@mastersthesis {2438,
	title = {Advancement of Defect Detection and Quantifying Measurement Uncertainty in X-Ray CT Inspection},
	volume = {PhD in Sciences: Physics},
	year = {2026},
	type = {PhD thesis},
	author = {Miroslav Yosifov}
}
@mastersthesis {2433,
	title = {Advances in Monte Carlo simulations for the design of X-ray phase contrast imaging systems},
	volume = {PhD in Science: Physics},
	year = {2026},
	type = {PhD thesis},
	author = {Jonathan Sanctorum}
}
@inproceedings {2442,
	title = {Cycloidal Acquisition for Inline Edge Illumination X-ray Phase Contrast Computed Tomography: A Simulation Study},
	booktitle = {15th Conference on Industrial Computed Tomography (iCT)},
	volume = {31},
	year = {2026},
	month = {February},
	address = {Linz, Austria},
	keywords = {computed tomography, edge illumination, inline acquisition, X-ray phase contrast imaging},
	doi = {10.58286/32604},
	url = {https://doi.org/10.58286/32604},
	author = {Verstraete, J. and Francken, N. and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2437,
	title = {Edge illumination phase contrast imaging  with continuous motion},
	volume = {PhD in Sciences: Physics},
	year = {2026},
	month = {February, 2026},
	type = {PhD thesis},
	author = {Ben Huyge}
}
@article {2423,
	title = {Framework for optimal design of a multi-source rectangular X-ray cargo scanning system},
	journal = {Radiation Physics and Chemistry},
	volume = {239},
	year = {2026},
	pages = {113332},
	doi = {https://doi.org/10.1016/j.radphyschem.2025.113332 },
	author = {Caroline Bossuyt and Arnold Jan den Dekker and Domenico Iuso and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2447,
	title = {GEO-ASTRA: a toolbox for non-conventional XCT scanning and reconstruction},
	booktitle = { 15th Conference on Industrial Computed Tomography (iCT), 10 - 13 February 2026, Linz, Austria (iCT 2026), e-Journal of Nondestructive Testing},
	volume = {31 (3)},
	year = {2026},
	doi = {https://doi.org/10.58286/32567},
	author = {Joaquim G. Sanctorum and Bjorn De Samber and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2443,
	title = {Inline Edge Illumination Computed Tomography: A Simulation Study},
	booktitle = {2026 IEEE 23rd Mediterranean Electrotechnical Conference (MELECON)},
	year = {2026},
	address = {Cairo, Egypt},
	keywords = {edge illumination, Industry 4.0, Inline inspection, Non-destructive testing, X-ray phase contrast computed tomography},
	doi = {https://doi.org/10.1109/MELECON64486.2026.11418832},
	author = {Verstraete, J. and Francken, N. and Jan Sijbers and Jan De Beenhouwer}
}
@article {2432,
	title = {Investigating the Influence of Individual Physical Effects on Dimensional Measurement Deviations Using XCT Simulations},
	journal = {Measurement,},
	volume = {263},
	year = {2026},
	doi = {https://doi.org/10.1016/j.measurement.2025.120168},
	author = {Miroslav Yosifov and Thiago Linhares Fernandes and Filippo Zanini and Simone Carmignato and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@inproceedings {2448,
	title = {Towards X-ray-based inspection of corrosion in maritime infrastructure},
	booktitle = {15th Conference on Industrial Computed Tomography (iCT), 10 - 13 February 2026, Linz, Austria (iCT 2026) Special Issue of e-Journal of Nondestructive Testing (eJNDT) ISSN 1435-4934 },
	volume = {31(3)},
	year = {2026},
	doi = {https://doi.org/10.58286/32583},
	author = {Joaquim G. Sanctorum and Nathan Bekaert and Wikke Witteveen and Geert Potters and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2401,
	title = {Correcting for focal spot drift in edge illumination X-ray phase contrast imaging},
	booktitle = {14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium},
	year = {2025},
	doi = {doi.org/10.58286/30746},
	author = {Nicholas Francken and Jonathan Sanctorum and Ben Huyge and Jan Sijbers and Jan De Beenhouwer}
}
@article {2412,
	title = {DAMMER: Direct Adaptive Multi-resolution MEsh Reconstruction from X-ray measurements},
	journal = {IEEE Transactions on Computational Imaging },
	volume = {11},
	year = {2025},
	pages = {926 - 941},
	doi = {10.1109/TCI.2025.3587408},
	author = {Jannes Merckx and Arnold Jan den Dekker and Jan Sijbers and Jan De Beenhouwer}
}
@article {2383,
	title = {Degradation Detection in Rice Products via Shape Variations in XCT Simulation-Empowered AI},
	journal = {Journal of Nondestructive Evaluation},
	volume = {44},
	year = {2025},
	doi = {https://doi.org/10.1007/s10921-024-01147-9},
	author = {Miroslav Yosifov and Thomas Lang and Virginia Florian and Stefan Gerth and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@mastersthesis {2415,
	title = {Edge illumination X-ray phase contrast imaging: Advancements in simulations and inline acquisitions},
	volume = {PhD in Sciences: Physics},
	year = {2025},
	type = {PhD thesis},
	author = {Nicholas Francken}
}
@article {2417,
	title = {Edge illumination X-ray phase contrast imaging with continuous mask motion},
	journal = {Optics Express},
	volume = {33},
	year = {2025},
	pages = {41271-41286},
	doi = {https://doi.org/10.1364/OE.570476},
	author = {Ben Huyge and Nicholas Francken and Joaquim Sanctorum and Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@article {2385,
	title = {Efficient X-ray dark field contrast simulations using a condensed history approach},
	journal = {Optics Express},
	volume = {33},
	year = {2025},
	month = {01/2025},
	pages = {3562-3576},
	doi = {10.1364/OE.544864},
	url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-33-2-3562\&id=567367},
	author = {Nicholas Francken and Jonathan Sanctorum and Ben Huyge and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2452,
	title = {Enhancing AdAPTS: Fast Field Evaporation Simulation with Parametric Local Electrodes for Atom Probe Tomography},
	year = {2025},
	abstract = {Atom probe tomography (APT) is a powerful technique for analyzing the composition of materials at the atomic level. However, no reconstruction method currently fully capitalizes on the spatial resolution potential of APT instrumentation. A model of field evaporation, efficiently and accurately describing ion trajectories, remains essential for reconstruction. To address this, we developed AdAPTS, a simulation tool that improves the efficiency of modeling individual evaporations compared to TAPSim. Both tools, however, lack a local electrode model, which influences ion trajectories. Directly incorporating a local electrode into the finite element mesh hinders simulation speed and memory efficiency. To overcome this, we introduce a local electrode feature in AdAPTS that leverages the superposition principle by projecting a solution of the field emitted by the local electrode onto a mesh of the experimental domain, resulting in constant computational overhead instead of recalculating the total electrostatic field in each iteration. The parametric definition of local electrodes allows for precise modeling of electrode geometries, providing a flexible framework for electrode design and potentially enabling more accurate 3D reconstruction. Future work will focus on integrating additional physical models in AdAPTS to expand its capabilities across diverse material systems.},
	url = {https://ge.iitm.ac.in/apt\&m-2025/schedule.html},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2450,
	title = {Exact reconstruction for helical cone-beam X-ray CT using the ASTRA toolbox},
	booktitle = {10th International Symposium on Digital Industrial Radiology and Computed Tomography, 1 {\textendash} 3 July 2025 in Paris, France (DIR 2025)},
	volume = {30(8)},
	year = {2025},
	url = {https://www.ndt.net/?id=31452},
	author = {Pavel Paramonov and Joaquim G. Sanctorum and Femke Danckaers and Jan De Beenhouwer and Jan Sijbers}
}
@article {2405,
	title = {Gratings for multiresolution edge illumination X-ray phase contrast imaging: concept and simulation},
	journal = {Optics Express},
	volume = {33},
	year = {2025},
	pages = {17886-17902},
	doi = {10.1364/OE.550252},
	author = {Pieter-Jan Vanthienen and Nicholas Francken and Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2400,
	title = {In-depth imaging of in-vitro tissue models using electrical impedance tomography},
	booktitle = {iCT 2025 - 14th Conference on Industrial Computed Tomography},
	volume = {4 - 7 February},
	year = {2025},
	doi = {doi.org/10.58286/30763},
	author = {Jian Deng and Babu Linkoon P Meenaketan and Saeedeh Ebrahimi Takalloo and Yoke Chin Chai and Tom Torfs and Dries Braeken and Jan De Beenhouwer and Jan Sijbers}
}
@article {2399,
	title = {Loss of the Ubiquitin-Associated Domain of sqstm1/p62 in Zebrafish Causes a Phenotype Resembling Paget{\textquoteright}s Disease of Bone},
	journal = {Calcified Tissue International},
	volume = {116},
	year = {2025},
	pages = {1-15},
	author = {Yentl Huybrechts and Rapha{\"e}l De Ridder and Dylan Bergen and Bjorn De Samber and Eveline Boudin and Francesca Tonelli and Dries Knapen and Lucia Vergauwen and Dorien Schepers and Evelien Van Dijck and Qiao Tong and Anja Verhulst and Jan De Beenhouwer and Jan Sijbers and Chrissy Hammond and Antonella Forlino and Geert Mortier and Paul Coucke and P Eckhard Witten and Ronald Young Kwon and Andy Willaert and Gretl Hendrickx and Wim Van Hul}
}
@article {2388,
	title = {Multi-contrast benchmarking of edge illumination Monte Carlo simulations using virtual gratings},
	journal = {Journal of Applied Physics},
	volume = {137},
	year = {2025},
	pages = {104904},
	doi = {10.1063/5.0244152},
	author = {Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@article {2407,
	title = {A PHASE-CONTRAST X-RAY IMAGING SYSTEM FOR OBTAINING A DARK-FIELD IMAGE AND A METHOD THEREFOR},
	number = {EP 4 351 425 B1},
	year = {2025},
	author = {Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2392,
	title = {Proximal Neural Networks based reconstruction for few-view CT applications},
	booktitle = {14th Conference on Industrial Computed Tomography (iCT), 4 - 7 February 2025, Antwerp, Belgium},
	year = {2025},
	author = {H. Le and Caroline Bossuyt and Julie Escoda and Marius Costin and Jan De Beenhouwer and Jan Sijbers}
}
@article {2425,
	title = {Superimposing Synthetic Defects into Real XCT Data and Segmentation-Based Comparison for Advanced Probability of Detection Evaluation},
	journal = { Journal of Nondestructive Evaluation },
	volume = {44},
	year = {2025},
	doi = {https://doi.org/10.1007/s10921-025-01262-1},
	author = {Miroslav Yosifov and Bernhard Fr{\"o}hler and Jan Sijbers and Jan De Beenhouwer and Johann Kastner and Christoph Heinzl}
}
@mastersthesis {2414,
	title = {Towards adaptive multi-resolution edge illumination X-ray phase contrast imaging},
	volume = {PhD in Sciences: Physics},
	year = {2025},
	type = {PhD thesis},
	author = {Pieter-Jan Vanthienen}
}
@inproceedings {2418,
	title = {About rapid phase-wrapping in terahertz phase contrast imaging},
	booktitle = {SPIE},
	volume = {13141},
	year = {2024},
	pages = {69-73},
	abstract = {Terahertz (THz) imaging has emerged as a powerful technique in diverse fields, ranging from medical diagnostics to material characterization. Due to its lower frequency, compared to x-ray-based techniques, THz imaging provides an alternative view into the internal structures of samples composed of low-density materials. Notably, phase contrast imaging is advantageous as it generally exhibits reduced distortion from refraction and reflection losses compared to attenuation contrast. However, in the course of THz phase measurements, a fresh issue arises. Due to the relatively wide beam shape of THz imaging combined with rapid phase wrapping, a new type of artifact emerges, posing a significant hindrance to the accuracy and reliability of the imaging process. This paper explores the intricate interplay between beam shape dynamics and phase-wrapping mechanisms in THz imaging systems, unraveling the source of the artifacts that arise from this phenomenon.},
	doi = {https://doi.org/10.1117/12.3027665},
	url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13141/131410F/About-rapid-phase-wrapping-in-terahertz-phase-contrast-imaging/10.1117/12.3027665.short},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2451,
	title = {AdAPTS: An Adaptive Atom Probe Tomography Simulation Library},
	year = {2024},
	abstract = {In atom probe tomography (APT), spatial reconstruction enables volumetric insight into a specimen{\textquoteright}s nanostructure. To this day, a fast reconstruction method which utilizes the true potential of APT in terms of resolution does not exist. A model of its effective inverse, the field evaporation, which provides a physically accurate description of the ion trajectories, is a crucial component in reconstruction. The simulation of each individual evaporation, such as in TAPSim, while being able to model some cases accurately, has been time inefficient. Novel methods track surface meshes, achieving better time efficiency, although at the cost of spatial accuracy.

We introduce AdAPTS, an adaptive atom probe tomography simulation library. AdAPTS is a modular volumetric finite element simulation and specimen modeling library for APT written in C++. It is capable of generating accurate detector hit maps of various specimens, efficiently representing and simulating the experimental domain from specimen to detector. Using AdAPTS, we are able to accurately simulate the field evaporation of various specimens, revealing realistic poles and zone lines.

AdAPTS utilizes a unique high quality mesh generation strategy, in which each individual atom is represented by a vertex carrying material property information (e.g. atomic mass, relative permittivity). To constitute the surrounding vacuum chamber, additional vertices are generated using efficient variable density Poisson disk sampling. The software library TetGen is used to Delaunay-tetrahedralize all generated vertices. This yields a tetrahedral mesh in which each element inherits its material properties from the material property previously assigned to each vertex. The resulting vacuum vertices constitute less than 2\% of the total vertices, effectively allowing for a fast and full-scale simulation without employing the finite element method/boundary element method (FEM/BEM) coupling scheme proposed by Fletcher et al. Simultaneously, this method provides a rigid surface notion that preserves local protrusions due to lattice nanostructure similar to TAPSim by Oberdorfer et al., which in turn preserves zone lines and poles on the hit map.

The modeling of a specimen comprises two steps. In the first step, individual crystal lattices can be defined using Bravais lattice descriptors (e.g. bcc, fcc), the material lattice constant and the Miller indices of the crystallic plane facing the detector. In the second step, the shape of the specimen and dopants contained within are modeled using implicit surfaces and binary set operators (e.g. union, intersection). However, for amorphous materials, the individual atomic positions can also be specified individually or generated by any other means. The height, tip radius and shank angle of an implicit  surface (a truncated cone with a quasi-hemispherical tip) that represents the specimen shape can be specified.

The modular finite element methods library MFEM is utilized to determine the electric field by solving Poisson{\textquoteright}s equation given an electric potential Dirichlet boundary condition at the base of the specimen. Using an Euler-forward scheme with variable time steps, the trajectory starting at each evaporation site is calculated. The trajectory integration is terminated when the trajectory intersects with the detector plane. To conclude, AdAPTS provides an efficient and accurate framework which combines specimen modeling with realistic field evaporation due to voltage pulses using state-of-the-art mesh generation and numerical simulation tools. A thorough quantitative comparison in terms of simulation time of the different simulators will be provided by the time of the conference.},
	url = {https://plan.events.mpg.de/event/261/contributions/1337/},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2379,
	title = {AdAPTS: An Adaptive Atom Probe Tomography Simulation Library},
	volume = {30},
	year = {2024},
	doi = {https://doi.org/10.1093/mam/ozae044.017},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@article {2323,
	title = {CAD-ASTRA: A versatile and efficient mesh projector for X-ray tomography with the ASTRA-toolbox},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {3425-3439},
	doi = {https://doi.org/10.1364/OE.498194},
	author = {Pavel Paramonov and Nicholas Francken and Jens Renders and Domenico Iuso and Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2419,
	title = {Coherent detection terahertz imaging with a continuous wave source},
	booktitle = {SPIE},
	volume = {13141},
	year = {2024},
	pages = {63-68},
	abstract = {The unique properties of terahertz (THz) radiation, coupled with its non-ionizing nature, enable high-contrast imaging of soft materials with less stringent safety precautions than those required for x-ray systems. In this study, we introduce novel methods for THz imaging using a system that employs two photoconductive antennas (PCAs): one as a Continuous-Wave (CW) source and the other as a coherent detector. To enable precise multiband imaging with high frequency resolution, a fiber stretcher for rapid phase modulation was included. This system allows for the registration of two types of imaging contrasts: light attenuation and phase shift. We outline methods for extracting these contrasts and evaluate the system{\textquoteright}s capabilities through experiments involving various materials and frequencies. Furthermore, its application in computed tomography is demonstrated. To the best of our knowledge, this is the first application of a CW setup based on PCAs for non-destructive inspection and imaging of concealed objects.},
	doi = {https://doi.org/10.1117/12.3027653},
	url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13141/131410E/Coherent-detection-terahertz-imaging-with-a-continuous-wave-source/10.1117/12.3027653.short},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2374,
	title = {Deep image prior for sparse-view reconstruction in static, rectangular multi-source x-ray CT systems for cargo scanning},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	doi = {https://doi.org/10.1117/12.3027668},
	author = {Caroline Bossuyt and Arnold Jan den Dekker and Domenico Iuso and T. Le Hoang and Julie Escoda and Marius Costin and Jan Sijbers and Jan De Beenhouwer}
}
@article {2360,
	title = {Direct reconstruction of wet foam from sparse-view, dynamic X-ray CT scans},
	journal = {Advanced Engineering Materials},
	volume = {2400957},
	year = {2024},
	pages = {1-10},
	doi = {https://doi.org/10.1002/adem.202400957},
	author = {Jens Renders and Lucia Mancini and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2376,
	title = {Dynamic flat field correction in edge illumination imaging},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	doi = {https://doi.org/10.1117/12.3028319},
	author = {Didem G{\"o}kbel Kekliko{\u g}lu and Nicholas Francken and Ben Huyge and Ziya Merdan and Jan De Beenhouwer and Jan Sijbers}
}
@article {2329,
	title = {Edge illumination x-ray phase contrast simulations using the CAD-ASTRA toolbox},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {10005-10021},
	doi = {10.1364/OE.516138},
	url = {https://opg.optica.org/oe/abstract.cfm?doi=10.1364/OE.516138},
	author = {Nicholas Francken and Jonathan Sanctorum and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2413,
	title = {Ensuring Flawlessness in Additive Manufacturing: Advances in X-ray Inspection Techniques for Efficient Defect Detection},
	volume = {PhD in Sciences},
	year = {2024},
	type = {PhD thesis},
	author = {Domenico Iuso}
}
@inproceedings {2375,
	title = {Fast and efficient tetrahedral volume mesh reconstruction with CAD-ASTRA},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	address = {San Diego, USA},
	doi = {https://doi.org/10.1117/12.3027610},
	author = {Jannes Merckx and Arnold Jan den Dekker and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2350,
	title = {High-resolution tiled X-ray cone-beam CT using the ASTRA toolbox},
	booktitle = {13th Conference on Industrial Computed Tomography (iCT) 2024},
	year = {2024},
	month = {03/2024},
	address = {School of Engineering, Wels Campus, Austria},
	abstract = {Dealing with large and/or elongated objects presents a challenge in micro computed tomography ({\textmu}CT). In conventional CT, the necessity for the X-ray beam to fully cover the scanned object which has to remain well within the detector boundaries is essential to avoid region-of-interest artifacts in the reconstructed images. Consequently, the magnification of the object and thereby the spatial resolution are limited by the physical dimensions and degrees of freedom of the imaging system. A possible way to increase the magnification and thus the resolution of a {\textmu}CT image is to perform a tiled scan of the object. In this paper, we propose an iterative reconstruction approach that yields a high-resolution image from such a tiled CT scan. The approach utilizes the ASTRA toolbox, leveraging its key features: the vector-based definition of projection geometry and the linear tomography operators. Our simulations demonstrate that the proposed approach achieves higher resolution through increased magnification.},
	keywords = {cone beam, iterative reconstruction, micro computed tomography, X-ray tomography},
	isbn = {1435-4934},
	doi = {10.58286/29258 },
	author = {Pavel Paramonov and Joaquim G. Sanctorum and Domenico Iuso and Jan Sijbers and Jan De Beenhouwer}
}
@article {2347,
	title = {Imaging Algorithm and Optimal Measurement Protocol for 3D Impedance Tomography on 2D High Density Micro Electrode Array},
	journal = {IEEE Sensors},
	volume = {24},
	year = {2024},
	pages = {24452-24465},
	doi = {10.1109/JSEN.2024.3417289},
	author = {Jian Deng and Jens Renders and Babu Linkoon P Meenaketan and Saeedeh Ebrahimi Takalloo and Dries Braeken and Jan De Beenhouwer and Jan Sijbers}
}
@mastersthesis {2363,
	title = {Improved 4DCT reconstruction algorithms for the imaging of foam microstructure formation},
	volume = {PhD in Sciences},
	year = {2024},
	type = {PhD thesis},
	author = {Jens Renders}
}
@mastersthesis {2326,
	title = {Improved X-ray CT reconstruction techniques with non-linear imaging models},
	year = {2024},
	type = {PhD thesis},
	author = {Nathana{\"e}l Six}
}
@inproceedings {2468,
	title = {Inline edge illumination through sample mask misalignment: a proof of concept},
	booktitle = {Proceedings of the 6th International Conference on X-ray and Neutron Phase Imaging with Gratings, Shenzhen, China},
	year = {2024},
	abstract = {Edge illumination (EI) is an X-ray phase contrast imaging setup that allows
measuring two additional complimentary contrasts. The setup consists of two absorbing
masks with slit shaped apertures. Typically, one of the masks is stepped during scans,
complicating the application of EI in inline settings. Current solutions exist, but require
either limiting the number of retrieved contrasts or fabricating specialized masks. In this
work, an EI scanning method with purposely misaligned conventional EI masks is
proposed to enable inline EI. Good agreement is found between conventional and inline EI
flatfield parameters, and first inline scan results are presented.},
	keywords = {X-ray phase contrast imaging},
	url = {https://files.sciconf.cn/upload/file/20240415/20240415160406_47435.pdf},
	author = {Nicholas Francken and Jan De Beenhouwer and Jan Sijbers}
}
@article {2348,
	title = {Inline edge illumination X-ray phase contrast imaging through mask misalignment},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {32048-32061},
	doi = {10.1364/OE.525730},
	author = {Nicholas Francken and Jonathan Sanctorum and Joaquim Sanctorum and Pieter-Jan Vanthienen and Jan Sijbers and Jan De Beenhouwer}
}
@article {2321,
	title = {Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {1135-1150},
	doi = {https://doi.org/10.1364/OE.502542},
	author = {Nathana{\"e}l Six and Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2467,
	title = {Mask assembly for edge illumination phase contrast radiation imaging},
	number = {EP2025062978W},
	year = {2024},
	month = {11/2025},
	edition = {G01N23/041 },
	chapter = {WO2025237942A1},
	abstract = {In general, the technology disclosed herein relates object inspection utilizing radiation imaging, more specifically, edge illumination phase contrast X-ray imaging. The apparatus and methods described in the present disclosure can be applied for inspection of various objects in different industrial settings, such as manufacturing, food, agriculture, aerospace, automotive, electronics, healthcare, transport, logistics, security, and others. An aspect of the present invention relates to a mask assembly for radiation phase contrast imaging apparatus, comprising a first mask comprising a plurality of X-ray absorbing element and apertures arranged in a manner that gradually diverges from one portion to an opposite portion of the body, resulting in a variable pitch perpendicular to the optical axis direction; and a mask alignment mechanism configured to adjust a position and/or orientation of the first mask to align the variable pitch of the first mask for phase contrast imaging.},
	author = {Jan De Beenhouwer and Jan Sijbers and Pieter-Jan Vanthienen}
}
@inproceedings {2378,
	title = {Multi-resolution gratings for edge illumination x-ray phase contrast imaging: a simulation study},
	booktitle = {Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	pages = {1315208},
	publisher = {International Society for Optics and Photonics},
	organization = {International Society for Optics and Photonics},
	keywords = {cone-beam, edge illumination, grating design, magnification, mask, monte-carlo, multi-resolution, Phase contrast},
	doi = {10.1117/12.3025968},
	url = {https://doi.org/10.1117/12.3025968},
	author = {Pieter-Jan Vanthienen and Nicholas Francken and Jan Sijbers and Jan De Beenhouwer}
}
@article {2358,
	title = {PACS: Projection-driven with Adaptive CADs X-ray Scatter compensation for additive manufacturing inspection},
	journal = {Precision Engineering},
	volume = {90},
	year = {2024},
	pages = {108-121},
	doi = {https://doi.org/10.1016/j.precisioneng.2024.08.006},
	author = {Domenico Iuso and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@article {2336,
	title = {Practical multi-mesh registration for few-view poly-chromatic X-ray inspection},
	journal = {Journal of Non-destructive Testing},
	volume = {43},
	year = {2024},
	chapter = {63},
	doi = {10.1007/s10921-024-01071-y},
	author = {Domenico Iuso and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@conference {2337,
	title = {Reconstruction with rigid motion correction technique in CT imaging: A simulation and application study},
	year = {2024},
	address = {Vietnam Institute for Advanced Study in Mathematics (VIASM), Hanoi, Vietnam},
	author = {Anh-Tuan Nguyen and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2449,
	title = {Simulating Atom Probe Tomography Using MFEM},
	year = {2024},
	abstract = {In atom probe tomography (APT), spatial reconstruction enables volumetric insight into a specimen{\textquoteright}s nanostructure. To this day, a fast reconstruction method which utilizes the true potential of APT in terms of resolution does not exist. A model of its effective inverse, the field evaporation, which provides a physically accurate description of the ion trajectories, is a crucial component in reconstruction. The simulation of each individual evaporation while has been time inefficient. We introduce AdAPTS, an adaptive atom probe tomography simulation library based on MFEM. AdAPTS is capable of generating accurate detector hit maps of various specimens, efficiently representing and simulating the experimental domain from specimen to detector. Using AdAPTS, we are able to accurately simulate the field evaporation of various specimens, revealing realistic poles and zone lines. },
	url = {https://mfem.org/workshop24/$\#$agenda},
	author = {Julian L{\"u}ken and Claudia Fleischmann and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2466,
	title = {A simulation study of optimized-aperture gratings for edge illumination cone-beam phase contrast x-ray imaging},
	booktitle = {Proceedings of the 6th International Conference on X-ray and Neutron Phase Imaging with Gratings},
	year = {2024},
	month = {04/2024},
	address = {Shenzhen, China},
	abstract = {Edge illumination (EI) is an established x-ray phase-contrast imaging method that relies on gratings to obtain attenuation, phase and dark field contrast. Despite the successful transition from synchrotron to lab sources, the cone-beam geometry of lab systems limits the effectiveness of conventional gratings. The non-parallel incidence of X-rays on planar gratings with equally sized apertures introduces unwanted shadowing effects. In this paper, a grating design with optimized position-dependent apertures is introduced and compared to a conventional grating and a grating with fan-beam shaped gratings bars. Numerical simulations show that this optimized-aperture design must be considered when constructing an EI setup.},
	author = {Pieter-Jan Vanthienen and Jan Sijbers and Jan De Beenhouwer}
}
@article {2349,
	title = {Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models},
	journal = {Applied Intelligence},
	volume = {54},
	year = {2024},
	pages = { 13160{\textendash}13177},
	doi = {https://doi.org/10.1007/s10489-024-05647-z},
	author = {Domenico Iuso and Soumick Chatterjee and Sven Cornelissen and Dries Verhees and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2373,
	title = {X-ray image reconstruction for continuous acquisition with accelerated rotation},
	booktitle = {SPIE Developments in X-Ray Tomography XV},
	volume = {13152},
	year = {2024},
	doi = {https://doi.org/10.1117/12.3027622},
	author = {Ben Huyge and Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2365,
	title = {X-ray image reconstruction for continuous acquisitions with a generalized motion model},
	journal = {Optics Express},
	volume = {32},
	year = {2024},
	pages = {39192-39207},
	doi = {https://doi.org/10.1364/OE.531999},
	author = {Ben Huyge and Jens Renders and Joaquim Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2295,
	title = {Adapting an XCT-scanner to enable edge illumination X-ray phase contrast imaging},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = {28},
	year = {2023},
	issn = {1435-4934},
	doi = {doi.org/10.58286/27755},
	author = {Ben Huyge and Pieter-Jan Vanthienen and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2287,
	title = {A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations},
	booktitle = {45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
	year = {2023},
	author = {Nicholas Francken and Jonathan Sanctorum and Jens Renders and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2292,
	title = {The Deep Steerable Convolutional Framelet Network for Suppressing Directional Artifacts in X-ray Tomosynthesis},
	booktitle = {31st European Signal Processing Conference, EUSIPCO},
	year = {2023},
	author = {Luis Filipe Alves Pereira and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2293,
	title = {Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = {28},
	year = {2023},
	issn = {1435-4934 },
	doi = {doi.org/10.58286/27716},
	author = {Miroslav Yosifov and Patrick Weinberger and Michael Reiter and Bernhard Fr{\"o}hler and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@inproceedings {2283,
	title = {DELTA-MRI: Direct deformation Estimation from LongiTudinally Acquired k-space data},
	booktitle = {IEEE International Symposium on Biomedical Imaging},
	year = {2023},
	pages = {1-4},
	doi = {10.1109/ISBI53787.2023.10230697},
	author = {Jens Renders and Banafshe Shafieizargar and Marleen Verhoye and Jan De Beenhouwer and Arnold Jan den Dekker and Jan Sijbers}
}
@article {2305,
	title = {Efficient iterative reconstruction with beam shape compensation for THz computed tomography},
	journal = {Applied Optics},
	volume = {62},
	year = {2023},
	month = {April 14, 2023},
	pages = {F31-F40},
	chapter = {F31},
	abstract = {Terahertz (THz) computed tomography is an emerging nondestructive and non-ionizing imaging method. Most THz reconstruction methods rely on the Radon transform, originating from x-ray imaging, in which x rays propagate in straight lines. However, a THz beam has a finite width, and ignoring its shape results in blurred reconstructed images. Moreover, accounting for the THz beam model in a straightforward way in an iterative reconstruction method results in extreme demands in memory and in slow convergence. In this paper, we propose an efficient iterative reconstruction that incorporates the THz beam shape, while avoiding the above disadvantages. Both simulation and real experiments show that our approach results in improved resolution recovery in the reconstructed image. Furthermore, we propose a suitable preconditioner to improve the convergence speed of our reconstruction.},
	keywords = {Beam shaping, computed tomography, Image quality, image reconstruction, THz imaging},
	doi = {https://doi.org/10.1364/AO.482511},
	url = {https://opg.optica.org/viewmedia.cfm?r=1\&rwjcode=ao\&uri=ao-62-17-F31\&seq=0},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2299,
	title = {Enhancing industrial inspection with efficient edge illumination x-ray phase contrast simulations},
	booktitle = {IEEE EUROCON 2023 -20th International Conference on Smart Technologies, Torino, Italy},
	year = {2023},
	author = {Nicholas Francken and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@article {2264,
	title = {Fast and accurate pose estimation of additive manufactured objects from few X-ray projections},
	journal = {Expert Systems With Applications},
	volume = {213},
	year = {2023},
	pages = {1-10},
	doi = {https://doi.org/10.1016/j.eswa.2022.118866},
	author = {Alice Presenti and Liang, Zhihua and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@article {2298,
	title = {Fiber Orientation Estimation from X-ray Dark Field Images of Fiber Reinforced Polymers using Constrained Spherical Deconvolution},
	journal = {Polymers},
	volume = {15},
	year = {2023},
	pages = {2887},
	doi = {https://doi.org/10.3390/polym15132887},
	author = {Ben Huyge and Jonathan Sanctorum and Ben Jeurissen and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2446,
	title = {Fitting a 2D mesh to X-ray measurements},
	booktitle = { 			 17th International Meeting on Fully 3D Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2023},
	address = {Stony Brook},
	author = {Merckx, Jannes and Jan Sijbers and Jan De Beenhouwer}
}
@article {2301,
	title = {Grating designs for cone beam edge illumination X-ray phase contrast imaging: a simulation study},
	journal = {Optics Express},
	volume = {31},
	year = {2023},
	pages = {28051-28064},
	abstract = {Edge illumination is an emerging X-ray phase contrast imaging technique providing attenuation, phase and dark field contrast. Despite the successful transition from synchrotron to lab sources, the cone beam geometry of lab systems limits the effectiveness of using conventional planar gratings. The non-parallel incidence of X-rays introduces shadowing effects, worsening with increasing cone angle. To overcome this limitation, several alternative grating designs can be considered. In this paper, the effectiveness of three alternative designs is compared to conventional gratings using numerical simulations. Improvements in flux and contrast are discussed, taking into account practical considerations concerning the implementation of the designs.},
	doi = {10.1364/OE.495789},
	url = {https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-17-28051\&id=536127},
	author = {Pieter-Jan Vanthienen and Jonathan Sanctorum and Ben Huyge and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@article {2304,
	title = {ImWIP: open-source image warping toolbox with adjoints and derivatives},
	journal = {SoftwareX},
	volume = {24},
	year = {2023},
	pages = {101524},
	doi = {https://doi.org/10.1016/j.softx.2023.101524},
	author = {Jens Renders and Ben Jeurissen and Anh-Tuan Nguyen and Jan De Beenhouwer and Jan Sijbers}
}
@mastersthesis {2290,
	title = {Parametric Fiber Analysis for Glass Fiber-reinforced Composite Tomographic Images},
	year = {2023},
	type = {PhD thesis},
	author = {Tim Elberfeld}
}
@article {2306,
	title = {A reconstruction method for atom probe tomography},
	number = {18017575},
	year = {2023},
	edition = {US20230307207A1},
	chapter = {US Patent App. 18/017,575, 2023},
	author = {Jan Sijbers and Jan De Beenhouwer and Yu-Ting Ling and Wilfried Vandervorst}
}
@inproceedings {2279,
	title = {Region-based motion-compensated iterative reconstruction technique for dynamic computed tomography},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI)},
	year = {2023},
	address = {Cartagena de Indias, Colombia},
	doi = {https://doi.org/10.1109/ISBI53787.2023.10230608},
	author = {Anh-Tuan Nguyen and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2281,
	title = {Sparse-view Medical Tomosynthesis via Mixed Scale Dense Convolutional Framelet Networks},
	booktitle = {IEEE International Symposium on Biomedical Imaging (ISBI)},
	year = {2023},
	pages = {880-884},
	doi = { https://doi.org/10.23919/EUSIPCO58844.2023.10289781},
	author = {Luis Filipe Alves Pereira and Jan De Beenhouwer and Jan Sijbers}
}
@article {2255,
	title = {Tabu-DART: A dynamic update strategy for efficient discrete algebraic reconstruction},
	journal = {The Visual Computer},
	volume = {39},
	year = {2023},
	pages = {4671{\textendash}4683},
	doi = {10.1007/s00371-022-02616-w},
	author = {Daniel Frenkel and Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2294,
	title = {Toward denoising of 3D CT scans with few data},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = {28},
	year = {2023},
	issn = {1435-4934},
	doi = {doi.org/10.58286/27741},
	author = {Liang, Zhihua and Anneke Van Heteren and Jan Sijbers and Jan De Beenhouwer}
}
@article {2204,
	title = {3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts},
	journal = {Measurement Science and Technology},
	volume = {33},
	year = {2022},
	pages = {1-12},
	doi = {10.1088/1361-6501/ac459a},
	author = {Rob Heylen and Aditi Thanki and Dries Verhees and Domenico Iuso and Jan De Beenhouwer and Jan Sijbers and Ann Witvrouw and Han Haitjema and Abdellatif Bey-Temsamani}
}
@mastersthesis {2280,
	title = {3D X-ray radiography-based inspection of manufactured objects},
	volume = {PhD},
	year = {2022},
	type = {PhD thesis},
	author = {Alice Presenti}
}
@inproceedings {2239,
	title = {An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography},
	booktitle = {Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122421F},
	year = {2022},
	address = {San Diego, CA, United States},
	doi = {https://doi.org/10.1117/12.2631570},
	author = {Anh-Tuan Nguyen and Jens Renders and Jeroen Soete and Martine Wevers and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2268,
	title = {Adaptive triangular mesh for phase contrast imaging},
	year = {2022},
	url = {https://ictms2022.sciencesconf.org/385325/document},
	author = {Jannes Merckx and Bart van Lith and Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {2278,
	title = {Advances in biplanar X-ray imaging: calibration and 2D/3D registration},
	volume = {PhD},
	year = {2022},
	type = {PhD thesis},
	author = {Van Nguyen}
}
@inproceedings {2262,
	title = {Alternative grating designs for cone-beam edge illumination X-ray phase contrast imaging},
	booktitle = { Proc. SPIE 12242, Developments in X-Ray Tomography XIV},
	volume = {12242},
	year = {2022},
	month = {10/2022},
	pages = {122420Z},
	publisher = {SPIE},
	organization = {SPIE},
	address = {San Diego, USA},
	doi = {10.1117/12.2632301},
	author = {Pieter-Jan Vanthienen and Jonathan Sanctorum and Ben Huyge and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2192,
	title = {Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography},
	booktitle = {e-Journal of Nondestructive Testing},
	volume = { 27 (3)},
	year = {2022},
	pages = {1-5},
	doi = {https://doi.org/10.58286/26588},
	url = {https://www.ndt.net/search/docs.php3?id=26588},
	author = {Anh-Tuan Nguyen and Jens Renders and Jeroen Soete and Martine Wevers and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2237,
	title = {Augmenting a conventional X-ray scanner with edge illumination based phase contrast imaging: how to design the gratings?},
	booktitle = {Proc. SPIE 12242, Developments in X-Ray Tomography XIV},
	year = {2022},
	month = {10/2022},
	pages = {1224218},
	publisher = {SPIE},
	organization = {SPIE},
	address = {San Diego, USA},
	doi = {10.1117/12.2633455},
	author = {Jonathan Sanctorum and Nathana{\"e}l Six and Jan Sijbers and Jan De Beenhouwer}
}
@article {2236,
	title = {Automatic anomaly detection from X-ray images based on autoencoder},
	journal = {Nondestructive Testing and Evaluation},
	volume = {37},
	year = {2022},
	doi = {10.1080/10589759.2022.2074415},
	author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@article {2257,
	title = {Automatic landmark detection and mapping for 2D/3D registration with BoneNet},
	journal = {Frontiers Veterinary Science},
	year = {2022},
	doi = {https://doi.org/10.3389/fvets.2022.923449},
	author = {Van Nguyen and Luis Filipe Alves Pereira and Liang, Zhihua and Falk Mielke and Jeroen Van Houtte and Jan Sijbers and Jan De Beenhouwer}
}
@article {2212,
	title = {A Bottom-Up Volume Reconstruction Method for Atom Probe Tomography},
	journal = {Microscopy and Microanalysis},
	volume = {28},
	year = {2022},
	pages = {1-14},
	doi = {10.1017/S1431927621012836},
	author = {Yu-Ting Ling and Siegfried Cools and Janusz Bogdanowicz and Claudia Fleischmann and Jan De Beenhouwer and Jan Sijbers and Wilfried Vandervorst}
}
@inproceedings {2194,
	title = {CNN-based pose estimation from a single X-ray projection for 3D inspection of manufactured objects},
	booktitle = {11th Conference on Industrial Computed Tomography},
	year = {2022},
	author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@article {2276,
	title = {cuPARE: Parametric Reconstruction of Curved Fibres from Glass fibre-reinforced Composites},
	journal = {Nondestructive Testing and Evaluation},
	year = {2022},
	doi = {10.1080/10589759.2022.2155647},
	author = {Tim Elberfeld and Bernhard Fr{\"o}hler and Christoph Heinzl and Jan Sijbers and Jan De Beenhouwer}
}
@article {2193,
	title = {Discrete Terahertz tomography: a simulation study},
	journal = {e-Journal of Nondestructive Testing},
	volume = {27},
	year = {2022},
	issn = {1435-4934},
	doi = {doi.org/10.58286/26608},
	author = {Jana Christopher and Lars-Paul Lumbeeck and Pavel Paramonov and Jan De Beenhouwer and Jan Sijbers}
}
@conference {2269,
	title = {Edge Illumination Phase Contrast Simulations Using the OptiX GPU Ray Tracing Engine},
	year = {2022},
	author = {Nicholas Francken and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2240,
	title = {Efficient X-ray projection of triangular meshes based on ray tracing and rasterization},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {122420W },
	doi = {https://doi.org/10.1117/12.2633448},
	author = {Pavel Paramonov and Jens Renders and Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2243,
	title = {Evaluation of deeply supervised neural networks for 3D pore segmentation in additive manufacturing},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {122421K},
	doi = {https://doi.org/10.1117/12.2633318},
	author = {Domenico Iuso and Soumick Chatterjee and Rob Heylen and Sven Cornelissen and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2272,
	title = {Fiber orientation estimation by constrained spherical deconvolution of the anisotropic edge illumination x-ray dark field signal},
	booktitle = {SPIE: Developments in X-Ray Tomography XIV},
	volume = {12242},
	year = {2022},
	pages = {122420V },
	doi = {ttps://doi.org/10.1117/12.2633482},
	author = {Ben Huyge and Ben Jeurissen and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2242,
	title = {Joint reconstruction of attenuation, refraction and dark field X-ray phase contrasts using split Barzilai-Borwein steps},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {122420O},
	doi = {https://doi.org/10.1117/12.2633587},
	author = {Nathana{\"e}l Six and Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2241,
	title = {Optimization of a multi-source rectangular X-ray CT geometry for inline inspection},
	booktitle = {SPIE Optical Engineering: Developments in X-Ray Tomography XIV },
	volume = {12242},
	year = {2022},
	pages = {1224219 },
	doi = {https://doi.org/10.1117/12.2633523},
	author = {Caroline Bossuyt and Jan De Beenhouwer and Jan Sijbers}
}
@article {2246,
	title = {Probability of Detection applied to X-ray inspection using numerical simulations},
	journal = {Nondestructive Testing and Evaluation},
	volume = {37},
	year = {2022},
	pages = {536-551},
	doi = {10.1080/10589759.2022.2071892},
	author = {Miroslav Yosifov and M. Reiter and S. Heupl and C. Gusenbauer and Bernhard Fr{\"o}hler and R. Fernandez- Gutierrez and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@conference {2217,
	title = {Sparse view rectangular X-ray CT for cargo inspection using the ASTRA toolbox},
	year = {2022},
	author = {Caroline Bossuyt and Jan De Beenhouwer and Jan Sijbers}
}
@article {2249,
	title = {The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget{\textquoteright}s disease of bone?},
	journal = {Bone Reports},
	volume = {16},
	year = {2022},
	pages = {75-76},
	doi = {10.1016/j.bonr.2022.101483},
	author = {Yentl Huybrechts and Rapha{\"e}l De Ridder and Bjorn De Samber and Eveline Boudin and Francesca Tonelli and Dries Knapen and Dorien Schepers and Jan De Beenhouwer and Jan Sijbers and Antonella Forlino and Paul Coucke and P. Eckhard Witten and Ronald Kwon and Andy Willaert and Gretl Hendrickx and Wim Van Hul}
}
@article {2263,
	title = {Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging},
	journal = {Optics Express},
	volume = {31},
	year = {2022},
	pages = {38695-38708},
	doi = {https://doi.org/10.1364/OE.472145},
	author = {Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2170,
	title = {3D atomic resolution tomography from iDPC-STEM images using multiple atom model prior},
	year = {2021},
	author = {Shiva Hosseinnejad and E. G. T. Bosch and H. Kohr and I. Lazi{\'c} and V. Zharinov and E. Franken and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2186,
	title = {3D THz Tomography Incorporating the Beam Shape},
	booktitle = {2021 OSA Imaging and Applied Optics Congress},
	year = {2021},
	doi = {10.1364/AIS.2021.JTu5A.36},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@article {2144,
	title = {Adjoint image warping using multivariate splines with application to 4D-CT},
	journal = {Medical Physics},
	volume = {48},
	year = {2021},
	pages = {6362-6374},
	doi = {10.1002/mp.14765},
	author = {Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2098,
	title = {Analysis of flat fields in edge illumination phase contrast imaging},
	booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
	year = {2021},
	pages = {1310-1313},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Nice, France},
	doi = {10.1109/ISBI48211.2021.9433849},
	url = {https://ieeexplore.ieee.org/document/9433849},
	author = {Ben Huyge and Jonathan Sanctorum and Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2172,
	title = {CAD-based scatter compensation for polychromatic reconstruction of additive manufactured parts},
	booktitle = {IEEE ICIP},
	year = {2021},
	pages = {2948-2952},
	doi = {10.1109/ICIP42928.2021.9506536},
	author = {Domenico Iuso and Ehsan Nazemi and Nathana{\"e}l Six and Bjorn De Samber and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2201,
	title = {CNN-based Pose Estimation of Manufactured Objects During Inline X-ray Inspection},
	booktitle = {2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI)},
	year = {2021},
	abstract = {X-ray Computed Tomography (CT) is a nondestructive technique widely used for inspection of manufactured objects generated from a reference computer-aided-design (CAD) representation. In a conventional CT inspection framework, a volumetric reconstruction is computed from a large number of X-ray projections of the object. Afterwards, a surface is extracted, aligned and compared to the CAD model. For an accurate comparison, a high-resolution reconstruction is needed, requiring hundreds of projections, making this procedure not suitable for real-time inspection. In contrast to CT-based inspection, radiograph-based inspection only requires a few radiographs that then can be compared with simulated projections from the reference CAD model. For an effective comparison, however, an accurate 3D pose estimation of the object and consequent alignment between the measured object and the reference model are crucial. In this paper, we present an inline projection-based 3D pose estimation framework using convolutional neural networks (CNNs). Through realistic simulation experiments, we show that, with only two projections, estimation of the pose of the object is possible at the resolution of the acquisition system.},
	author = {Alice Presenti and Zhihua Liang and Luis Filipe Alves Pereira and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2099,
	title = {Dark field sensitivity in single mask edge illumination lung imaging},
	booktitle = {2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
	year = {2021},
	pages = {775-778},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Nice, France},
	doi = {10.1109/ISBI48211.2021.9434024},
	url = {https://ieeexplore.ieee.org/document/9434024},
	author = {Jonathan Sanctorum and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2158,
	title = {A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis},
	booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2021},
	author = {Luis Filipe Alves Pereira and Vincent Van Nieuwenhove and Jan De Beenhouwer and Jan Sijbers}
}
@article {2171,
	title = {Dynamic few-view X-ray imaging for inspection of CAD-based objects},
	journal = {Expert Systems with Applications},
	volume = {180},
	year = {2021},
	pages = {115012},
	keywords = {CAD, Dynamic acquisition, Few-view inspection, Pose estimation, Visibility angles},
	issn = {0957-4174},
	doi = {https://doi.org/10.1016/j.eswa.2021.115012},
	url = {https://www.sciencedirect.com/science/article/pii/S095741742100453X},
	author = {Alice Presenti and Jan Sijbers and Jan De Beenhouwer}
}
@article {2188,
	title = {Extended imaging volume in cone-beam x-ray tomography using the weighted simultaneous iterative reconstruction technique},
	journal = {Physics in Medicine and Biology},
	volume = {66},
	year = {2021},
	chapter = {165008},
	doi = {10.1088/1361-6560/ac16bc},
	author = {Joaquim Sanctorum and Sam Van Wassenbergh and Van Nguyen and Jan De Beenhouwer and Jan Sijbers and Joris J. J. Dirckx}
}
@article {2092,
	title = {FleXCT: a Flexible X-ray CT scanner with 10 degrees of freedom},
	journal = {Optics Express},
	volume = {29},
	year = {2021},
	pages = {3438-3457},
	doi = {https://doi.org/10.1364/OE.409982},
	author = {Bjorn De Samber and Jens Renders and Tim Elberfeld and Yves Maris and Jonathan Sanctorum and Nathana{\"e}l Six and Liang, Zhihua and Jan De Beenhouwer and Jan Sijbers}
}
@article {2203,
	title = {Gauss-Newton-Krylov for Reconstruction of Polychromatic X-ray CT Images},
	journal = {IEEE Transactions on Computational Imaging},
	volume = {7},
	year = {2021},
	pages = {1304-1313},
	doi = {10.1109/TCI.2021.3133226},
	author = {Nathana{\"e}l Six and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@article {2148,
	title = {Geometry Calibration of a Modular Stereo Cone-Beam X-ray CT System},
	journal = {Journal of Imaging},
	volume = {7},
	year = {2021},
	pages = {1-12},
	doi = {https://doi.org/10.3390/jimaging7030054},
	author = {Van Nguyen and Joaquim Sanctorum and Sam Van Wassenbergh and Joris J. J. Dirckx and Jan Sijbers and Jan De Beenhouwer}
}
@article {2096,
	title = {Joint Deblurring and Denoising of THz Time-Domain Images},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	pages = {162-176},
	doi = {10.1109/ACCESS.2020.3045605},
	author = {Marina Ljubenovi{\'c} and Lina Zhuang and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2198,
	title = {Mesh-based reconstruction of dynamic foam images using X-ray CT},
	booktitle = {International Conference on 3D Vision (3DV2021)},
	year = {2021},
	pages = {1312-1320},
	doi = {10.1109/3DV53792.2021.00138},
	author = {Jens Renders and Jan De Beenhouwer and Jan Sijbers}
}
@article {2163,
	title = {Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction},
	journal = {Applied Sciences},
	volume = {11},
	year = {2021},
	chapter = {3145},
	doi = {https://doi.org/10.3390/app11073145},
	author = {Ehsan Nazemi and Nathana{\"e}l Six and Domenico Iuso and Bjorn De Samber and Jan Sijbers and Jan De Beenhouwer}
}
@conference {2178,
	title = {Motion compensating X-ray micro-CT of diamonds in a processing stage},
	year = {2021},
	month = {September},
	author = {Jens Renders and Anh-Tuan Nguyen and Jan De Beenhouwer and Jan Sijbers}
}
@article {2071,
	title = {Projection-angle-dependent distortion correction in high-speed image-intensifier-based x-ray computed tomography},
	journal = {Measurement Science and Technology},
	volume = {32},
	year = {2021},
	pages = {1-11},
	doi = {10.1088/1361-6501/abb33e},
	author = {Joaquim Sanctorum and Sam Van Wassenbergh and Van Nguyen and Jan De Beenhouwer and Jan Sijbers and Joris J. J. Dirckx}
}
@inproceedings {2187,
	title = {A study of terahertz beam simulation with ray tracing for computed tomography},
	booktitle = {2021 OSA Imaging and Applied Optics Congress},
	year = {2021},
	doi = {10.1364/AIS.2021.JTu5A.37},
	author = {Pavel Paramonov and Lars-Paul Lumbeeck and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2157,
	title = {Tabu-DART: a dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search},
	booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2021},
	author = {Daniel Frenkel and Jan De Beenhouwer and Jan Sijbers}
}
@article {2087,
	title = {To Recurse or not to Recurse A Low Dose CT Study},
	journal = {Progress in Artificial Intelligence},
	volume = {10},
	year = {2021},
	pages = {65{\textendash}81},
	doi = {https://doi.org/10.1007/s13748-020-00224-0},
	author = {Shabab Bazrafkan and Vincent Van Nieuwenhove and Joris Soons and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2053,
	title = {Accurate terahertz simulation with ray tracing incorporating beam shape and refraction},
	booktitle = {IEEE ICIP },
	year = {2020},
	pages = {3035-3039},
	doi = {10.1109/ICIP40778.2020.9190937},
	author = {Pavel Paramonov and Lars-Paul Lumbeeck and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1979,
	title = {An adaptive probability map for the Discrete Algebraic Reconstruction Technique},
	booktitle = {10th Conference on Industrial Computed Tomography (ICT 2020)},
	year = {2020},
	pages = {1-6},
	author = {Daniel Frenkel and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2028,
	title = {Adjoint pairs of image warping operators for motion modeling in 4D-CT},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	author = {Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@article {2057,
	title = {Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibres},
	journal = {Nondestructive Testing and Evaluation},
	volume = {35},
	year = {2020},
	pages = {328-341},
	doi = {https://doi.org/10.1080/10589759.2020.1774583},
	author = {Bernhard Fr{\"o}hler and Tim Elberfeld and Torsten M{\"o}ller and Hans-Christian Hege and Jan De Beenhouwer and Jan Sijbers and Johann Kastner and Christoph Heinzl}
}
@inproceedings {2084,
	title = {Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020)},
	year = {2020},
	author = {Benjamin Auer and Kesava Kalluri and Aly H. Abayazeed and Jan De Beenhouwer and Navid Zeraatkar and Clifford Lindsay and Neil Momsen and R. Garrett Richards and Micaehla May and Matthew A. Kupinski and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@inproceedings {2027,
	title = {BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	pages = {518-521},
	author = {Van Nguyen and Jan De Beenhouwer and Shabab Bazrafkan and A-T. Hoang and Sam Van Wassenbergh and Jan Sijbers}
}
@inproceedings {2034,
	title = {CNN-based Deblurring of Terahertz Images},
	booktitle = {Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)},
	volume = {4},
	year = {2020},
	pages = {323-330},
	doi = {10.5220/0008973103230330},
	author = {Marina Ljubenovi{\'c} and Shabab Bazrafkan and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1977,
	title = {Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT},
	booktitle = {10th Conference on Industrial Computed Tomography (ICT 2020)},
	year = {2020},
	author = {Alice Presenti and Shabab Bazrafkan and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2072,
	title = {Extreme Sparse X-ray Computed Laminography Via Convolutional Neural Networks},
	booktitle = {ICTAI 2020},
	year = {2020},
	author = {Luis Filipe Alves Pereira and Jan De Beenhouwer and Johann Kastner and Jan Sijbers}
}
@article {2083,
	title = {Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging},
	journal = {Journal of Nuclear Medicine},
	volume = {61},
	year = {2020},
	pages = {573},
	abstract = {573Objectives: Given its excellent resolution versus sensitivity trade-off, multi-pinhole SPECT has become a powerful tool for clinical imaging of small human structures such as the brain [1]. Our research team is designing and constructing a next-generation multi-pinhole system, AdaptiSPECT-C, for quantitative brain imaging. In this context, keel-edge pinhole has proven to increase significantly attenuation of gamma rays through the edges of the pinhole aperture compared to the most commonly clinically used knife-edge profile [2-4]. In this work, we investigate the potential improvement in imaging performance of multiple keel-edge pinhole profiles as a function of keel height for AdaptiSPECT-C compared to a knife-edge collimation for 123I-IMP brain perfusion. Methods: The prototype AdaptiSPECT-C system used herein is composed of 23 hexagonal detector modules hemi-spherically arranged along 3 rings. For modeling in GATE simulation (GS) [5], each of these modules is composed of 1.5 mm radius pinhole and a 1 cm thick NaI(Tl) crystal with a 5 cm thick back-scattering compartment, which was considered to simulate 123I down-scatter interactions. Multiple keel-edge heights, corresponding to 0.0 (knife edge), 0.375, 0.75, 1.0, 1.125, 1.5, 1.875, and 2.25 mm were studied. We evaluated the volumetric sensitivity and relative amount of collimator penetration for a 15\% energy window centered at 159 keV in simulated projections of a 21 cm diameter spherical source (e.g. corresponding to the system{\textquoteright}s volume of interest) centered at the focal point of the pinholes. For reconstruction, an approach developed in our group was employed for modeling using GS the system response and especially collimator penetration into the system matrix [6,7] for the knife and the keel-edge designs. An XCAT [8] brain phantom with source distribution for the perfusion imaging agent 123I-IMP was simulated using the pinhole designs. Projection were acquired considering two scenarios: noise free (S1), and equal imaging time comparison for a realistic clinical scan time (e.g. 30 min [9,10]) (S2). Reconstructions were performed with a customized 3D-MLEM software into images of 1203 voxels of (2 mm)3. The reconstructed images were then compared to the ground truth image in terms of the normalized root mean squared error (NRMSE) and activity recovery (\%AR) for selected three-dimensional brain regions. Results: A keel-edge height of 0.375-0.75 mm represents the best choice leading to a significant reduction of the amount of penetration (up to  50\%) at the expense of sensitivity (-20\%) compared to a knife-edge profile. Visually, for all scenarios, the use of such a keel-edge profile leads to better separation of the brain structures, especially the caudate and the putamen. When sensitivity is not taken into account (e.g. noise free scenario), increasing the keel height improves NRMSE results. For an equal imaging time comparison, lowest NRMSE values are achieved for a 0.375-0.75 mm keel-height. A further keel-height increase degrades the NRMSE results due to significant loss of counts compared to knife-edge design. A 0.75 mm keel height leads on average to the best \%ARs (e.g. closest value to 100\%), especially for the striatum and putamen. For cortex and cerebellum regions, \%ARs are comparable with those obtained for a knife-edge design. Conclusion: In this work, we demonstrated that the use of a  0.75 mm height keel-edge profile for AdaptiSPECT-C incorporating 1.5 mm radius pinholes leads to superior imaging performance compared to knife-edge collimation for clinical 123I brain perfusion imaging. A range of aperture radii from 0.5 to 3.5 mm for each design have been investigated and will be shown at the time of the conference. We are currently working on performing a numerical-observer task-performance study of defect-detection in perfusion. Research Support: National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institutes of Health, Grant No R01 EB022521. Volumetric Sensitivities, Amount of Penetration, and Lowest NRMSE for the designs investigated},
	url = {http://jnm.snmjournals.org/content/61/supplement_1/573.abstract},
	author = {Benjamin Auer and Kesava Kalluri and Jan De Beenhouwer and Navid Zeraatkar and Neil Momsen and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@article {2055,
	title = {A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system},
	journal = {Nondestructive Testing and Evaluation },
	volume = {35},
	year = {2020},
	pages = { 252-265},
	doi = {https://doi.org/10.1080/10589759.2020.1774580},
	author = {Van Nguyen and Jan De Beenhouwer and Joaquim Sanctorum and Sam Van Wassenbergh and Shabab Bazrafkan and Joris J. J. Dirckx and Jan Sijbers}
}
@article {2010,
	title = {A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants},
	journal = {Scientific Reports},
	volume = {10},
	year = {2020},
	doi = {https://doi.org/10.1038/s41598-019-57405-8},
	author = {Brian G. Booth and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {2133,
	title = {Newton-Krylov Methods For Polychromatic X-Ray CT},
	booktitle = {2020 IEEE International Conference on Image Processing (ICIP)},
	year = {2020},
	pages = {3045-3049},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Abu Dhabi},
	keywords = {Attenuation, computed tomography, image reconstruction, Jacobian matrices, Linear programming, Mathematical model, Structural beams},
	isbn = {978-1-7281-6396-3},
	doi = {10.1109/ICIP40778.2020.9190717},
	url = {https://ieeexplore.ieee.org/abstract/document/9190717},
	author = {Nathana{\"e}l Six and Jens Renders and Jan Sijbers and Jan De Beenhouwer}
}
@article {2018,
	title = {Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning},
	journal = {Food Control},
	volume = {113},
	year = {2020},
	pages = {1-13},
	doi = {https://doi.org/10.1016/j.foodcont.2020.107170},
	author = {Tim Van De Looverbosch and Hafizur Rahman Bhuiyan and Pieter Verboven and Manuel Dierick and Van Loo, D. and Jan De Beenhouwer and Jan Sijbers and Bart Nicolai}
}
@inproceedings {2054,
	title = {The Radon Transform for Terahertz Computed Tomography Incorporating the Beam Shape},
	booktitle = {IEEE ICIP},
	year = {2020},
	pages = {3040-3044},
	doi = {10.1109/ICIP40778.2020.9191175},
	author = {Lars-Paul Lumbeeck and Pavel Paramonov and Jan Sijbers and Jan De Beenhouwer}
}
@article {2082,
	title = {Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT},
	journal = {Journal of Nuclear Medicine},
	volume = {61},
	year = {2020},
	pages = {103},
	abstract = {103Objectives: Brain SPECT has many clinical applications, especially for cerebral blood flow and dopamine transporter imaging [1,2]. In this context, a dedicated brain imaging, multi-pinhole system, AdaptiSPECT-C, is being developed by our group. Recent studies in cardiac and small animal imaging have demonstrated that the use of curved detector could improve image quality, by reducing parallax errors due to the depth of interaction (DOI) effect [3,4]. In this simulation study, we proposed to investigate using reconstruction with DOI modeling the potential advantage in imaging performance of curved over flat detectors for 123I-IMP perfusion imaging using the AdaptiSPECT-C system. Methods: The AdaptiSPECT-C design used in this work consists of 26 detector modules, 158 by 158 mm2 in size, arranged around the patient{\textquoteright}s head in three rings. The simulated detector modules were composed of a 8 mm thick NaI(Tl) crystal coupled to a 5 cm thick back-scattering compartment, representing components behind the crystal, to model 123I down-scatter interactions. Each detector module is associated with a 1.36 mm radius direct knife-edge pinhole aperture collimator. Two different system designs were considered, one based on curved detectors, and the other on flat detectors. The curved detectors were designed so that the radius of curvature corresponds to the detector to system center distance (e.g. 30.5 cm). This distance was the same for the flat detectors. GATE simulation [5] was employed to compute the system matrix [6,7] for both detector designs by forming the system response for the activity within each three-dimensional image-voxel of a 24 cm diameter sphere, thus including DOI variations and corrections in reconstruction [6,7]. An XCAT brain phantom [8] emulating 123I-IMP perfusion source distribution was simulated using the two designs. Data were acquired following three scenarios: noise free case (S1), equal number of counts comparison (S2) (e.g. 5.5M detected counts [9]), and equal imaging time comparison for the typical scan time (e.g. 30 min [10]) (S3). For S3, the total number of counts for the curved and flat detector designs, were respectively 9.24M and 9.17M. Projections were reconstructed with 3D-MLEM into images of 1203 voxels of (2 mm)3 and reconstruction compared to the ground truth image. The normalized root mean squared error (NRMSE) as well as percentage of activity recovery (\%AR) for several brain regions were used to evaluate the image quality. Results: Only a small gain in volumetric sensitivity ( 0.8\%) was obtained with the curved detector design. Qualitatively, the reconstructions for the curved and flat detector designs appear similar for all the 3 noise scenarios. Differences are mostly for the peripheral regions of the head where the differences in the obliquity of the gamma-rays passing through the apertures would be the greatest. Due to lower activity, those regions are also more impacted by noise. Quantitatively, a slight NRMSE improvement using curved detectors was seen. The curved detector design leads on average to the best ARs, especially for the striatum and putamen. Regions at the edges of the brain (e.g. cortex and cerebellum), more impacted by DOI effect, are similarly recovered by the two designs. Conclusion: We demonstrated that using curved instead of flat detector for AdaptiSPECT-C with solely centered pinholes leads to small improvement in sensitivity and image quality based on visual inspection, NRMSE, and activity recovery analysis. Flat detector associated with a sophisticated DOI correction was found to lead to similar results than those obtained with the curved detector. Further investigation will be performed using additional pinholes irradiating the 4 quadrants of the detectors which will increase the obliquity of the rays striking the detectors and may thus result in larger difference. Research Support: Grant No R01 EB022521 (NIBIB).},
	url = {http://jnm.snmjournals.org/content/61/supplement_1/103.abstract},
	author = {Benjamin Auer and Kesava Kalluri and Jan De Beenhouwer and Kimberly Doty and Navid Zeraatkar and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@inproceedings {2029,
	title = {Ring Artifact Reduction in Sinogram Space Using Deep Learning},
	booktitle = {6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	author = {Maxime Nauwynck and Shabab Bazrafkan and Anneke Van Heteren and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2068,
	title = {Ringing Artefact Removal From Sparse View Tomosynthesis using Deep Neural Networks},
	booktitle = {The 6th International Conference on Image Formation in X-Ray Computed Tomography},
	year = {2020},
	pages = {380-383},
	author = {Shabab Bazrafkan and Vincent Van Nieuwenhove and Joris Soons and Jan De Beenhouwer and Jan Sijbers}
}
@article {2077,
	title = {X-ray phase contrast simulation for grating-based interferometry using GATE},
	journal = {Optics Express},
	volume = {28},
	year = {2020},
	pages = {33390-33412},
	doi = {https://doi.org/10.1364/OE.392337},
	author = {Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {2090,
	title = {CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	pages = {1-5},
	address = {Padova, Italy},
	author = {Alice Presenti and Jan Sijbers and Arnold Jan den Dekker and Jan De Beenhouwer}
}
@conference {1965,
	title = {Deep learning based missing wedge artefact removal for electron tomography},
	year = {2019},
	pages = {660-661},
	author = {Juho Rimpelainen and Shabab Bazrafkan and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {1945,
	title = {Dynamic angle selection for few-view X-ray inspection of CAD based objects},
	booktitle = {Proc. SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D)},
	volume = {11072},
	year = {2019},
	doi = {https://doi.org/10.1117/12.2534894},
	author = {Alice Presenti and Jan Sijbers and Jan De Beenhouwer}
}
@inproceedings {1883,
	title = {Fast detection of cracks in ultrasonically welded parts by inline X-ray inspection},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_48.pdf},
	author = {Eline Janssens and Jan Sijbers and Manuel Dierick and Jan De Beenhouwer}
}
@inproceedings {1946,
	title = {Fiber assignment by continuous tracking for parametric fiber reinforced polymer reconstruction},
	booktitle = {15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D)},
	volume = {11072},
	year = {2019},
	doi = {http://dx.doi.org/10.1117/12.2534836},
	author = {Tim Elberfeld and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1918,
	title = {An Interactive Visual Comparison Tool for 3D Volume Datasets represented by Nonlinearly Scaled 1D Line Plots through Space-filling Curves},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	author = {Johannes Weissenb{\"o}ck and Bernhard Fr{\"o}hler and Eduard Gr{\"o}ller and Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers and Santhosh Ayalur Karunakaran and Helmuth Hoeller and Johann Kastner and Christoph Heinzl}
}
@inproceedings {1989,
	title = {Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging},
	booktitle = {15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	volume = {11072},
	year = {2019},
	pages = {187 {\textendash} 190},
	publisher = {International Society for Optics and Photonics},
	organization = {International Society for Optics and Photonics},
	keywords = {image reconstruction, Monte-Carlo simulation, SPECT I-123 brain imaging, System response modeling, Variance reduction technique (forced detection)},
	doi = {10.1117/12.2534881},
	url = {https://doi.org/10.1117/12.2534881},
	author = {Benjamin Auer and Navid Zeraatkar and Jan De Beenhouwer and Kesava Kalluri and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@conference {1990,
	title = {Investigation of keel versus knife edge pinhole profiles for a next-generation SPECT system dedicated to clinical brain imaging},
	year = {2019},
	month = {2019},
	author = {Benjamin Auer and Kesava Kalluri and Jan De Beenhouwer and Navid Zeraatkar and Arda K{\"o}nik and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@inproceedings {1885,
	title = {A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_54.pdf},
	author = {Van Nguyen and Jan De Beenhouwer and Joaquim Sanctorum and Sam Van Wassenbergh and Peter Aerts and Joris J. J. Dirckx and Jan Sijbers}
}
@conference {1952,
	title = {Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images},
	year = {2019},
	month = {07/2019},
	abstract = {For the study of glass fiber-reinforced polymers (GFRP), {\textmu}CT is the method of choice. Obtaining
GFRP parameters from a {\textmu}CT scan is difficult, due to the presence of noise and artifacts. We propose a method
to improve GFRP image quality using a recently introduced deep neural network. We describe the network{\textquoteright}s
setup and the data generation and show how the trained network improves the reconstruction.},
	author = {Tim Elberfeld and Shabab Bazrafkan and Jan De Beenhouwer and Jan Sijbers}
}
@article {1973,
	title = {poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT},
	journal = {Optics Express},
	volume = {27},
	year = {2019},
	pages = {33427-33435},
	doi = {https://doi.org/10.1364/OE.27.033670},
	author = {Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1988,
	title = {Preliminary investigation of attenuation and scatter correction strategies for a next-generation SPECT system dedicated to quantitative clinical brain imaging},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2019},
	month = {11/2019},
	address = {Manchester, UK},
	author = {Benjamin Auer and Jan De Beenhouwer and Navid Zeraatkar and Philip H. Kuo and Lars R. Furenlid and Michael A. King}
}
@article {2085,
	title = {Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT},
	journal = {Physics in Medicine \& Biology},
	volume = {64},
	year = {2019},
	pages = {245001},
	abstract = {Multi-pinhole (MPH) collimators are known to provide better trade-off between sensitivity and resolution for preclinical, as well as for smaller regions in clinical SPECT imaging compared to conventional collimators. In addition to this geometric advantage, MPH plates typically offer better stopping power for penetration than the conventional collimators, which is especially relevant for I-123 imaging. The I-123 emits a series of high-energy (>300 keV,  2.5\% abundance) gamma photons in addition to the primary emission (159 keV, 83\% abundance). Despite their low abundance, high-energy photons penetrate through a low-energy parallel-hole (LEHR) collimator much more readily than the 159 keV photons, resulting in large downscatter in the photopeak window. In this work, we investigate the primary, scatter, and penetration characteristics of a single pinhole collimator that is commonly used for I-123 thyroid imaging and our two MPH collimators designed for I-123 DaTscan imaging for Parkinson{\textquoteright}s Disease, in comparison to three different parallel-hole collimators through a series of experiments and Monte Carlo simulations. The simulations of a point source and a digital human phantom with DaTscan activity distribution showed that our MPH collimators provide superior count performance in terms of high primary counts, low penetration, and low scatter counts compared to the parallel-hole and single pinhole collimators. For example, total scatter, multiple scatter, and collimator penetration events for the LEHR were 2.5, 7.6 and 14 times more than that of MPH within the 15\% photopeak window. The total scatter fraction for LEHR was 56\% where the largest contribution came from the high-energy scatter from the back compartments (31\%). For the same energy window, the total scatter for MPH was 21\% with only 1\% scatter from the back compartments. We therefore anticipate that using MPH collimators, higher quality reconstructions can be obtained in a substantially shorter acquisition time for I-123 DaTscan and thyroid imaging.},
	doi = {10.1088/1361-6560/ab58fe},
	url = {https://doi.org/10.1088\%2F1361-6560\%2Fab58fe},
	author = {Arda K{\"o}nik and Benjamin Auer and Jan De Beenhouwer and Kesava Kalluri and Navid Zeraatkar and Lars R. Furenlid and Michael A. King}
}
@inproceedings {1884,
	title = {Simulated grating-based x-ray phase contrast images of CFRP-like objects},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	pages = {1-8},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_45.pdf},
	author = {Jonathan Sanctorum and Jan De Beenhouwer and Johannes Weissenb{\"o}ck and Christoph Heinzl and Johann Kastner and Jan Sijbers}
}
@inproceedings {1917,
	title = {Tools for the Analysis of Datasets from X-Ray Computed Tomography based on Talbot-Lau Grating Interferometry},
	booktitle = {9th Conference on Industrial Computed Tomography},
	year = {2019},
	address = {Padova, Italy},
	url = {https://www.ndt.net/article/ctc2019/papers/iCT2019_Full_paper_52.pdf},
	author = {Bernhard Fr{\"o}hler and Lucas da Cunha Melo and Johannes Weissenb{\"o}ck and Johann Kastner and Torsten M{\"o}ller and Hans-Christian Hege and Eduard Gr{\"o}ller and Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers and Christoph Heinzl}
}
@conference {1980,
	title = {A Trajectory Based Bottom-Up Volume Reconstruction Method for Atom Probe Tomography},
	year = {2019},
	author = {Yu-Ting Ling and Siegfried Cools and Jan De Beenhouwer and Jan Sijbers and Wilfried Vandervorst}
}
@article {1923,
	title = {A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science},
	journal = {Computer Graphics Forum},
	volume = {38},
	year = {2019},
	pages = {273-283},
	doi = {10.1111/cgf.13688},
	author = {Bernhard Fr{\"o}hler and Tim Elberfeld and Torsten M{\"o}ller and Johannes Weissenb{\"o}ck and Jan De Beenhouwer and Jan Sijbers and Hans-Christian Hege and Johann Kastner and Christoph Heinzl}
}
@mastersthesis {1867,
	title = {Advances in X-ray reconstruction algorithms for limited data problems in conventional and non-conventional projection geometries},
	volume = {PhD in Sciences / Physics},
	year = {2018},
	type = {PhD thesis},
	author = {Eline Janssens}
}
@inproceedings {1831,
	title = {Comparative Visualization of Orientation Tensors in Fiber-Reinforced Polymers},
	booktitle = {8th Conference on Industrial Computed Tomography, Wels, Austria },
	year = {2018},
	author = {Johannes Weissenb{\"o}ck and M Arikan and D Salaberger and Johann Kastner and Jan De Beenhouwer and Jan Sijbers and S Rauchenzauner and T Raab-Wernig and E Gr{\"o}ller and Christoph Heinzl}
}
@inproceedings {1830,
	title = {An efficient CAD projector for X-ray projection based 3D inspection with the ASTRA Toolbox},
	booktitle = {8th Conference on Industrial Computed Tomography, Wels, Austria},
	year = {2018},
	author = {{\'A}rp{\'a}d Marinovszki and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1869,
	title = {Joint reconstruction and flat-field estimation using support estimation},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2018},
	address = {Sydney, Australia},
	doi = {10.1109/NSSMIC.2018.8824406},
	author = {Nathana{\"e}l Six and Jan De Beenhouwer and Vincent Van Nieuwenhove and Wim Vanroose and Jan Sijbers}
}
@article {1816,
	title = {Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection},
	journal = {Measurement Science and Technology},
	volume = {29},
	year = {2018},
	doi = {10.1088/1361-6501/aa9de3},
	author = {Eline Janssens and Jan De Beenhouwer and Mattias Van Dael and Thomas De Schryver and Luc Van Hoorebeke and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@conference {1847,
	title = {Parametric Reconstruction of Advanced Glass Fiber-reinforced Polymer Composites from X-ray Images},
	year = {2018},
	address = {Wels, Austria},
	abstract = {A novel approach to the reconstruction of glass fiber-reinforced polymers (GFRP) from X-ray micro-computed tomography
(μCT) data is presented. The traditional fiber analysis workflow requires complete sample reconstruction, pre-processing and
segmentation, followed by the analysis of fiber distribution, orientation, and other features of interest. Each step in the chain
introduces errors that propagate through the pipeline and impair the accuracy of the estimation of those features. In the
approach presented in this paper, we combine iterative reconstruction techniques and a priori knowledge about the sample, to
reconstruct the volume and estimate the orientation of the fibers simultaneously. Fibers are modeled using rigid cylinders in
space whose orientation and position is then iteratively refined. The output of the algorithm is a non voxel-based dataset of the
fibers{\textquoteright} parametric representation, allowing to directly assess fiber features and distribution characteristics and to simulate the resulting material properties.},
	keywords = {GFRP, Materials Science, Modeling of Microstructures, Parametric Reconstruction, Tomography, {\textmu}CT},
	author = {Tim Elberfeld and Jan De Beenhouwer and Arnold Jan den Dekker and Christoph Heinzl and Jan Sijbers}
}
@article {1859,
	title = {Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data - A Simulation Study},
	journal = {Journal of Nondestructive Evaluation},
	volume = {37},
	year = {2018},
	month = {Jul},
	pages = {1573-4862},
	abstract = {We present a new approach to estimate geometry parameters of glass fibers in glass fiber-reinforced polymers from simulated X-ray micro-computed tomography scans. Traditionally, these parameters are estimated using a multi-step procedure including image reconstruction, pre-processing, segmentation and analysis of features of interest. Each step in this chain introduces errors that propagate through the pipeline and impair the accuracy of the estimated parameters. In the approach presented in this paper, we reconstruct volumes from a low number of projection angles using an iterative reconstruction technique and then estimate position, direction and length of the contained fibers incorporating a priori knowledge about their shape, modeled as a geometric representation, which is then optimized. Using simulation experiments, we show that our method can estimate those representations even in presence of noisy data and only very few projection angles available.},
	keywords = {GFRP, Glass fiber reinforced polymer, Materials Science, Modeling of micro-structures, Parametric model, Tomography, {\textmu}CT},
	doi = {10.1007/s10921-018-0514-0},
	url = {https://doi.org/10.1007/s10921-018-0514-0},
	author = {Tim Elberfeld and Jan De Beenhouwer and Arnold Jan den Dekker and Christoph Heinzl and Jan Sijbers}
}
@inproceedings {1833,
	title = {pDART: Discrete algebraic reconstruction using a polychromatic forward model},
	booktitle = {The Fifth International Conference on Image Formation  in X-Ray Computed Tomography},
	year = {2018},
	address = {Salt Lake City, Utah, USA},
	author = {Nathana{\"e}l Six and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1880,
	title = {Preliminary evaluation of surface mesh modeling of system geometry, anatomy phantom, and source activity for GATE simulations},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2018},
	month = {11/2018},
	address = {Sydney, Australia},
	author = {Benjamin Auer and Arda K{\"o}nik and Timothy J. Fromme and Kesava Kalluri and Jan De Beenhouwer and George I. Zubal and Lars R. Furenlid and Michael A. King}
}
@inproceedings {1879,
	title = {Preliminary investigation of design parameters of an innovative multi- pinhole system dedicated to brain SPECT imaging},
	booktitle = {IEEE Nuclear Science Symposium and Medical Imaging Conference},
	year = {2018},
	month = {11/2018},
	address = {Sydney, Australia},
	author = {Benjamin Auer and Jan De Beenhouwer and Timothy J. Fromme and Kesava Kalluri and Justin C. Goding and George I. Zubal and Lars R. Furenlid and Michael A. King}
}
@article {1877,
	title = {Simulations of a Multipinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging},
	journal = {IEEE Transactions on Radiation and Plasma Medical Sciences},
	volume = {2},
	year = {2018},
	month = {Sept},
	pages = {444-451},
	keywords = {Analytical models, Apertures, Brain, Collimators, Logic gates, multipinhole (MPH), Sensitivity, simulation, Single photon emission computed tomography, SPECT},
	issn = {2469-7311},
	doi = {10.1109/TRPMS.2018.2831208},
	author = {Arda K{\"o}nik and Jan De Beenhouwer and J. M. Mukherjee and Kesava Kalluri and S Banerjee and N Zeraatkar and Timothy J. Fromme and Michael A. King}
}
@inproceedings {1858,
	title = {X-ray Phase-contrast Simulations of Fibrous Phantoms using GATE},
	booktitle = {2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)},
	year = {2018},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Sydney, Australia},
	doi = {10.1109/NSSMIC.2018.8824641},
	author = {Jonathan Sanctorum and Jan De Beenhouwer and Jan Sijbers}
}
@article {1727,
	title = {Data-Driven Affine Deformation Estimation and Correction in Cone Beam Computed Tomography},
	journal = {IEEE Transactions on Image Processing},
	volume = {26},
	year = {2017},
	pages = {1441-1451},
	doi = {10.1109/TIP.2017.2651370},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Thomas De Schryver and Luc Van Hoorebeke and Jan Sijbers}
}
@conference {1785,
	title = {Dual axis Dark Field Contrast Tomography for visualisation of scattering directions in a CFRP sample},
	year = {2017},
	pages = {79-80},
	address = {Z{\"u}rich, Switzerland},
	abstract = {In Carbon Fiber Reinforced Polymer (CFRP), the carbon fibers embedded into the polymer matrix cause scattering when inspected with X-rays. This scattering is captured within the dark field image when the sample is scanned with a grating based interferometer. The main disadvantage is, however, that only directional scattering information can be achieved due to the orientation of the gratings. By scanning the sample twice, with a 90 degrees rotation of the sample in between, information from two different scattering directions can be combined into one 3D reconstruction volume. In this abstract, such an approach is shown to improve the representation of scattering inside the sample.},
	keywords = {Dark field tomography, Dual axis, Phase contrast, Tomography, X-rays},
	url = {https://indico.psi.ch/getFile.py/access?resId=1\&materialId=2\&confId=5055},
	author = {Eline Janssens and Jan De Beenhouwer and Jonathan Sanctorum and Sascha Senck and Christoph Heinzl and Jan Sijbers}
}
@inproceedings {1753,
	title = {Fast Reconstruction of CFRP X-ray Images based on a Neural Network Filtered Backprojection Approach},
	booktitle = {7th Conference on Industrial Computed Tomography},
	year = {2017},
	address = {Leuven, Belgium},
	url = {http://www.ndt.net/events/iCT2017/app/content/Extended_Abstract/63_Janssens_Rev4.pdf},
	author = {Eline Janssens and Sascha Senck and Christoph Heinzl and Johann Kastner and Jan De Beenhouwer and Jan Sijbers}
}
@article {2047,
	title = {Mobile imaging of an object using penetrating radiation},
	number = {WO/2017/178334},
	year = {2017},
	chapter = {PCT/EP2017/058270},
	author = {Jan Sijbers and Jan De Beenhouwer}
}
@mastersthesis {1821,
	title = {Model-based reconstruction algorithms for dynamic X-ray CT},
	volume = {PhD in Sciences/Physics},
	year = {2017},
	type = {PhD thesis},
	author = {Vincent Van Nieuwenhove}
}
@article {1773,
	title = {MoVIT: A tomographic reconstruction framework for 4D-CT},
	journal = {Optics Express},
	volume = {25},
	year = {2017},
	pages = {19236-19250},
	abstract = {4D computed tomography (4D-CT) aims to visualise the temporal dynamics of a 3D sample with a sufficiently high temporal and spatial resolution.  Successive time frames are typically obtained by sequential scanning, followed by independent reconstruction of each 3D dataset. Such an approach requires a large number of projections for each scan to obtain images with sufficient quality (in terms of artefacts and SNR). Hence, there is a clear trade-off between the rotation speed of the gantry (i.e. time resolution) and the quality of the reconstructed images.
In this paper, the MotionVector-based Iterative Technique (MoVIT) is introduced which reconstructs a particular time frame by including the projections of neighbouring time frames as well. It is shown that such a  strategy improves the trade-off between the rotation speed and the SNR.
The framework is tested on both numerical simulations and on 4D X-ray CT datasets of polyurethane foam under compression.
Results show that reconstructions obtained with MoVIT have a significantly higher SNR compared to the SNR of conventional 4D reconstructions.},
	doi = {https://doi.org/10.1364/OE.25.019236},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jelle Vlassenbroeck and Mark Brennan and Jan Sijbers}
}
@inproceedings {1743,
	title = {Registration Based SIRT: A reconstruction algorithm for 4D CT},
	booktitle = {7th Conference on Industrial Computed Tomography},
	year = {2017},
	address = {Leuven, Belgium},
	abstract = {The goal of 4D computed tomography (4D CT) is to study the temporal deformation of a 3D sample with a sufficiently high temporal and spatial resolution. Conventionally, the sample is sequentially scanned, resulting in datasets of successive time frames. Each of these datasets is then independently reconstructed. This framework results in a trade-off between the temporal resolution and the signal-to-noise ratio (SNR) of the reconstructed images. The proposed registration based simultaneous iterative reconstruction technique (RBSIRT) allows shortening the acquisition time per time frame, leading to improved temporal resolution at comparable SNR. To this end, the algorithm estimates the deformation field between different time frames, which allows incorporating projections of other time frames into the reconstruction of a particular time frame. The technique was validated on numeric simulations and on a real dynamic experiment of a polyurethane foam sample. The reconstructions obtained with RBSIRT have a significantly higher SNR compared to the SNR of conventional 4D reconstructions.},
	url = {http://www.ndt.net/events/iCT2017/app/content/Paper/42_VanNieuwenhove.pdf},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jelle Vlassenbroeck and Maarten Moesen and Mark Brennan and Jan Sijbers}
}
@conference {1784,
	title = {A workflow to reconstruct grating-based X-ray phase contrast CT images: application to CFRP samples},
	year = {2017},
	pages = {139-140},
	address = {Z{\"u}rich, Switzerland},
	abstract = {Carbon fiber reinforced polymer (CFRP) is an extremely strong and lightweight plastic of which the strength depends on the distribution of its fibers. Fiber bundles can be visualized by means of phase contrast X-ray computed tomography (PCCT) based on grating-based interferometry (GBI). However, many steps are involved in the reconstruction of GBI-PCCT images. In this abstract, a workflow for the reconstruction of 3D CFRP phase contrast images based on GBI projection data is presented.},
	keywords = {Carbon fiber reinforced polymer, Image processing, Phase contrast, Tomography, X-rays},
	url = {https://indico.psi.ch/getFile.py/access?resId=1\&materialId=2\&confId=5055},
	author = {Jonathan Sanctorum and Eline Janssens and Arnold Jan den Dekker and Sascha Senck and Christoph Heinzl and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1652,
	title = {Discrete tomographic reconstruction from deliberately motion blurred X-ray projections},
	booktitle = {6th Conference on Industrial Computed Tomography},
	year = {2016},
	pages = {1-6},
	address = {Wels, Austria},
	author = {Wim Van Aarle and Jeroen Cant and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1619,
	title = {Dynamic flat field correction in X-ray computed tomography},
	booktitle = {Optimess conference},
	year = {2016},
	edition = {Antwerp},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1627,
	title = {A dynamic region estimation method for cerebral perfusion CT},
	booktitle = {6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS)},
	year = {2016},
	pages = {331-342},
	abstract = {In cerebral perfusion computed tomography (PCT), multiple scans of the brain are acquired after an intravenous contrast bolus injection. Therefore, radiation dose is a major issue. 
Recently, methods have been proposed that can reconstruct high quality dynamic (i.e., 4D) images, while keeping the radiation dose limited. These methods typically require an accurate estimate of the dynamic region inside the brain volume, i.e., the region containing tissue/vessels. Conventionally, the dynamic region is indicated manually.
In this work, a method for low-dose cerebral PCT is presented in which the dynamic region is estimated in an automatic way.
Simulation results on two PCT phantoms show that the dynamic region can be accurately estimated, even in a very low-dose regime, which is an important step towards more powerful reconstruction methods for low-dose cerebral PCT.
},
	author = {Van Eyndhoven, Geert and Jan De Beenhouwer and Jan Sijbers}
}
@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 {1665,
	title = {Fast inline inspection by neural network based filtered backprojection: Application to apple inspection},
	journal = {Case Studies in Nondestructive Testing and Evaluation},
	volume = {6},
	year = {2016},
	pages = {14{\textendash}20},
	doi = {10.1016/j.csndt.2016.03.003},
	author = {Eline Janssens and Luis Filipe Alves Pereira and Jan De Beenhouwer and Ing Ren Tsang and Mattias Van Dael and Pieter Verboven and Bart Nicolai and Jan Sijbers}
}
@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}
}
@inproceedings {1667,
	title = {Investigation on Effect of scintillator thickness on Afterglow in Indirect X-ray Detectors},
	booktitle = {6th Conference on Industrial Computed Tomography, Wels, Austria (iCT 2016)},
	year = {2016},
	abstract = {Solid-state scintillation detectors are widely used in modern multi-slice CT systems as well as synchrotron micro-tomography beamlines. Amongst other parameters, the performance of these detectors depends on the thickness of the scintillator. Thicker scintillators result in higher emission intensities, yet the resolution deteriorates as the thickness increases. To achieve a higher scan speed, thicker scintillators are more common. The thickness of scintillators however may influence the afterglow.  In this paper, we investigate the effect of scintillator thickness on the afterglow, using scintillating screens of two different materials (LAG:Ce and Gadox) and different thicknesses.  
Experimental results show that, apart from the scintillator material and excitation condition, the thickness of scintillator has a decisive role on the scintillator decay and particularly on the afterglow.
},
	keywords = {afterglow, flat-panel, image lag, scintillator thickness, synchrotron, x-ray detector},
	url = {http://www.ndt.net/article/ctc2016/papers/ICT2016_paper_id74.pdf},
	author = {Karim Zarei Zefreh and Jan De Beenhouwer and Federica Marone Welford and Jan Sijbers}
}
@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}
}
@inproceedings {1573,
	title = {Projection-based polygon estimation in X-ray computed tomography},
	booktitle = {6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS)},
	year = {2016},
	pages = {41-50},
	author = {Andrei Dabravolski and Jan De Beenhouwer and Jan Sijbers}
}
@inproceedings {1592,
	title = {Affine deformation correction in cone beam Computed Tomography},
	booktitle = {Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2015},
	pages = {182-185},
	address = {Newport, Rhode Island, USA},
	abstract = {In Computed Tomography (CT), motion and deformation during the acquisition produce streaks and blurring, known as motion artefacts. In contrast to other deformation correction techniques, this work introduces an efficient algorithm to correct for global affine deformations directly on the cone beam projections. During an experiment, the exact deformation parameters are unknown. These parameters are estimated in the projection domain by minimizing a plane based raw data redundancy criterion. Simulations and experimental data show a reduction of motion artefacts in the reconstructed images.},
	url = {http://fully3d.org/proceedings.html},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Thomas De Schryver and Luc Van Hoorebeke 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}
}
@article {1615,
	title = {Dynamic intensity normalization using eigen flat fields in X-ray imaging},
	journal = {Optics Express},
	volume = {23},
	year = {2015},
	pages = {27975-27989},
	abstract = {In X-ray imaging, it is common practice to normalize the acquired projection data with averaged flat fields taken prior to the scan. Unfortunately, due to source instabilities, vibrating beamline components such as the monochromator, time varying detector properties, or other confounding factors, flat fields are often far from stationary, resulting in significant systematic errors in intensity normalization. In this work, a simple and efficient method is proposed to account for dynamically varying flat fields. Through principal component analysis of a set of flat fields, eigen flat fields are computed. A linear combination of the most important eigen flat fields is then used to individually normalize each X-ray projection. Experiments show that the proposed dynamic flat field correction leads to a substantial reduction of systematic errors in projection intensity normalization compared to conventional flat field correction. },
	doi = {10.1364/OE.23.027975},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Francesco De Carlo and Lucia Mancini and Federica Marone and Jan Sijbers}
}
@conference {1618,
	title = {A fast 4D CT reconstruction algorithm for affine deforming objects},
	year = {2015},
	edition = {Helsinki},
	author = {Vincent Van Nieuwenhove and Jan De Beenhouwer and Jan Sijbers}
}
@article {1591,
	title = {Fast Neural Network Based X-Ray Tomography of Fruit on a Conveyor Belt},
	journal = {Chemical Engineering Transactions},
	volume = {44},
	year = {2015},
	pages = {181-186},
	address = {Milano, Italy},
	doi = {10.3303/CET1544031},
	author = {Eline Janssens and Daan Pelt and Jan De Beenhouwer and Mattias Van Dael and Pieter Verboven and Bart Nicolai 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}
}
@inproceedings {1576,
	title = {Neural Network Based X-Ray Tomography for Fast Inspection of Apples on a Conveyor Belt},
	booktitle = {IEEE International Conference on Image Processing},
	year = {2015},
	month = {Sept 21-27},
	pages = {917-921},
	doi = {10.1109/ICIP.2015.7350933},
	author = {Eline Janssens and Jan De Beenhouwer and Mattias Van Dael and Pieter Verboven and Bart Nicolai 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 {1504,
	title = {Combined Estimation of Affine Movement and Reconstruction in  Tomography},
	year = {2014},
	publisher = {3D Materials Science Conference},
	author = {Vincent Van Nieuwenhove and Van Eyndhoven, Geert and Jan De Beenhouwer and Jan Sijbers}
}
@conference {1503,
	title = {Compensation of affine deformations in fan and cone beam projections},
	year = {2014},
	pages = {187-189},
	author = {Vincent Van Nieuwenhove and Van Eyndhoven, Geert and Jan De Beenhouwer and Jan Sijbers}
}
@article {1472,
	title = {Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor},
	journal = {Progress in Nuclear Energy},
	volume = {72},
	year = {2014},
	pages = {55-62},
	doi = {http://dx.doi.org/10.1016/j.pnucene.2013.11.001},
	author = {Hakon Kristian Jenssen and B.C. Oberlander and Jan De Beenhouwer and Jan Sijbers and M. Verwerft}
}
@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}
}
@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}
}
