Publications

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S. Jillings, Pechenkova, E. V., Tomilovskaya, E., Rukavishnikov, I., Jeurissen, B., Van Ombergen, A., Nosikova, I., Rumshiskaya, A., Litvinova, L., Annen, J., De Laet, C., Schoenmaekers, C., Sijbers, J., Petrovichev, V., Sunaert, S., Parizel, P. M., Sinitsyn, V., P Eulenburg, zu, Laureys, S. S. L., Demertzi, A., and Wuyts, F. L., Prolonged microgravity induces reversible and persistent changes on human cerebral connectivity, Communications Biology, vol. 6, no. 46, 2023.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Laureys, S., P Eulenburg, zu, Sunaert, S., Sijbers, J., Wuyts, F. L., and Jeurissen, B., Diffusion-weighted imaging reveals structural brain changes in cosmonauts after long-duration spaceflight, 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology, Rotterdam, The Netherlands, vol. 32 (Suppl. 1). p. Magn Reson Mater Phy. 2019; 32(Suppl. 1):S101, 2019.
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., 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.
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, 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, 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)
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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., 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.
A. Karami, M.Yazdi,, and Zolghadre, A., Noise Reduction of Hyperspectral Images Using Kernel Nonnegative Tucker Decomposition, IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 3, 2011.
A. Karami, M.Rashidinejad,, and Gharaveisi, A. A., Optimal Location of STATCOM for Voltage Security Enhancement via Artificial Intelligent, IEEE Conference,ICIT. 2006.
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.

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