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S. Jillings, The impact of long-duration spaceflight on brain structure and function, University of Antwerp, 2021.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., P Eulenburg, zu, Sijbers, J., Wuyts, F. L., and Jeurissen, B., Diffusion MRI reveals macro- and microstructural changes in cosmonauts' brains after long-duration spaceflight, Proc Intl Soc Mag Reson Med 28. p. 4531, 2020.
J. S. Jorgensen and Sijbers, J., Just enough physics, in Computed Tomography: Algorithms, Insight, and Just Enough Theory , vol. 4, SIAM, 2021.
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)
J. Juntu, Schepper, A. D. M., Van Dyck, P., Van Dyck, D., Gielen, J. L., Parizel, P. M., and Sijbers, J., Classification of Soft Tissue Tumors by Machine Learning Algorithms, in Soft Tissue Tumors, InTech, 2011.PDF icon Book.Chapter-Copy.Sent_.to_.InTech-(21.07.2011).pdf (732.07 KB)
J. Juntu, Sijbers, J., Van Dyck, D., and Gielen, J. L., Bias Field Correction for MRI Images, in Proceedings of the 4th International Conference on Computer Recognition Systems (CORES05), Rydzyna Castle, Poland, 2005, pp. 543-551.
J. Juntu, Sijbers, J., and Van Dyck, D., Classification of soft tissue tumors in MRI images using kernel PCA and regularized least square classifier, in Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, Anaheim, CA, USA, 2007, pp. 362–367.
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J. Kaartinen, Hätönen, J., and Roine, T., Machine Vision of Flotation Froths with a Rapid-Prototyping Platform, in IFAC Workshop on Automation in Mining, Mineral and Metal Industry (IFACMMM2009), 2009.
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.
A. Karami, Heylen, R., and Scheunders, P., Band-specific Shearlet-based Hyperspectral Image Noise Reduction, IEEE Transaction Geosciences and Remote Sensing , vol. 53, no. 9, 2015.
A. Karami, Heylen, R., and Scheunders, P., Hyperspectral Image Noise Reduction and its Effect on Spectral Unmixing, in IEEE-Whispers 2014, Workshop on Hyperspectral Image and Signal Processing, Lausanne, Suisse, 2014.
A. Karami, M.Yazdi,, and Zolghadre, A., Best Rank-r Tensor Selection Using Genetic Algorithm for Better Noise Reduction and Compression of Hyperspectral Images, International Conference on Digital Information Management . 2010.
A. Karami, Heylen, R., and Scheunders, P., Lossy Compression of hyperspectral images optimizing spectral unmixing, in IEEE IGARSS 2015, International Geoscience and Remote Sensing Symposium, Milan, Italy, July 26-31, 2015, pp. 5031-034.
A. Karami, M.Rashidinejad,, and Gharaveisi, A. A., Coordination of UPFC & SVC for Voltage Security Enhancement, WSEAS Transactions on Circuits and Systems, vol. 5, no. 1, 2006.
A. Karami, M.Yazdi,, and Zolghadre, A., Hyperspectral Image Compression Based on Tucker Decomposition and Discrete Cosine Transform, International Conference on Image Processing Theory, Tools and Applications. 2010.
A. Karami, R.Heylen,, and Scheunders, P., Lossy Compression of Hyperspectral Images Optimizing Spectral Unmixing, in IGARSS 2015, Milan, Italy, 2015.
A. Karami, M.Yazdi,, and Zolghadre, A., Compression and Noise Reduction of Hyperspectral Images Using Hybrid Genetic Algorithm and Nonnegative Tucker Decomposition, International Journal of Information studies , vol. 2, no. 4, 2010.
A. Karami, M.Rashidinejad,, and Gharaveisi, A. A., Voltage Security Enhancement by Optimal FACTS Location via RGA, TPE conference. 2006.
A. Karami, Heylen, R., and Scheunders, P., Hyperspectral Image Compression Optimized for Spectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. pp, no. 99, 2016.
A. Karami, Heylen, R., and Scheunders, P., Hyperspectral Image Noise Reduction and its Effect on Spectral Unmixing, in IEEE-Whispers 2014, Workshop on Hyperspectral Image and Signal Processing, Lausanne, Suisse, 2014.
A. Karami, M.Yazdi,, and Mercier, G., Hyperspectral Image Compression based on Tucker Decomposition and Wavelet Transform, WHISPERS . Lisbon, Portugal, 2011.
A. Karami, Heylen, R., and Scheunders, P., Denoising Of Hyperspectral Images Using Shearlet Transform And Fully Constrained Least Squares Unmixing, in 8th workshop on Hyperspectral Image and Signal Processing : Evolution in Remote Sensing, Los Angeles, USA, 2016.
A. Karami, M.Yazdi,, and Mercier, G., Compression and Noise Reduction of Hyperspectral Images using Tucker Decomposition and Discrete Wavelet Transform, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 2, 2012.
A. Karami, M.Rashidinejad,, and Gharaveisi, A. A., Application of RGA to Optimal Choice and Allocation of UPFC for Voltage Security Enhancement in Deregulated Power System, WSEAS International Conference on Energy & Environmental Systems. 2006.
A. Karami, Beheshti, S., and M.Yazdi, Hyperspectral Image Compression Using 3d Discrete Cosine Transform and Support Vector Machine Learning, International Conference on Information Science, Signal Processing and their Applications . Montreal, Canada, 2012.

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