Publications

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A
H. Aerts, Schirner, M., Jeurissen, B., Van Roost, D., Achten, E., Ritter, P., and Marinazzo, D., Modeling brain dynamics in brain tumor patients using The Virtual Brain, eNeuro, 2018.
M. A. Akhter, Heylen, R., and Scheunders, P., A geometric matched filter for hyperspectral target detection and partial unmixing, IEEE Geoscience and Remote Sensing letters, vol. 12, pp. 661-665, 2015.
L. F. Alves Pereira, Janssens, E., Cavalcanti, G. D. C., Tsang, I. R., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Inline Discrete Tomography system: application to agricultural product inspection, Computers and Electronics in Agriculture, vol. 138, pp. 117–126, 2017.
V. Anania, Collier, Q., Veraart, J., Buikema, A. Eline, Vanhevel, F., Billiet, T., Jeurissen, B., den Dekker, A. J., and Sijbers, J., Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model, NeuroImage, vol. 256, p. 119219, 2022.
V. Andrejchenko, Liao, W., Philips, W., and Scheunders, P., Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields, Remote Sensing, vol. 11, 2019.PDF icon remotesensing-11-00624.pdf (1.5 MB)
B. T. Antonsen, Jiang, Y., Veraart, J., Qu, H., Nguyen, H. P., Sijbers, J., Von Hörsten, S., Johnson, A. G., and Leergaard, T. B., Altered diffusion tensor imaging measurements in aged transgenic Huntington disease rats., Brain structure & function, vol. 218, no. 3, pp. 767-78, 2013.PDF icon Download paper (645.02 KB)
M. Shahrimie Asaari, Mishra, P., Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., Close-range hyperspectral image analysis for the early detection of plant stress responses in individual plants in a high-throughput phenotyping platform, ISPRS Journal of Photogrammetry and Remote Sensing , vol. 138, pp. 121-138, 2018.
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., Wuyts, N., and Scheunders, P., Analysis of hyperspectral images for detection of drought stress and recovery in maize plants in a high-throughput phenotyping platform, Computers and Electronics in Agriculture, vol. 162, pp. 749-758, 2019.PDF icon shahrimie_2019.pdf (3.12 MB)
M. Shahrimie Asaari, Mertens, S., Verbraeken, L., Dhondt, S., Inze, D., Koirala, B., and Scheunders, P., Non-Destructive Analysis of Plant Physiological Traits Using Hyperspectral Imaging: A Case Study on Drought Stress, Computers and Electronics in Agriculture, vol. 195, no. 106806, 2022.PDF icon 1-s2.0-s0168169922001235-main.pdf (5.53 MB)
B. Auer, Kalluri, K., De Beenhouwer, J., Doty, K., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Reconstruction using Depth of Interaction Information of Curved and Flat Detector Designs for Quantitative Multi-Pinhole Brain SPECT, Journal of Nuclear Medicine, vol. 61, p. 103, 2020.PDF icon snm2020_recon_curved.pdf (103.23 KB)
B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Momsen, N., Kuo, P. H., Furenlid, L. R., and King, M. A., Keel-Edge Height Selection for Improved Multi-Pinhole 123I Brain SPECT Imaging, Journal of Nuclear Medicine, vol. 61, p. 573, 2020.PDF icon Download paper (127.73 KB)
B
M. Baillieux and Scheunders, P., On-line determination of the velocity of simultaneously moving organisms by image analysis for the detection of sublethal toxicity, Water Research, vol. 32, pp. 1027-1034, 1998.
S. Bals, Batenburg, K. J., Verbeeck, J., Sijbers, J., and Van Tendeloo, G., Quantitative three-dimensional reconstruction of catalyst particles for bamboo-like carbon nanotubes, Nano Letters, vol. 7, pp. 3669-3674, 2007.
G. Barisano, Sepehrband, F., Collins, H. R., Jillings, S., Jeurissen, B., Taylor, A. J., Schoenmaekers, C., De Laet, C., Rukavishnikov, I., Nosikova, I., Rumshiskaya, A., Annen, J., Sijbers, J., Laureys, S. S. L., Van Ombergen, A., Petrovichev, V., Sinitsyn, V., Pechenkova, E. V., Grishin, A., Eulenburg, Pzu, Law, M., Sunaert, S., Parizel, P. M., Tomilovskaya, E., Roberts, D., and Wuyts, F. L., The effect of prolonged Spaceflight on Cerebrospinal Fluid and Perivascular Spaces of Astronauts and Cosmonauts, PNAS, vol. 119, no. 17, 2022.
K. J. Batenburg, Sijbers, J., Poulsen, H. F., and Knudsen, E., DART: A Robust Algorithm for Fast Reconstruction of 3D Grain Maps, Journal of Applied Crystallography, vol. 43, pp. 1464-1473, 2010.PDF icon Download paper (824.99 KB)
K. J. Batenburg, Palenstijn, W. J., Balazs, P., and Sijbers, J., Dynamic angle selection in binary tomography, Computer Vision and Image Understanding, vol. 117, no. 5, pp. 306–318, 2013.PDF icon Download paper (2.71 MB)
K. J. Batenburg, Van Aarle, W., and Sijbers, J., A Semi-Automatic Algorithm for Grey Level Estimation in Tomography, Pattern Recognition Letters, vol. 32, pp. 1395-1405, 2011.
K. J. Batenburg, De Carlo, F., Mancini, L., and Sijbers, J., Advanced X-ray tomography: experiment, modeling, and algorithms, Measurement Science and Technology, vol. 29, no. 8, p. 080101, 2018.
K. J. Batenburg and Sijbers, J., Optimal Threshold Selection for Tomogram Segmentation by Projection Distance Minimization, IEEE Transactions on Medical Imaging, vol. 28, pp. 676-686, 2009.PDF icon Download full paper (2.51 MB)
K. J. Batenburg and Sijbers, J., DART: A practical reconstruction algorithm for discrete tomography, IEEE Transactions on Image Processing, vol. 20, pp. 2542-2553, 2011.PDF icon Download paper (2.12 MB)
K. J. Batenburg, Bals, S., Sijbers, J., Kubel, C., Midgley, P. A., Hernandez, J. C., Kaiser, U., Encina, E. R., Coronado, E. A., and Van Tendeloo, G., 3D imaging of nanomaterials by discrete tomography, Ultramicroscopy, vol. 109, pp. 730-740, 2009.
K. J. Batenburg and Sijbers, J., Adaptive thresholding of tomograms by projection distance minimization, Pattern Recognition, vol. 42, pp. 2297-2305, 2009.PDF icon Download paper (1.05 MB)
K. J. Batenburg and Sijbers, J., Generic iterative subset algorithms for discrete tomography, Discrete Applied Mathematics, vol. 157, pp. 438-451, 2009.PDF icon Download paper (1.41 MB)
S. Bazrafkan, Van Nieuwenhove, V., Soons, J., De Beenhouwer, J., and Sijbers, J., To Recurse or not to Recurse A Low Dose CT Study, Progress in Artificial Intelligence, vol. 10, pp. 65–81, 2021.
Q. Beirinckx, Jeurissen, B., Nicastro, M., Poot, D. H. J., Verhoye, M., den Dekker, A. J., and Sijbers, J., Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping, Computerized Medical Imaging and Graphics, In Press.

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