Publications

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Journal Article
A. Leemans, Sijbers, J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., Mathematical Framework for Simulating Diffusion Tensor MR Neural Fiber Bundles, Magnetic Resonance in Medicine, vol. 53, pp. 944-953, 2005.PDF icon Download full paper (1.55 MB)
R. Delgado Y Palacios, Adriaan, C., Kim, H., Verhoye, M., Poot, D. H. J., Jouke, D., Van Audekerke, J., Benveniste, H., Sijbers, J., Wiborg, O., and Van Der Linden, A., Magnetic resonance imaging and spectroscopy reveal differential hippocampal changes in anhedonic and resilient subtypes of the chronic mild stress rat model, Biological psychiatry, vol. 70, pp. 449-457, 2011.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I. B., Manko, O., Danilichev, S., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., Eulenburg, Pzu, Sijbers, J., Wuyts, F. L., and Jeurissen, B., Macro- and microstructural changes in cosmonauts’ brains after long-duration spaceflight, Science Advances, vol. 6, no. 36, p. eaaz9488, 2020.PDF icon Download paper (942.53 KB)
J. Juntu, Sijbers, J., De Backer, S., Rajan, J., and Van Dyck, D., A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images, Journal of Magnetic Resonance Imaging, vol. 31, pp. 680–689, 2010.PDF icon Download paper (300.61 KB)
B. Koirala, Zahiri, Z., and Scheunders, P., A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements, IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 10, pp. 7393-7405, 2020.PDF icon final_version_leaf_parameter_estimation.pdf (2.66 MB)
B. G. Booth, Sijbers, J., and De Beenhouwer, J., A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants, Scientific Reports, vol. 10, no. 661, 2020.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system, Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 252-265, 2020.
P. Scheunders, Local mapping for multispectral image visualisation, Image and Vision Computing, vol. 19, pp. 971-978, 2001.
V. Van Nieuwenhove, Van Eyndhoven, G., Batenburg, K. J., Buls, N., Vandemeulebroucke, J., De Beenhouwer, J., and Sijbers, J., Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT, Medical Physics, vol. 43, no. 12, pp. 6429-6438, 2016.
L. Emsell, Leemans, A., Langan, C., Van Hecke, W., Barker, G. J., McCarthy, P., Jeurissen, B., Sijbers, J., Sunaert, S., Cannon, D. M., and McDonald, C., Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion MRI tractography study, Biologicial Psychiatry, vol. 73, no. 2, pp. 194-201, 2013.
J. Sijbers, den Dekker, A. J., and Bos, R., A likelihood ratio test for functional MRI data analysis to account for colored noise, Lecture Notes in Computer Science, vol. 3708, pp. 538-546, 2005.PDF icon Download full paper (483.15 KB)
A. J. den Dekker, Poot, D. H. J., Bos, R., and Sijbers, J., Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study, IEEE Transactions on Medical Imaging, vol. 28, pp. 287-296, 2009.
E. Fransen, Dhooghe, R., Van Camp, G., Verhoye, M., Sijbers, J., Reyniers, E., Soriano, P., Kamiguchi, H., Willemsen, R., Koekoek, K. E., Zeeuw, D. C. I., De Deyn, P. P., Van Der Linden, A., Lemmon, V., Kooy, R. F., and Willems, P. J., L1 knockout mice show dilated ventricles, vermis hypoplasia and impaired exploration patterns, Human Molecular Genetics, vol. 7, pp. 999-1009, 1998.PDF icon Download paper (248.02 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)
P. Scheunders, Joint quantization and error-diffusion of color images using competitive learning, Journal of the IEE Proceedings, Vision, Image and Signal Processing, vol. 14, pp. 137-140, 1998.
N. Six, Renders, J., De Beenhouwer, J., and Sijbers, J., Joint multi-contrast CT for edge illumination X-ray phase contrast imaging using split Barzilai-Borwein steps, Optics Express, vol. 32, no. 2, pp. 1135-1150, 2024.PDF icon Download paper (13.42 MB)
Q. Beirinckx, Ramos-Llordén, G., Jeurissen, B., Poot, D. H. J., Parizel, P. M., Verhoye, M., Sijbers, J., and den Dekker, A. J., Joint Maximum Likelihood estimation of motion and T1 parameters from magnetic resonance images in a super-resolution framework: a simulation study, Fundamenta Informaticae, vol. 172, pp. 105–128, 2020.PDF icon Download paper (final author version) (2.15 MB)
M. Ljubenović, Zhuang, L., De Beenhouwer, J., and Sijbers, J., Joint Deblurring and Denoising of THz Time-Domain Images, IEEE Access, vol. 9, pp. 162-176, 2021.PDF icon Download paper (2.38 MB)
Q. Collier, Veraart, J., Jeurissen, B., den Dekker, A. J., and Sijbers, J., Iterative Reweighted Linear Least Squares for Accurate, Fast, and Robust Estimation of Diffusion Magnetic Resonance Parameters, Magnetic Resonance in Medicine, vol. 73, no. 6, pp. 2174–2184, 2015.
G. Van Eyndhoven, Batenburg, K. J., Kazantsev, D., Van Nieuwenhove, V., Lee, P. D., Dobson, K. J., and Sijbers, J., An iterative CT reconstruction algorithm for fast fluid flow imaging, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4446-4458, 2015.
G. Van Gompel, Van Slambrouck, K., Defrise, M., Batenburg, K. J., De Mey, J., Sijbers, J., and Nuyts, J., Iterative correction of beam hardening artifacts in CT, Medical Physics, vol. 38, pp. 36-49, 2011.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., Isotropic non-white matter partial volume effects in constrained spherical deconvolution, Information-based methods for neuroimaging: analyzing structure, function and dynamics, p. 112, 2015.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., Isotropic non-white matter partial volume effects in constrained spherical deconvolution, Frontiers in Neuroinformatics, vol. 8, pp. 1-9, 2014.PDF icon Download paper (1.79 MB)
D. Giraldo, Smith, R. E., Struyfs, H., Niemantsverdriet, E., De Roeck, E., Bjerke, M., Engelborghs, S., Romero, E., Sijbers, J., and Jeurissen, B., Investigating tissue-specific abnormalities in Alzheimer’s disease with multi-shell diffusion MRI, Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022.
B. Jeurissen, Leemans, A., Tournier, J. - D., Jones, D. K., and Sijbers, J., Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging., Human Brain Mapping, vol. 34, pp. 2747-66, 2013.

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