journal of Imaging, 4(11), 128–128. doi:10.3390/jimaging4110128
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Tick, J, Pulkkinen, A, Lucka, F, Ellwood, R, Cox, B.T, Kaipio, J.P. (Jari), … Tarvainen, T. (2018). Three dimensional photoacoustic tomography in Bayesian framework. The Journal of the Acoustical Society of America, 144(4), 2061–2071. doi:10.1121/1.5057109
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der Sarkissian, H.H, Viganò, N.R, & Batenburg, K.J. (2018). A data consistent variational segmentation approach suitable for real-time tomography. Fundamenta Informaticae, 163(1), 1–20. doi:10.3233/FI-2018-1729
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Hauptmann, A, Arridge, S, Lucka, F, Muthurangu, V, & Steeden, J.A. (2018). Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning–proof of concept in congenital heart disease. Magnetic Resonance in Medicine. doi:10.1002/mrm.27480
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Buurlage, J.W, Bannink, T, & Bisseling, R.H. (2018). Bulk: A modern C++ interface for bulk-synchronous parallel programs. In Euro-Par 2018: Parallel Processing (pp. 519–532). doi:10.1007/978-3-319-96983-1_37
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Treeby, B, Lucka, F, Martin, E, & Cox, B.T. (2018). Equivalent-source acoustic holography for projecting measured ultrasound fields through complex media. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. doi:10.1109/TUFFC.2018.2861895
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van Liere, R, Batenburg, K.J, Kostenko, A, Wang, C-L, & Garachon, I. (2018). Imaging ancient Chinese ivory puzzle balls: deducing the make Process. In PROCEEDINGS of the sixth International workshop on Image Processing for Art Investigation (IP4AI) Gent, Belgium 21-22 June 2018 (pp. 48–50).
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Buurlage, J.W, Kohr, H, Palenstijn, W.J, & Batenburg, K.J. (2018). Real-time quasi-3D tomographic reconstruction. Measurement Science and Technology, 29(6). doi:10.1088/1361-6501/aab754
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Hauptmann, A, Lucka, F, Betcke, M, Huynh, N, Adler, J, Cox, B.T, … Arridge, S. (2018). Model based learning for accelerated, limited-view 3D photoacoustic tomography. IEEE Transactions on Medical Imaging. doi:10.1109/TMI.2018.2820382
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Boink, Y.E, Lagerwerf, M.J, Steenbergen, W, van Gils, S.A, Manohar, S, & Brune, C. (2018). A framework for directional and higher-order reconstruction in photoacoustic tomography. Physics in Medicine and Biology, 63(4). doi:10.1088/1361-6560/aaaa4a
Software
Current projects with external funding
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Machine learning for large 3D tomographic images
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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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PPS contract Planmeca
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Rapid 3D Printing through full-field volumetric photolithography
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Real-Time 3D Tomography
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The See-Through Museum
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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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Volumetric medical x-ray imaging at extremely low dose (VOXEL)
Related partners
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Centre National de la Recherche Scientifique (CNRS), Gif-sur-Yvette, France
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CNR Pisa
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COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
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IMAGINE OPTIC
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Meyn Food Processing Technology B.V.
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Naturalis
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Planmeca
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Rijksmuseum Amsterdam
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Universidad Politécnica de Madrid