@article {1857,
	title = {Advanced X-ray tomography: experiment, modeling, and algorithms},
	journal = {Measurement Science and Technology},
	volume = {29},
	year = {2018},
	pages = {080101},
	doi = {https://doi.org/10.1088/1361-6501/aacd25},
	author = {Kees Joost Batenburg and Francesco De Carlo and Lucia Mancini and Jan Sijbers}
}
@article {1792,
	title = {TomoBank: A Tomographic Data Repository for Computational X-ray Science},
	journal = {Measurement Science and Technology},
	volume = {29},
	year = {2018},
	pages = {1-10},
	doi = {https://doi.org/10.1088/1361-6501/aa9c19},
	author = {Francesco De Carlo and Doga Gursoy and Daniel Ching and Kees Joost Batenburg and Ludwig, Wolfgang and Lucia Mancini and Federica Marone Welford and Rajmund Mokso and Daan Pelt and Jan Sijbers and Mark Rivers}
}
@article {1715,
	title = {A distributed ASTRA Toolbox},
	journal = {Advanced Structural and Chemical Imaging},
	volume = {2},
	year = {2016},
	doi = {10.1186/s40679-016-0032-z},
	author = {Willem Jan Palenstijn and Jeroen B{\'e}dorf and Jan Sijbers and Kees Joost Batenburg}
}
@article {1600,
	title = {Easy implementation of advanced tomography algorithms using the ASTRA toolbox with Spot operators},
	journal = {Numerical Algorithms},
	volume = {71},
	number = {3},
	year = {2016},
	pages = {673-697},
	doi = {10.1007/s11075-015-0016-4},
	author = {Folkert Bleichrodt and Tristan van Leeuwen and Willem Jan Palenstijn and Wim Van Aarle and Jan Sijbers and Kees Joost Batenburg}
}
@article {1701,
	title = {Fast and Flexible X-ray Tomography Using the ASTRA Toolbox},
	journal = {Optics Express},
	volume = {24},
	number = {22},
	year = {2016},
	pages = {25129-25147},
	doi = {10.1364/OE.24.025129},
	author = {Wim Van Aarle and Willem Jan Palenstijn and Jeroen Cant and Eline Janssens and Folkert Bleichrodt and Andrei Dabravolski and Jan De Beenhouwer and Kees Joost Batenburg and Jan Sijbers}
}
@article {1664,
	title = {Integration of TomoPy and the ASTRA toolbox for advanced processing and reconstruction of tomographic synchrotron data},
	journal = {Journal of Synchrotron Radiation},
	volume = {23},
	year = {2016},
	pages = {842-849},
	doi = {10.1107/S1600577516005658},
	author = {Daan Pelt and Doga Gursoy and Willem Jan Palenstijn and Jan Sijbers and Francesco De Carlo and Kees Joost Batenburg}
}
@conference {1741,
	title = {Investigating lattice strain in Au nanodecahedrons},
	year = {2016},
	doi = {10.1002/9783527808465.EMC2016.5519},
	author = {Bart Goris and Jan De Beenhouwer and Annick De Backer and Daniele Zanaga and Kees Joost Batenburg and Ana S{\'a}nchez-Iglesias and Luis M Liz-Marzán and Sandra Van Aert and Jan Sijbers and Van Tendeloo, Gustaaf and Sara Bals}
}
@article {1703,
	title = {Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT},
	journal = {Medical Physics},
	volume = {43},
	year = {2016},
	pages = {6429-6438},
	doi = {10.1118/1.4967263},
	author = {Vincent Van Nieuwenhove and Van Eyndhoven, Geert and Kees Joost Batenburg and Nico Buls and Jaf Vandemeulebroucke and Jan De Beenhouwer and Jan Sijbers}
}
@article {1674,
	title = {Quantitative 3D analysis of huge nanoparticle assemblies.},
	journal = {Nanoscale},
	volume = {8},
	year = {2016},
	month = {2016 Jan 7},
	pages = {292-9},
	abstract = {Nanoparticle assemblies can be investigated in 3 dimensions using electron tomography. However, it is not straightforward to obtain quantitative information such as the number of particles or their relative position. This becomes particularly difficult when the number of particles increases. We propose a novel approach in which prior information on the shape of the individual particles is exploited. It improves the quality of the reconstruction of these complex assemblies significantly. Moreover, this quantitative Sparse Sphere Reconstruction approach yields directly the number of particles and their position as an output of the reconstruction technique, enabling a detailed 3D analysis of assemblies with as many as 10,000 particles. The approach can also be used to reconstruct objects based on a very limited number of projections, which opens up possibilities to investigate beam sensitive assemblies where previous reconstructions with the available electron tomography techniques failed.},
	issn = {2040-3372},
	doi = {10.1039/c5nr06962a},
	author = {Daniele Zanaga and Folkert Bleichrodt and Thomas Altantzis and Winckelmans, Naomi and Willem Jan Palenstijn and Jan Sijbers and de Nijs, Bart and Marijn A van Huis and Ana S{\'a}nchez-Iglesias and Luis M Liz-Marzán and van Blaaderen, Alfons and Kees Joost Batenburg and Sara Bals and Van Tendeloo, Gustaaf}
}
@conference {1589,
	title = {A 4D CT reconstruction algorithm for fast liquid flow imaging},
	year = {2015},
	abstract = {  The study of fluid flow through solid matter by computed tomography (CT) imaging has a broad range of applications, ranging from oil extraction to scientific research on fluid dynamics. Current techniques are often limited by a low temporal/spatial resolution. In this talk, a new iterative CT reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flowing through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. Firstly, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Secondly, the attenuation of a particular voxel in the dynamic region is modeled by a piecewise constant function over time (i.e., the voxel consists of fluid or air). Experiments on simulation data and on a real neutron tomography dataset demonstrate that the proposed approach can significantly increase the temporal resolution in comparison to conventional algorithms.},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Vincent Van Nieuwenhove and Lee, Peter D. and Katherine J Dobson and Jan Sijbers}
}
@article {1580,
	title = {The ASTRA Toolbox: a platform for advanced algorithm development in electron tomography},
	journal = {Ultramicroscopy},
	volume = {157},
	year = {2015},
	pages = {35{\textendash}47},
	doi = {10.1016/j.ultramic.2015.05.002},
	author = {Wim Van Aarle and Willem Jan Palenstijn and Jan De Beenhouwer and Thomas Altantzis and Sara Bals and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1542,
	title = {Filtered backprojection using algebraic filters; Application to biomedical micro-CT data},
	booktitle = {International Symposium on Biomedical Imaging (ISBI)},
	year = {2015},
	pages = {1596-1599},
	author = {Linda Plantagie and Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers}
}
@article {1606,
	title = {An iterative CT reconstruction algorithm for fast fluid flow imaging},
	journal = {IEEE Transactions on Image Processing},
	volume = {24},
	year = {2015},
	pages = {4446-4458},
	abstract = {The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique.

In this paper, a new iterative CT reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. Firstly, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Secondly, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary.

Quantitative and qualitative results on different simulation experiments and a real neutron tomography dataset show that, in comparison state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, temporal resolution can be substantially increased and thus fluid flow experiments with faster dynamics can be performed.},
	issn = {1057-7149},
	doi = {10.1109/TIP.2015.2466113},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Vincent Van Nieuwenhove and Lee, Peter D. and Katherine J Dobson and Jan Sijbers}
}
@conference {1588,
	title = {An iterative prior knowledge based reconstruction algorithm for increased temporal/spatial resolution in the CT imaging of fluid flow through solid matter},
	year = {2015},
	abstract = {The study of fluid flow through solid matter by computed tomography (CT) imaging has a broad range of applications, e.g., in oil production (the manner in which water displaces oil in rocks determines the fraction of oil that can be recovered) and in scientific research on fluid dynamics (validation of fluid flow models) [1-4]. In this work, a novel iterative computed tomography reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flowing through solid matter is introduced. The proposed algorithm exploits prior knowledge in a twofold manner. Firstly, a dynamic reconstruction is generated assuming the existence of stationary regions (the solid matter) and dynamic regions (the fluid flow) throughout the reconstruction domain. This assumption is enforced by sharing iterative updates in the stationary regions over different time frames. Secondly, the fact that a particular voxel in the dynamic region can typically be described by a piecewise constant (PWC) function over time (i.e., the voxel consists of fluid or air) is exploited by estimating a PWC function in a robust manner in all voxels belonging to the dynamic region at intermediate iterations. The proposed reconstruction algorithm was validated on simulation data and on a real neutron tomography dataset (PSI ICON experiment, courtesy of Manchester X-ray Imaging Facility). These experiments demonstrated that the new iterative technique is able to significantly increase the temporal resolution in comparison to more conventional algorithms such as the Simultaneous Iterative Reconstruction Technique (SIRT) or Filtered Backprojection (FBP) [5-6].

[1]	V. Cnudde and M. Boone: High-resolution x-ray computed tomography in geosciences: A review of the current technology and applications. Earth-Science Reviews, vol. 123, pp. 1 {\textendash} 17, 2013
[2]	S. Akin and A. Kovscek: Computed tomography in petroleum engineering research. Geological Society, London, Special Publications, vol. 215, no. 1, pp. 23{\textendash}38, 2003
[3]	O. P. Wennberg, L. Rennan, and R. Basquet: Computed tomography scan imaging of natural open fractures in a porous rock; geometry and fluid flow. Geophysical Prospecting, vol. 57, no. 2, pp. 239{\textendash}249, 2009
[4]	M. Kumar, T. J. Senden, A. P. Sheppard, J. P. Middleton, and M. A. Knackstedt: Visualizing and quantifying the residual phase distribution in core material. Petrophysics, vol. 51, no. 5, p. 323, 2010
[5]	J. Gregor and T. Benson: Computational analysis and improvement of SIRT. IEEE Trans. Med. Imag., vol. 27, no. 7, pp. 918{\textendash}24, 2008
[6]	L. Feldkamp, L. Davis, and J. Kress: Practical cone-beam algorithm. J. Opt. Soc. Am. A, vol. 1, no. 6, pp. 612{\textendash}619, 1984
},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Jan Sijbers}
}
@article {1611,
	title = {Measuring Lattice Strain in Three Dimensions through Electron Microscopy},
	journal = {Nano Letters},
	volume = {15},
	year = {2015},
	pages = {6996{\textendash}7001},
	doi = {10.1021/acs.nanolett.5b03008},
	author = {Bart Goris and Jan De Beenhouwer and Annick De Backer and Daniele Zanaga and Kees Joost Batenburg and Ana S{\'a}nchez-Iglesias and Luis M Liz-Marzán and Sandra Van Aert and Sara Bals and Jan Sijbers and Van Tendeloo, Gustaaf}
}
@mastersthesis {1631,
	title = {Model-based iterative reconstruction algorithms for computed tomography},
	volume = {PhD in Sciences},
	year = {2015},
	month = {12/2015},
	type = {PhD thesis},
	author = {Van Eyndhoven, Geert}
}
@article {1496,
	title = {Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials},
	journal = {Ultramicroscopy},
	volume = {148},
	year = {2015},
	pages = {10-19},
	abstract = {Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm ({\textquotedblleft}POre REconstruction and Segmentation{\textquotedblright}) is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials.},
	doi = {10.1016/j.ultramic.2014.08.008},
	author = {Van Eyndhoven, Geert and Mert Kurttepeli and C. J. {Van Oers} and Pegie Cool and Sara Bals and Kees Joost Batenburg and Jan Sijbers}
}
@article {1626,
	title = {Quantitative 3D analysis of huge nanoparticle assemblies},
	journal = {Nanoscale},
	volume = {8},
	year = {2015},
	pages = {292-299},
	doi = {10.1039/C5NR06962A},
	author = {Daniele Zanaga and Folkert Bleichrodt and Thomas Altantzis and Winckelmans, Naomi and Willem Jan Palenstijn and Jan Sijbers and B. van Nijs and Marijn A van Huis and van Blaaderen, Alfons and Ana S{\'a}nchez-Iglesias and Luis M Liz-Marzán and Kees Joost Batenburg and Sara Bals and Van Tendeloo, Gustaaf}
}
@inproceedings {1590,
	title = {Region based 4D tomographic image reconstruction: application to cardiac X-ray CT},
	booktitle = {IEEE International Conference on Image Processing},
	year = {2015},
	pages = {113 - 117},
	abstract = {X-ray computed tomography (CT) is a powerful tool for noninvasive cardiac imaging. However, radiation dose is a major issue. In this paper, we propose an iterative reconstruction method that reduces the radiation dose without compromising image quality. This is achieved by exploiting prior knowledge in two ways: the reconstructed object is assumed to consist of both stationary and dynamic regions over time and the dynamic region is assumed to have sparse structures after a proper sparsifying space-time transform. Experiments on simulation data and a real micro CT cardiac mouse dataset show that, with comparable image quality, the radiation dose can be substantially reduced compared to conventional acquisition/reconstruction protocols.},
	doi = {10.1109/ICIP.2015.7350770},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers}
}
@mastersthesis {1632,
	title = {Towards In Loco X-ray Computed Tomography},
	year = {2015},
	month = {12/2015},
	type = {PhD thesis},
	author = {Andrei Dabravolski}
}
@inproceedings {1499,
	title = {3D imaging of semiconductor components by discrete laminography},
	booktitle = {Stress induced phenomena and reliability in 3D microelectronics: AIP Conference Proceedings},
	volume = {1601},
	year = {2014},
	pages = {168-179},
	doi = { http://dx.doi.org/10.1063/1.4881350},
	author = {Kees Joost Batenburg and Willem Jan Palenstijn and Jan Sijbers}
}
@conference {1607,
	title = {Accurate reconstruction of porous samples in CT},
	year = {2014},
	month = {2014},
	abstract = {Quantification of a sample{\textquoteright}s porosity from computed tomography (CT) images is important in many industrial applications. However, in non-standard acquisition set-ups (e.g., limited data or angular range), the reconstruction and subsequent segmentation of pore-space is challenging. In this paper, a novel algorithm exploiting prior knowledge about the porous structure of the scanned is proposed, improving the quality of both reconstruction and segmentation.},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers}
}
@article {1424,
	title = {Adaptive zooming in X-ray computed tomography},
	journal = {Journal of X-Ray Science and Technology},
	volume = {22},
	number = {1},
	year = {2014},
	pages = {77-89},
	keywords = {Acquisition geometry, adaptive zooming, computed tomography, prior information},
	doi = {10.3233/XST-130410},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1471,
	title = {Aligning Projection Images from Binary Volumes},
	journal = {Fundamenta Informaticae},
	volume = {135},
	year = {2014},
	pages = {1-22},
	doi = {10.3233/FI-2014-1090},
	author = {Folkert Bleichrodt and Jan De Beenhouwer and Jan Sijbers and Kees Joost Batenburg}
}
@article {1418,
	title = {Dynamic Angle Selection in X-ray Computed Tomography},
	journal = {Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms},
	volume = {324},
	year = {2014},
	pages = {17-24},
	keywords = {Angle selection, computed tomography, dynamic imaging, information gain},
	doi = {10.1016/j.nimb.2013.08.077},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1678,
	title = {Filter for Tomographic Reconstructions},
	number = {WO2013011031A1},
	year = {2014},
	chapter = {WO2013011031A1},
	author = {Kees Joost Batenburg and Jan Sijbers and Linda Plantagie}
}
@conference {1449,
	title = {A local enhancement based tomographic reconstruction technique for radiation exposure reduction in cerebral perfusion computed tomography},
	year = {2014},
	doi = {10.1594/ecr2014/C-0282},
	url = {http://posterng.netkey.at/esr/online_viewing/index.php?module=view_postercoverpage\&task=viewcoverpage\&start=0\&ls=authorlist\&pi=121333\&perid=248156\&num=1\&count=1\&cid=515},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers}
}
@article {1502,
	title = {A Multiresolution Approach to Discrete Tomography Using DART},
	journal = {PLoS ONE},
	volume = {9},
	year = {2014},
	doi = {10.1371/journal.pone.0106090},
	url = {http://www.plosone.org/article/info\%3Adoi\%2F10.1371\%2Fjournal.pone.0106090},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@conference {1457,
	title = {A multiresolution approach to the Discrete Algebraic Reconstruction Technique (DART)},
	year = {2014},
	month = {07/2014},
	keywords = {computed tomography, DART, Discrete tomography, prior information},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1480,
	title = {The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography},
	journal = {Computer Vision and Image Understanding},
	volume = {126},
	year = {2014},
	pages = {28-37},
	doi = {10.1016/j.cviu.2014.05.007},
	author = {Roelandts, Tom and Kees Joost Batenburg and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1436,
	title = {Region-based iterative reconstruction of structurally changing objects in CT},
	journal = {IEEE Transactions on Image Processing},
	volume = {23},
	year = {2014},
	pages = {909-919},
	chapter = {909-919},
	doi = {10.1109/TIP.2013.2297024},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers}
}
@conference {1454,
	title = {Reliable Pore-size Measurements Based on a Procedure Specifically Designed for Electron Tomography Measurements of Nanoporous Samples},
	year = {2014},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Cynthia Van Oers and Mert Kurttepeli and Sara Bals and Pegie Cool and Jan Sijbers}
}
@article {1437,
	title = {Super-resolution for computed tomography based on discrete tomography},
	journal = {IEEE Transactions on Image Processing},
	volume = {23},
	year = {2014},
	pages = {1181 - 1193},
	doi = {10.1109/TIP.2013.2297025},
	author = {Wim Van Aarle and Kees Joost Batenburg and Gert Van Gompel and Elke Van de Casteele and Jan Sijbers}
}
@inproceedings {1386,
	title = {Adaptive Zooming in X-ray Computed Tomography},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {5-8},
	address = {Ghent, Belgium},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1343,
	title = {Advanced reconstruction algorithms for electron tomography: from comparison to combination},
	journal = {Ultramicroscopy},
	volume = {127},
	year = {2013},
	pages = {40{\textendash}47},
	author = {Bart Goris and Roelandts, Tom and Kees Joost Batenburg and Hamed Heidari Mezerji and Sara Bals}
}
@article {1392,
	title = {Advances in X-ray diffraction contrast tomography: flexibility in the setup geometry and application to multiphase materials},
	journal = {Journal of Applied Crystallography},
	volume = {46},
	year = {2013},
	month = {04/2013},
	pages = {297 - 311},
	issn = {0021-8898},
	doi = {10.1107/S0021889813002604},
	author = {Reischig, P{\'e}ter and King, Andrew and Nervo, Laura and Vigan{\'o}, Nicola and Guilhem, Yoann and Willem Jan Palenstijn and Kees Joost Batenburg and Preuss, Michael and Ludwig, Wolfgang}
}
@inproceedings {1399,
	title = {An Algebraic Reconstruction Technique for the Study of Local Structural Changes during CT},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {137-141},
	abstract = {If an object undergoes structural changes during a CT-scan, artefacts are introduced in the reconstruction. Current methods that compensate for these changes assume a continuous deformation model, which is insufficient to capture the complexity of structural changes. In this paper, an iterative method is proposed that incorporates prior knowledge about the changing region in the reconstruction algorithm, which results in significantly more accurate reconstructions.},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1650,
	title = {An Alignment Method for Fan Beam Tomography},
	booktitle = {International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {103-107},
	author = {Folkert Bleichrodt and Jan De Beenhouwer and Jan Sijbers and Kees Joost Batenburg}
}
@inproceedings {1403,
	title = {The ASTRA Tomography Toolbox},
	booktitle = {13th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2013},
	volume = {4},
	year = {2013},
	pages = {1139-1145},
	isbn = {978-84-616-2723-3},
	author = {Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers}
}
@article {1407,
	title = {DART: a new approach for super-resolution reconstruction of license plates},
	journal = {Journal of Electronic Imaging},
	volume = {22},
	year = {2013},
	chapter = {041111},
	doi = {10.1117/1.JEI.22.4.041111},
	url = {http://electronicimaging.spiedigitallibrary.org/article.aspx?articleid=1733763},
	author = {Karim Zarei Zefreh and Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers}
}
@conference {1405,
	title = {Discrete Tomography in MRI: a proof of concept},
	volume = {21},
	year = {2013},
	pages = {2662},
	author = {Segers, Hilde and Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers}
}
@article {1404,
	title = {Discrete Tomography in MRI: a Simulation Study},
	journal = {Fundamenta Informaticae},
	volume = {125},
	year = {2013},
	pages = {223-237},
	doi = {10.3233/FI-2013-861},
	author = {Segers, Hilde and Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers}
}
@article {1370,
	title = {Dynamic angle selection in binary tomography},
	journal = {Computer Vision and Image Understanding},
	volume = {117},
	year = {2013},
	pages = {306{\textendash}318},
	doi = {http://dx.doi.org/10.1016/j.cviu.2012.07.005},
	author = {Kees Joost Batenburg and Willem Jan Palenstijn and Peter Balazs and Jan Sijbers}
}
@inproceedings {1387,
	title = {Dynamic Angle Selection in X-ray Computed Tomography},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {27-30},
	address = {Ghent, Belgium},
	author = {Andrei Dabravolski and Kees Joost Batenburg and Jan Sijbers}
}
@article {1677,
	title = {Dynamic tomography angle selection},
	number = {PCT/EP2012/071421},
	year = {2013},
	chapter = {WO2013064472 A1},
	issn = {US2014307934A1},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1423,
	title = {Fast Tomographic Reconstruction from Highly Limited Data Using Artificial Neural Networks},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	year = {2013},
	pages = {109-112},
	author = {Daan Pelt and Jan Sijbers and Kees Joost Batenburg}
}
@mastersthesis {1428,
	title = {Local Prior Knowledge in Tomography},
	volume = {PhD in Sciences: Physics},
	year = {2013},
	month = {11/2013},
	type = {PhD thesis},
	author = {Roelandts, Tom}
}
@inproceedings {1400,
	title = {Localizing DART using the Reconstructed Residual Error},
	booktitle = {1st International Conference on Tomography of Materials and Structures (ICTMS)},
	volume = {Book of Abstracts: Talks},
	year = {2013},
	pages = {113-116},
	address = {Ghent, Belgium},
	author = {Roelandts, Tom and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1422,
	title = {Practical Error Bounds for Binary Tomography},
	booktitle = {1st International Conference on Tomography of Materials and Structures},
	year = {2013},
	pages = {97-100},
	author = {Wagner Fortes and Jan Sijbers and Kees Joost Batenburg}
}
@conference {1398,
	title = {Region-Based SIRT algorithm for the reconstrcution of phase bins in dynamic micro-CT},
	year = {2013},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Jan Sijbers}
}
@article {1419,
	title = {Super-Resolution of License Plate Images using Algebraic Reconstruction Technique},
	journal = {Journal of Image and Graphics},
	volume = {1},
	year = {2013},
	month = {2013},
	pages = {94 - 98},
	publisher = {Engineering and Technology Publishing (ETP)},
	address = {USA},
	abstract = {In this paper, an iterative super-resolution reconstruction method is introduced for license plate recognition. A high-resolution image of the license plate is reconstructed by fusing the information derived from a set of subpixel shifted low-resolution images. The reconstruction problem is formulated as a system of linear equations that is solved by using the simultaneous algebraic reconstruction technique (SIRT). Simulation experiments show that SIRT can reconstruct a HR image with superior quality compared to conventional super-resolution reconstruction methods.},
	keywords = {algebraic reconstruction technique, license plate, reconstruction, SIRT, super-resolution},
	issn = {23013699},
	doi = {10.12720/joig.1.2.94-98},
	url = {http://www.joig.org/index.php?m=content\&c=index\&a=show\&catid=31\&id=41},
	author = {Karim Zarei Zefreh and Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers}
}
@article {1320,
	title = {Accurate segmentation of dense nanoparticles by partially discrete electron tomography},
	journal = {Ultramicroscopy},
	volume = {114},
	year = {2012},
	pages = {96-105},
	author = {Roelandts, Tom and Kees Joost Batenburg and E. Biermans and C. Kubel and Sara Bals and Jan Sijbers}
}
@article {1350,
	title = {Automatic parameter estimation for the Discrete Algebraic Reconstruction Technique (DART)},
	journal = {IEEE Transactions on Image Processing},
	volume = {21},
	year = {2012},
	pages = {4608-4621},
	doi = {10.1109/TIP.2012.2206042},
	author = {Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1367,
	title = {Combined Motion Estimation and Reconstruction in Tomography},
	booktitle = {12th European Conference on Computer Vision},
	volume = {7583},
	year = {2012},
	pages = {12-21},
	publisher = {Lecture Notes on Computer Science},
	organization = {Lecture Notes on Computer Science},
	address = {Firenze, Italy},
	abstract = {If objects or patients move during a CT scan, reconstructions suffer from severe motion artifacts. Time dependent computed tomography (4DCT) tries to minimize these artifacts by estimating motion and/or reconstruction simultaneously. Most current methods assume a known deformation or a reconstruction without artifacts at a certain time point. This work explores the possibilities of estimating the motion model and reconstruction simultaneously. It does so by modifying the simultaneous iterative reconstruction technique (SIRT) to incorporate motion (trans-SIRT) and uses this method in an optimization routine that computes motion and reconstruction at the same time. Results show that the optimization routine is able to estimate motion accurately, assuming only the type of parametrization for the motion model. Our approach can potentially be extended to more complex motion models.},
	author = {Van Eyndhoven, Geert and Jan Sijbers and Kees Joost Batenburg}
}
@conference {1714,
	title = {A framework for markerless alignment with full 3D flexibility},
	year = {2012},
	author = {Jan De Beenhouwer and Willem Jan Palenstijn and Folkert Bleichrodt and Kees Joost Batenburg and Jan Sijbers}
}
@conference {1430,
	title = {Segmentation of MR Images by k-space distance minimization: a proof of concept},
	volume = {25},
	year = {2012},
	pages = {63-64},
	author = {Segers, Hilde and Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1360,
	title = {Spatial Variations in Reconstruction Methods for CT},
	booktitle = {The Second International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting)},
	year = {2012},
	month = {07/2012},
	pages = {170-173},
	author = {Linda Plantagie and Willem Jan Palenstijn and Jan Sijbers and Kees Joost Batenburg}
}
@mastersthesis {1327,
	title = {Tomographic segmentation and discrete tomography for quantitative analysis of transmission tomography data},
	year = {2012},
	pages = {190},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp, Belgium},
	author = {Wim Van Aarle}
}
@inproceedings {1358,
	title = {Visualizing the Segmentation Error of a Tomogram using the Residual Projection Error},
	booktitle = {The Second International Conference on Image Formation in X-Ray Computed Tomography (CT Meeting)},
	year = {2012},
	pages = {293-296},
	address = {Salt Lake City, UT, USA},
	author = {Roelandts, Tom and Kees Joost Batenburg and Jan Sijbers}
}
@article {zmaiR.jbatenbumverhoyepscheundjsijbers2011,
	title = {Bias field reduction by localized Lloyd-Max quantization},
	journal = {Magnetic Resonance Imaging},
	volume = {29},
	year = {2011},
	pages = {536-545},
	doi = {http://dx.doi.org/10.1016/j.mri.2010.10.015},
	author = {Zhenhua Mai and Rudolf Hanel and Kees Joost Batenburg and Marleen Verhoye and Paul Scheunders and Jan Sijbers}
}
@inproceedings {1298,
	title = {Bone segmentation using discrete tomography},
	booktitle = {Micro-CT User Meeting},
	year = {2011},
	pages = {178-183},
	isbn = {9789081678100},
	issn = {2033-8031},
	author = {Elke Van de Casteele and Kees Joost Batenburg and Salmon, Phil and Jan Sijbers}
}
@article {jbatenbujsijbers2011,
	title = {DART: A practical reconstruction algorithm for discrete tomography},
	journal = {IEEE Transactions on Image Processing},
	volume = {20},
	number = {9},
	year = {2011},
	pages = {2542-2553},
	doi = {10.1109/TIP.2011.2131661},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1429,
	title = {Efficient parameter estimation for discrete tomography using adaptive modeling},
	booktitle = {11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2011},
	month = {07/2011},
	author = {Wim Van Aarle and K. Crombecq and I. Couckuyt and Kees Joost Batenburg and Jan Sijbers}
}
@article {gvgompelSlambrouckDefrisejbatenbuMeyjsijbersNuyts2011,
	title = {Iterative correction of beam hardening artifacts in CT},
	journal = {Medical Physics},
	volume = {38},
	number = {1},
	year = {2011},
	month = {July},
	pages = {36-49},
	doi = {http://dx.doi.org/10.1118/1.3577758},
	author = {Gert Van Gompel and Van Slambrouck, Katrien and M. Defrise and Kees Joost Batenburg and Johan De Mey and Jan Sijbers and Johan Nuyts}
}
@article {wvaarlejbatenbujsijbers2011,
	title = {Optimal threshold selection for segmentation of dense homogeneous objects in tomographic reconstructions},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {30},
	number = {4},
	year = {2011},
	pages = {980-989},
	doi = {http://dx.doi.org/doi:10.1109/TMI.2010.2104328},
	author = {Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {1194,
	title = {PDART: A Partially Discrete Algorithm for the Reconstruction of Dense Particles},
	booktitle = {11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D)},
	year = {2011},
	pages = {448-451},
	address = {Potsdam, Germany},
	author = {Roelandts, Tom and Kees Joost Batenburg and Jan Sijbers}
}
@article {1249,
	title = {Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)},
	journal = {Journal of structural biology},
	volume = {176},
	year = {2011},
	month = {2011 Nov},
	pages = {250-253},
	abstract = {Iterative reconstruction algorithms are becoming increasingly important in electron tomography of biological samples. These algorithms, however, impose major computational demands. Parallelization must be employed to maintain acceptable running times. Graphics Processing Units (GPUs) have been demonstrated to be highly cost-effective for carrying out these computations with a high degree of parallelism. In a recent paper by Xu et al. (2010), a GPU implementation strategy was presented that obtains a speedup of an order of magnitude over a previously proposed GPU-based electron tomography implementation. In this technical note, we demonstrate that by making alternative design decisions in the GPU implementation, an additional speedup can be obtained, again of an order of magnitude. By carefully considering memory access locality when dividing the workload among blocks of threads, the GPU{\textquoteright}s cache is used more efficiently, making more effective use of the available memory bandwidth.},
	issn = {1095-8657},
	doi = {10.1016/j.jsb.2011.07.017},
	author = {Willem Jan Palenstijn and Kees Joost Batenburg and Jan Sijbers}
}
@article {jbatenbuwvaarlejsijbers2011,
	title = {A Semi-Automatic Algorithm for Grey Level Estimation in Tomography},
	journal = {Pattern Recognition Letters},
	volume = {32},
	number = {9},
	year = {2011},
	month = {July},
	pages = {1395-1405},
	author = {Kees Joost Batenburg and Wim Van Aarle and Jan Sijbers}
}
@conference {1204,
	title = {Ultra-High Resolution Electron Tomography for Materials Science: A Roadmap},
	year = {2011},
	address = {Nashville, TN, United States},
	doi = {http://dx.doi.org/10.1017/S143192761100554X},
	author = {Kees Joost Batenburg and Sara Bals and Sandra Van Aert and Roelandts, Tom and Jan Sijbers}
}
@inproceedings {wvaarlegvgompeljbatenbuevdcastejsijbers2010,
	title = {A 3-dimensional discrete tomography approach for superresolution micro-CT images: application to foams},
	booktitle = {The first international conference on image formation in X-ray computed tomography},
	year = {2010},
	month = {June},
	pages = {45-48},
	author = {Wim Van Aarle and Gert Van Gompel and Kees Joost Batenburg and Elke Van de Casteele and Jan Sijbers},
	editor = {Fr{\'e}d{\'e}ric Noo}
}
@article {jbatenbujsijbersH.F.E.2010,
	title = {DART: A Robust Algorithm for Fast Reconstruction of 3D Grain Maps},
	journal = {Journal of Applied Crystallography},
	volume = {43},
	year = {2010},
	pages = {1464-1473},
	doi = {https://doi.org/10.1107/S0021889810034114},
	author = {Kees Joost Batenburg and Jan Sijbers and H.F. Poulsen and E. Knudsen}
}
@inproceedings {gvgompeljbatenbuevdcastewvaarlejsijbers2010,
	title = {A discrete tomography approach for superresolution micro-CT images},
	booktitle = {IEEE International Symposium on Biomedical Imaging},
	year = {2010},
	month = {April},
	pages = {816-819},
	address = {Rotterdam},
	author = {Gert Van Gompel and Kees Joost Batenburg and Elke Van de Casteele and Wim Van Aarle and Jan Sijbers}
}
@inproceedings {1322,
	title = {Iterative correction of beam hardening artifacts in CT},
	booktitle = {The First International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2010},
	month = {06/2010},
	author = {Van Slambrouck, Katrien and Gert Van Gompel and M. Defrise and Kees Joost Batenburg and Jan Sijbers and Johan Nuyts}
}
@conference {1203,
	title = {Partially Discrete Tomography for the Reconstruction of Dense Particles},
	year = {2010},
	pages = {I7.19},
	address = {Rio de Janeiro, Brazil},
	author = {Roelandts, Tom and Kees Joost Batenburg and E. Biermans and Sara Bals and Jan Sijbers}
}
@inproceedings {1568,
	title = {Projection and backprojection in tomography: design choices and considerations},
	booktitle = {Workshop on Applications of Discrete Geometry and Mathematical Morphology},
	year = {2010},
	pages = {106-110},
	author = {Kees Joost Batenburg and Willem Jan Palenstijn and Jan Sijbers}
}
@article {jbatenbuBalsjsijbersKubelMidgleyHernandezKaiserEncinaCoronadoTendeloo2009,
	title = {3D imaging of nanomaterials by discrete tomography},
	journal = {Ultramicroscopy},
	volume = {109},
	year = {2009},
	pages = {730-740},
	doi = {10.1016/j.ultramic.2009.01.009},
	author = {Kees Joost Batenburg and Sara Bals and Jan Sijbers and C. Kubel and P.A. Midgley and J.C. Hernandez and U. Kaiser and E.R. Encina and E.A. Coronado and Van Tendeloo, Gustaaf}
}
@article {jbatenbujsijbers2009,
	title = {Adaptive thresholding of tomograms by projection distance minimization},
	journal = {Pattern Recognition},
	volume = {42},
	number = {10},
	year = {2009},
	month = {April},
	pages = {2297-2305},
	doi = {10.1016/j.patcog.2008.11.027},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {svdmaarjbatenbujsijbers2009,
	title = {Experiences with Cell-BE and GPU for tomography},
	booktitle = {Embedded COmputer Systems: Architectures, Modeling, and Simulation - 9th International Workshop, SAMOS 2009 - Proceedings},
	year = {2009},
	month = {July},
	pages = {298-307},
	publisher = {Springer-Verlag Berlin Heidelberg},
	organization = {Springer-Verlag Berlin Heidelberg},
	author = {S. van der Maar and Kees Joost Batenburg and Jan Sijbers},
	editor = {Koen Bertels and Stephan Wong}
}
@article {jbatenbujsijbers2009,
	title = {Generic iterative subset algorithms for discrete tomography},
	journal = {Discrete Applied Mathematics},
	volume = {157},
	number = {3},
	year = {2009},
	pages = {438-451},
	doi = {https://doi.org/10.1016/j.dam.2008.05.033},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {jbatenbuwvaarlejsijbers2009,
	title = {Grey Level Estimation for Discrete Tomography},
	booktitle = {Discrete Geometry for Computer Imaging},
	series = {Lecture Notes in Computer Science},
	volume = {5810},
	year = {2009},
	month = {September},
	pages = {517-529},
	publisher = {Springer},
	organization = {Springer},
	doi = {https://doi.org/10.1007/978-3-642-04397-0_44},
	author = {Kees Joost Batenburg and Wim Van Aarle and Jan Sijbers},
	editor = {Srecko Brlek}
}
@article {jbatenbujsijbers2009,
	title = {Optimal Threshold Selection for Tomogram Segmentation by Projection Distance Minimization},
	journal = {IEEE Transactions on Medical Imaging},
	volume = {28},
	number = {5},
	year = {2009},
	month = {June},
	pages = {676-686},
	doi = {10.1109/TMI.2008.2010437},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
@article {gvgompelDefrisejbatenbu2009,
	title = {Reconstruction of a uniform star object from interior x-ray data: uniqueness, stability and algorithm},
	journal = {Inverse Problems},
	volume = {25},
	number = {65010},
	year = {2009},
	month = {June},
	doi = {10.1088/0266-5611/25/6/065010},
	author = {Gert Van Gompel and M. Defrise and Kees Joost Batenburg}
}
@mastersthesis {1270,
	title = {Towards accurate image reconstruction from truncated X-ray CT projections},
	year = {2009},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp},
	author = {Gert Van Gompel}
}
@inproceedings {svdmaarjbatenbujsijbers2008,
	title = {Algebraic tomographic reconstruction on the GPU},
	booktitle = {Li{\`e}ge Image Days 2008: Medical Imaging},
	year = {2008},
	month = {March},
	author = {S. van der Maar and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {jbatenbujsijbers2008,
	title = {Automatic local thresholding of tomographic reconstructions based on the projection data},
	booktitle = {SPIE Medical Imaging},
	volume = {6913},
	year = {2008},
	month = {February},
	pages = {69132},
	address = {San Diego, CA, USA},
	author = {Kees Joost Batenburg and Jan Sijbers},
	editor = {Jiang Hsieh, Ehsan Samei}
}
@conference {1493,
	title = {Computed tomography on all scales using the ASTRA toolbox},
	year = {2008},
	author = {Wim Van Aarle and S. van der Maar and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {Haneljbatenbujsijbers2008,
	title = {Fast bias field estimation by localized Lloyd-Max quantization},
	booktitle = {SPIE Medical Imaging},
	year = {2008},
	month = {February},
	address = {San Diego, CA, USA},
	author = {Rudolf Hanel and Kees Joost Batenburg and Jan Sijbers}
}
@conference {1382,
	title = {FASTRA: Fast Tomographic Reconstructions Using an Eight GPU Desktop Super Computer},
	year = {2008},
	address = {San Jose, California, USA},
	author = {S. van der Maar and Kees Joost Batenburg and Toon Huysmans and Jan Sijbers}
}
@conference {gvgompeljbatenbuDefrisejsijbers2008,
	title = {An iterative post-reconstruction method for beam hardening reduction without prior information},
	year = {2008},
	month = {March},
	author = {Gert Van Gompel and Kees Joost Batenburg and M. Defrise and Jan Sijbers}
}
@inproceedings {gvgompelDefrisejbatenbu2008,
	title = {Reconstruction of a uniform star object from interior X-ray data},
	booktitle = {Nuclear Science Symposium Conference Record, NSS08, IEEE},
	number = {2},
	year = {2008},
	month = {October},
	pages = {4115-4119},
	address = {Dresden, Germany},
	author = {Gert Van Gompel and M. Defrise and Kees Joost Batenburg}
}
@inproceedings {rpinhoBatenburgjsijbers2008,
	title = {Seeing Through the Window: Pre-fetching Strategies for Out-of-core Image Processing Algorithms},
	booktitle = {Proceedings of SPIE Medical Imaging},
	volume = {6919},
	year = {2008},
	month = {February},
	publisher = {SPIE},
	organization = {SPIE},
	address = {San Diego, CA, USA},
	doi = {doi:10.1117/12.769423},
	author = {R{\^o}mulo Pinho and Kees Joost Batenburg and Jan Sijbers}
}
@inproceedings {wvaarlejbatenbujsijbers2008,
	title = {Threshold Selection for Segmentation of Dense Objects in Tomograms},
	booktitle = {International Symposium on Visual Computing},
	series = {Lecture Notes on Computer Science},
	volume = {5358},
	year = {2008},
	month = {December},
	pages = {700-709},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Berlin Heidelberg},
	author = {Wim Van Aarle and Kees Joost Batenburg and Jan Sijbers},
	editor = {G. Bebis}
}
@inproceedings {Batenburgjsijbers2007,
	title = {Automatic multiple threshold scheme for segmentation of tomograms},
	booktitle = {Proceedings of SPIE Medical Imaging: Physics of Medical Imaging},
	year = {2007},
	month = {February},
	address = {San Diego, CA, USA},
	author = {Kees Joost Batenburg and Jan Sijbers},
	editor = {Michael J. Flynn, Jiang Hsieh}
}
@inproceedings {jbatenbujsijbers2007,
	title = {DART: a fast heuristic algebraic reconstruction algorithm for discrete tomography},
	booktitle = {Proceedings of the IEEE International Conference on Image Processing (ICIP)},
	year = {2007},
	month = {September},
	address = {San Antonio, Texas, USA},
	doi = {10.1109/ICIP.2007.4379972},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
@article {BalsjbatenbuVerbeeckjsijbersTendeloo2007,
	title = {Quantitative three-dimensional reconstruction of catalyst particles for bamboo-like carbon nanotubes},
	journal = {Nano Letters},
	volume = {7},
	number = {12},
	year = {2007},
	pages = {3669-3674},
	author = {Sara Bals and Kees Joost Batenburg and Jo Verbeeck and Jan Sijbers and Van Tendeloo, Gustaaf}
}
@inproceedings {Batenburgjsijbersevdcaste2006,
	title = {Automatic multiple threshold scheme for segmentation of tomograms},
	booktitle = {Proceedings of the Biomedical Engineering IEEE/EMBS Benelux Symposium},
	volume = {2},
	year = {2006},
	month = {December},
	pages = {143-146},
	address = {Brussels, Belgium},
	author = {Kees Joost Batenburg and Jan Sijbers and Elke Van de Casteele}
}
@inproceedings {Batenburgjsijbers2006,
	title = {Discrete tomography from micro-CT data: application to the mouse trabecular bone structure},
	booktitle = {Proceedings of SPIE Medical Imaging: Physics of Medical Imaging},
	volume = {6142},
	year = {2006},
	month = {February},
	pages = {1325-1335},
	address = {San Diego, CA, USA},
	author = {Kees Joost Batenburg and Jan Sijbers},
	editor = {Michael J. Flynn, Jiang Hsieh}
}
@inproceedings {Batenburgjsijbers2006,
	title = {Trabecular bone reconstruction from micro-CT data using discrete tomography},
	booktitle = {Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium)},
	year = {2006},
	month = {March},
	pages = {65-69},
	address = {Antwerp, Belgium},
	author = {Kees Joost Batenburg and Jan Sijbers}
}
