Magnetic Resonance Imaging

Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks

T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Sijbers, J., and Leemans, A., “Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks”, Medical Image Analysis, vol. 52, pp. 56-67, 2019.

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Brain Tissue–Volume Changes in Cosmonauts

A. Van Ombergen, Jillings, S., Jeurissen, B., Tomilovskaya, E., Rühl, M., Rumshiskaya, A., Nosikova, I., Litvinova, L., Annen, J., Pechenkova, E. V., Kozlovskaya, I. B., Sunaert, S., Parizel, P. M., Sinitsyn, V., Laureys, S. S. L., Sijbers, J., Eulenburg, Pzu, and Wuyts, F. L., “Brain Tissue–Volume Changes in Cosmonauts”, New England Journal of Medicine, vol. 379, no. 17, pp. 1678 - 1680, 2018.

A three-dimensional digital neurological atlas of the mustached bat (Pteronotus parnellii)

S. D. Washington, Hamaide, J., Jeurissen, B., Van Steenkiste, G., Huysmans, T., Sijbers, J., Deleye, S., Kanwal, J. S., De Groof, G., Liang, S., Van Audekerke, J., Wenstrup, J. J., Van Der Linden, A., Radtke-Schuller, S., and Verhoye, M., “A three-dimensional digital neurological atlas of the mustached bat (Pteronotus parnellii)”, NeuroImage, vol. 183, pp. 300-313, 2018.

Modeling brain dynamics in brain tumor patients using The Virtual Brain

H. Aerts, Schirner, M., Jeurissen, B., Van Roost, D., Achten, E., Ritter, P., and Marinazzo, D., “Modeling brain dynamics in brain tumor patients using The Virtual Brain”, eNeuro, 2018.

NOVIFAST: A fast algorithm for accurate and precise VFA MRI T1 mapping

G. Ramos-Llordén, Vegas-Sánchez-Ferrero, G., Björk, M., Vanhevel, F., Parizel, P. M., Estépar, R. San José, den Dekker, A. J., and Sijbers, J., “NOVIFAST: A fast algorithm for accurate and precise VFA MRI T1 mapping”, IEEE Transactions on Medical Imaging, vol. 37, no. 11, pp. 2414 - 2427, 2018.

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NOVIFAST

In quantitative magnetic resonance T1 mapping, the Variable Flip Angle (VFA) steady state spoiled gradient recalled echo (SPGR) imaging technique is popular as it provides a series of high resolution T1 weighted images in a clinically feasible time. Fast, linear methods that estimate T1 maps from these weighted images have been proposed, such as DESPOT1 and iterative reweighted linear least squares (IRWLLS).

Improved MRI Relaxometry through Statistical Signal Processing

G. Ramos-Llordén, “Improved MRI Relaxometry through Statistical Signal Processing”, University of Antwerp, Antwerp, 2018.

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An educational presentation on accurate and precise MRI relaxometry: the often disregarded but critical role of statistical parameter estimation

G. Ramos-Llordén, Beirinckx, Q., den Dekker, A. J., and Sijbers, J., “An educational presentation on accurate and precise MRI relaxometry: the often disregarded but critical role of statistical parameter estimation”, 10th Annual Meeting of the ISMRM Benelux Chapter. Antwerp, Belgium, 2018.

Accurate and precise MRI relaxometry: the often disregarded but critical role of statistical parameter estimation

G. Ramos-Llordén, Beirinckx, Q., den Dekker, A. J., and Sijbers, J., “Accurate and precise MRI relaxometry: the often disregarded but critical role of statistical parameter estimation”, Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), 26th Annual Meeting. Paris, France, p. 5664, 2018.

Super-resolution multi-PLD PCASL: a simulation study

P. Bladt, Beirinckx, Q., Van Steenkiste, G., Jeurissen, B., Achten, E., den Dekker, A. J., and Sijbers, J., “Super-resolution multi-PLD PCASL: a simulation study”, 34th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology (ESMRMB), Barcelona, Spain, vol. 30 (Suppl. 1). Magn Reson Mater Phy, 2017.

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