Log in

Magnetic Resonance Imaging

Magnetic resonance imaging and derived modalities.

Recurrent Inference Machines as inverse problem solvers for MR relaxometry

E. Ribeiro Sabidussi, Klein, S., Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., “Recurrent Inference Machines as inverse problem solvers for MR relaxometry”, Medical Image Analysis, vol. 74, pp. 1-11, 2021.

Files:

Multi-contrast multi-shot EPI for accelerated diffusion MRI

B. Shafieizargar, Jeurissen, B., Poot, D. H. J., den Dekker, A. J., and Sijbers, J., “Multi-contrast multi-shot EPI for accelerated diffusion MRI”, in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021, pp. 3869-3872.

Outcome prediction of mild traumatic brain injury using support vector machine based on longitudinal MRdiffusion imaging from CENTER-TBI

M. Siqueira Pinto, Winzeck, S., Richter, S., Correia, M. M., Kornaropoulos, E. N., Menon, D. K., Glocker, B., Guns, P. - J., den Dekker, A. J., Sijbers, J., Newcombe, V. F. J., and Van Dyck, P., “Outcome prediction of mild traumatic brain injury using support vector machine based on longitudinal MRdiffusion imaging from CENTER-TBI”, Magn Reson Mater Phy (ESMRMB), vol. 34. p. S54, 2021.

Accelerated multi-shot diffusion weighted imaging with joint estimation of diffusion and phase parameters

B. Shafieizargar, Jeurissen, B., Poot, D. H. J., Van Audekerke, J., Verhoye, M., den Dekker, A. J., and Sijbers, J., “Accelerated multi-shot diffusion weighted imaging with joint estimation of diffusion and phase parameters”, Magn Reson Mater Phy, vol. 34. pp. S57-S58, 2021.

EPIFANI for ultrafast B1-corrected T1 and PD mapping

M. A. Zampini, Sijbers, J., Verhoye, M., and Garipov, R., “EPIFANI for ultrafast B1-corrected T1 and PD mapping”, Magn Reson Mater Phy, vol. 34. pp. S59-S60, 2021.

Optimal experimental design for the T2-weighted diffusion kurtosis imaging free water elimination model

V. Anania, Jeurissen, B., Morez, J., Buikema, A. Eline, Billiet, T., Sijbers, J., and den Dekker, A. J., “Optimal experimental design for the T2-weighted diffusion kurtosis imaging free water elimination model”, ESMRMB 2021 Online 38th Annual Scientific Meeting 7–9 October 2021. Magn Reson Mater Phy, vol. 34. pp. S54-S55, 2021.

Rotated or shifted sets of multi-slice MR images for super-resolution reconstruction? A Bayesian answer

M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., “Rotated or shifted sets of multi-slice MR images for super-resolution reconstruction? A Bayesian answer”, Magn Reson Mater Phy (ESMRMB), vol. 34. pp. S56-S57, 2021.

Decoding Multiple Sclerosis EDSS disability scores from MRI using Deep Learning

R. Paolella, de la Rosa, E., Sima, D. M., Dive, D., Durand-Dubief, F., Sappey-Marinier, D., Jeurissen, B., Sijbers, J., and Billiet, T., “Decoding Multiple Sclerosis EDSS disability scores from MRI using Deep Learning”, 38th Annual Scientific Meeting Congress of the European Society for Magnetic Resonance in Medicine and Biology, vol. 34. pp. S57-S58, 2021.

On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge

A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.

Outcome prediction in Mild Traumatic Brain Injury patients using conventional and diffusion MRI via Support Vector Machine: A CENTER-TBI study

M. Siqueira Pinto, Winzeck, S., Correia, M. M., Kornaropoulos, E. N., Menon, D. K., Glocker, B., den Dekker, A. J., Sijbers, J., Guns, P. - J., Van Dyck, P., and Newcombe, V. F. J., “Outcome prediction in Mild Traumatic Brain Injury patients using conventional and diffusion MRI via Support Vector Machine: A CENTER-TBI study”, ISMRM & SMRT Annual Meeting. 2021.

Pages