Publications

Export 1318 results:
Author [ Type(Asc)] Year
Patent
K. J. Batenburg, Sijbers, J., and Plantagie, L., “Filter for Tomographic Reconstructions”, U.S. Patent WO2013011031A12014.
K. J. Batenburg and Sijbers, J., “Dynamic tomography angle selection”, U.S. Patent PCT/EP2012/0714212013.
J. Cant and Sijbers, J., “Computerized Tomographic Image Exposure and Reconstruction Method”, U.S. Patent PCT/EP2015/0599562016.PDF icon Download patent (595.32 KB)
S. Verwulgen, Lacko, D., Vleugels, J., Huysmans, T., and Truijen, S., “Brain Computer Interface”, 2020.
M. Van Dael, Verboven, P., Nicolai, B., Dhaene, J., Van Hoorebeke, L., and Sijbers, J., “Automated quality control and selection ”, U.S. Patent PCT/EP2016/0557182016.
Miscellaneous
N. Garofil, “On the problem of uploading pdf files”. 2016.PDF icon testje.pdf (36.47 KB)
G. Ramos-Llordén, den Dekker, A. J., and Sijbers, J., “Joint motion correction and estimation for T1 mapping: proof of concept”, Medical Imaging Summer School 2014, Favignana, Italy. 2014.
Journal Article
J. Sanctorum, De Beenhouwer, J., and Sijbers, J., “X-ray phase contrast simulation for grating-based interferometry using GATE”, Optics Express, vol. 28, no. 22, pp. 33390-33412, 2020.PDF icon Download paper (2.5 MB)
G. Perfetti, Van de Casteele, E., Rieger, B., Wildeboer, W. J., and Meesters, G. M. H., “X-ray micro tomography and image analysis as complementary methods for morphological characterization and coating thickness measurement of coated particles”, Advanced Powder Technology, vol. 21, no. 6, pp. 663 - 675, 2010.
B. Huyge, Renders, J., Sanctorum, J., De Beenhouwer, J., and Sijbers, J., “X-ray image reconstruction for continuous acquisitions with a generalized motion model”, Optics Express, vol. 32, no. 22, pp. 39192-39207, 2024.
S. Van Dongen, Danckaers, F., Beerten, J., and Huysmans, T., “Women's preferences for male facial masculinity are not condition-dependent in a large online study”, The All Results Journals: Biol, vol. 10, no. 1, 2019.
H. Zivari Adab, Chalavi, S., Beets, I., Gooijers, J., Leunissen, I., Cheval, B., Collier, Q., Sijbers, J., Jeurissen, B., Swinnen, S. P., and Boisgontier, M., “White matter microstructural organization of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults”, European Journal of Neuroscience , vol. 47, no. 5, pp. 446–459, 2018.
J. Veraart, Sijbers, J., Sunaert, S., Leemans, A., and Jeurissen, B., “Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls.”, NeuroImage, vol. 81, no. 1, pp. 335-346, 2013.PDF icon Download paper (2.89 MB)
G. Van de Wouwer and Scheunders, P., “Wavelet-based texture classification”, Recent Research in the Development of Pattern Recognition, vol. 1, pp. 77-87, 2000.
P. Scheunders, Livens, S., Van de Wouwer, G., Vautrot, P., and Van Dyck, D., “Wavelet-based texture analysis”, Intern. Journal on Computer Science and Information Management, vol. 1, pp. 22-34, 1998.
A. Duijster, Scheunders, P., and De Backer, S., “Wavelet-Based EM Algorithm for Multispectral-Image Restoration”, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3892-3898, 2009.
P. Scheunders, “Wavelet thresholding of multivalued images”, IEEE Transactions on Image Processing, vol. 13, pp. 475-483, 2004.
P. Scheunders and De Backer, S., “Wavelet denoising of multicomponent images, using Gaussian Scale Mixture models and a noise-free image as priors”, IEEE Transactions on Image Processing, vol. 16, pp. 1865-1872, 2007.
G. Van de Wouwer, Scheunders, P., Livens, S., and Van Dyck, D., “Wavelet correlation signatures for color texture characterization”, pattern Recognition, vol. 32, pp. 443-451, 1999.
J. Sijbers, Verhoye, M., Scheunders, P., Van Der Linden, A., Van Dyck, D., and Raman, E., “Watershed based segmentation of 3D MR data for volume quantization”, Magnetic Resonance Imaging, vol. 15, pp. 679-688, 1997.PDF icon Download paper (3.18 MB)
D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, In Press.
A. Karami, M.Rashidinejad,, and Gharaveisi, A. A., “Voltage Security Enhancement and Congestion Management via STATCOM & IPFC Using Artificial Intelligence”, Iranian Journal of Science and Technology, vol. 1, no. 5, 2007.
G. Van de Wouwer, Scheunders, P., Van Dyck, D., Wuyts, F. L., and Van de Heyning, P. H., “Voice recognition from spectrograms: a wavelet based approach”, Fractals, vol. 5, pp. 165-172, 1997.
B. Fröhler, Elberfeld, T., Möller, T., Weissenböck, J., De Beenhouwer, J., Sijbers, J., Hege, H. - C., Kastner, J., and Heinzl, C., “A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science”, Computer Graphics Forum, vol. 38, no. 3, pp. 273-283, 2019.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging”, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)

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