Willem Jan Palenstijn

- Full Name
- W.J. Palenstijn
- Function(s)
- Scientific Software Developer
- W.J.Palenstijn@cwi.nl
- Telephone
- +31 20 592 4030
- Room
- L020b
- Department(s)
- Computational Imaging
Biography
After obtaining a PhD in number theory from Universiteit Leiden, I am now working on high performance computing for tomography, in particular using GPUs to accelerate reconstruction algorithms. I am the lead developer of the open-source ASTRA Tomography Toolbox.
Publications
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Bossema, F.G, Domínguez-Delmás, M, Palenstijn, W.J, Kostenko, A, Dorscheid, J, Coban, S.B, … Batenburg, K.J. (2021). A novel method for dendrochronology of large historical wooden objects using line trajectory X-ray tomography. Nature Scientific Reports, 11(1). doi:10.1038/s41598-021-90135-4
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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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Coban, S.B, Lucka, F, Palenstijn, W.J, Van Loo, D, & Batenburg, K.J. (2020). Explorative imaging and its implementation at the FleX-ray laboratory. Journal of Imaging, 6(4). doi:10.3390/jimaging6040018
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Lagerwerf, M.J, Palenstijn, W.J, Kohr, H, & Batenburg, K.J. (2020). Automated FDK-filter selection for cone-beam CT in research environments. IEEE Transactions on Computational Imaging, 6, 739–748. doi:10.1109/TCI.2020.2971136
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Kostenko, A, Palenstijn, W.J, Coban, S.B, Hendriksen, A.A, van Liere, R, & Batenburg, K.J. (2020). Prototyping X-ray tomographic reconstruction pipelines with FleXbox. SoftwareX, 11. doi:10.1016/j.softx.2019.100364
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van Werkhoven, B, Palenstijn, W.J, & Sclocco, A. (2020). Lessons learned in a decade of research software engineering gpu applications. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence. doi:10.1007/978-3-030-50436-6_29
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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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Bender, H, Richard, O, Kundu, P, Favia, P, Zhong, Z, Palenstijn, W.J, … Schoenmakers, R. (2019). Combined STEM-EDS tomography of nanowire structures. Semiconductor Science and Technology, 34(11). doi:10.1088/1361-6641/ab4840
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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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Coban, S.B, Hendriksen, A.A, Pelt, D.M, Palenstijn, W.J, & Batenburg, K.J. (2018). Oatmeal Data: Experimental cone-beam tomographic data for techniques to improve image resolution. doi:10.5281/zenodo.2657644
Current projects with external funding
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Cambridge RG99590 AIO cancer imaging optimisation (Cancer Imaging Optimisation)