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J. Morez, Sijbers, J., and Jeurissen, B., “Optimal experimental design for multi-tissue spherical deconvolution of diffusion MRI”, Proc Intl Soc Mag Reson Med 28. p. 4321, 2020.
J. Morez, Sijbers, J., and Jeurissen, B., “Spherical Deconvolution of Non-Spherically Sampled Diffusion MRI Data”, International Society for Magnetic Resonance in Medicine. 2017.
J. Morez, Sijbers, J., and Jeurissen, B., “Spherical Deconvolution of Non-Spherically Sampled Diffusion MRI Data”, Proc. Intl. Soc. Mag. Reson. Med. 25. p. 66, 2017.
J. Morez, Sijbers, J., and Jeurissen, B., “A comparison of response function tensor models for multi-tissue spherical deconvolution”, 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology, Rotterdam, The Netherlands, vol. 32 (Suppl. 1). pp. S138–S139, 2019.
J. Morez, Szczepankiewicz, F., den Dekker, A. J., Vanhevel, F., Sijbers, J., and Jeurissen, B., “Optimal experimental design and estimation for q-space trajectory imaging”, Human Brain Mapping, vol. 44, no. 4, pp. 1793-1809, 2023.PDF icon Download paper (5.87 MB)
J. Morez, Sijbers, J., Vanhevel, F., and Jeurissen, B., “Constrained spherical deconvolution of non-spherically sampled diffusion MRI data”, Human Brain Mapping, vol. 42, pp. 521–538, 2020.PDF icon Download paper (5.87 MB)
M. Mohammadian, Roine, T., Hirvonen, J., Kurki, T., Ala-Seppälä, H., Frantzén, J., Katila, A., Kyllönen, A., Maanpää, H. - R., Posti, J., Takala, R., Tallus, J., and Tenovuo, O., “High angular resolution diffusion-weighted imaging in mild traumatic brain injury”, NeuroImage: Clinical, vol. 13, pp. 174 - 180, 2017.PDF icon Download paper (848.3 KB)
P. Mishra, Asaari, M. Shahrimie, Mertens, S., Wuyts, N., Dhondt, S., and Scheunders, P., “Close range hyperspectral imaging for plant phenotyping”, in Hyperspectral Imaging and Applications Conference, Coventry, UK, 2016.
I. Michiels, Sijbers, J., Eelen, J., Verhoye, M., Dhooghe, R., Nagels, G., De Deyn, P. P., and Van Der Linden, A., “Simultaneous EEG and MRI in an animal model for generalized epilepsy induced in the MRI instrument”, in 16th annual meeting: Magnetic Resonance Materials in Physics, Biology, and Medicine, Sevilla, Spain, 1999.
I. Michiels, Sijbers, J., Eelen, J., Verhoye, M., Dhooghe, R., Nagels, G., De Deyn, P. P., and Van Der Linden, A., “Simultaneous EEG and MRI in an animal model for generalized epilepsy induced in the MRI instrument”, in Third Meeting of the Belgian Society for Neuroscience, Brussels, Belgium, 1999.
K. Meuleman, Coppin, P., De Backer, S., Debruyn, W., Nackaerts, K., Scheunders, P., and Sterckx, S., “Optimal hyperspectral indicators for stress detection in orchards”, in Proc. Earsel 2003, Imaging Spectroscopy workshop Oberpfaffenhofen, 2003, pp. 534-541.
J. Merckx, den Dekker, A. J., De Beenhouwer, J., and Sijbers, J., “Fast and efficient tetrahedral volume mesh reconstruction with CAD-ASTRA”, in SPIE Developments in X-Ray Tomography XV, San Diego, USA, 2024, vol. 13152.
J. Merckx, van Lith, B., Sijbers, J., and De Beenhouwer, J., “Adaptive triangular mesh for phase contrast imaging”, 5th international Conference on Tomography of Materials & Structures, 27the June - 1ste July, Grenoble, France. 2022.
Z. Jiang, Liang, Z., Das, M., and Gifford, H. C., “SPIE ProceedingsTowards using eye-tracking data to develop visual-search observers for x-ray breast imaging”, in SPIE Medical ImagingMedical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, Orlando, Florida, United States, 2015, vol. 9416, p. 94160V.
O. Melet, Huysmans, T., Hummel, M., and Brunet, P. - M., “GPGPU and MIC in accelerated cluster for remote sensed image processing software”, in Conference on Big Data from Space (BiDS), 12-14 November, ESRIN, Frascati, Italy, 2014.PDF icon paper (158.32 KB)
D. Meersman, Scheunders, P., and Van Dyck, D., “Detection of microcalcifications using non-linear filtering”, in Proc. EUSIPCO'98, European Signal Processing Conference, 1998, pp. 2465-2468.
D. Meersman, Scheunders, P., and Van Dyck, D., “Detection of microcalcifications using neural networks”, in Digital Mammography, 1996, pp. 287-290.
D. Meersman, Scheunders, P., and Van Dyck, D., “Classification of microcalcifications using texture-based features”, in Digital Mammography, 1998, pp. 233-236.
Á. Marinovszki, De Beenhouwer, J., and Sijbers, J., “An efficient CAD projector for X-ray projection based 3D inspection with the ASTRA Toolbox”, in 8th Conference on Industrial Computed Tomography, Wels, Austria, 2018.PDF icon Download paper (364.16 KB)
S. Manhaeve, Van Nieuwenhove, V., and Sijbers, J., “Performance and memory use trade-off in CPU and GPU implementations of a deformation operator for 4D-CT”, in 8th Conference on Industrial Computed Tomography, Wels, Austria, 2018.
Z. Mai, “Advances in the quality and resolution improvement of Magnetic Resonance images”, 2012.
Z. Mai, Verhoye, M., Van Der Linden, A., and Sijbers, J., “Diffusion tensor image up-sampling: a registration-based approach”, Magnetic resonance Imaging, vol. 28, pp. 1497-1506, 2010.PDF icon Download paper (814.96 KB)
Z. Mai, Huysmans, T., and Sijbers, J., “Colon Visualization Using Cylindrical Parameterization”, Lecture Notes in Computer Science, vol. 4678, pp. 607-615, 2007.PDF icon Full text (1.44 MB)
Z. Mai, Rajan, J., Verhoye, M., and Sijbers, J., “Robust edge directed interpolation of diffusion weighted MR images”, ESMRMB Congress 28th Annual Scientific Meeting. p. 382, 2011.
Z. Mai, Verhoye, M., and Sijbers, J., “Diffusion Tensor Images Edge-Directed Interpolation”, in International Symposium on Biomedical Imaging 2010, 2010, pp. 732-735.

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