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Magnetic Resonance Imaging

Magnetic resonance imaging and derived modalities.

Statistically optimal separation of multi-component MR signals with a Majorize-Minimize approach: application to MWF estimation

G. Ramos-Llordén, den Dekker, A. J., Bladt, P., Cuyt, A., and Sijbers, J., “Statistically optimal separation of multi-component MR signals with a Majorize-Minimize approach: application to MWF estimation”, 34th annual scientific meeting of the ESMRMB. 2017.

Diffusion MRI fiber tractography of the brain

B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., “Diffusion MRI fiber tractography of the brain”, NMR in Biomedicine, 2019.

The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density

F. Calamante, Jeurissen, B., Smith, R. E., Tournier, J. - D., and Connelly, A., “The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density”, Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2738–2744, 2018.

Spherical Deconvolution of Non-Spherically Sampled Diffusion MRI Data

J. Morez, Sijbers, J., and Jeurissen, B., “Spherical Deconvolution of Non-Spherically Sampled Diffusion MRI Data”, International Society for Magnetic Resonance in Medicine. 2017.

Improved reliability of fiber orientation estimation and graph theoretical analysis of structural brain networks with diffusion MRI

T. Roine, “Improved reliability of fiber orientation estimation and graph theoretical analysis of structural brain networks with diffusion MRI”, University of Antwerp, 2017.

A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps

P. V. Sudeep, Palanisamy, P., Kesavadas, C., Sijbers, J., den Dekker, A. J., and Rajan, J., “A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps”, Signal Image and Video Processing, vol. 11, no. 5, pp. 913-920, 2017.

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging

J. Hamaide, De Groof, G., Van Steenkiste, G., Jeurissen, B., Van Audekerke, J., Naeyaert, M., Van Ruijssevelt, L., Cornil, C., Sijbers, J., Verhoye, M., and Van Der Linden, A., “ Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging”, NeuroImage, vol. 146, pp. 789-803, 2017.

Solving the Free Water Elimination Estimation Problem by Incorporating T2 Relaxation Properties

Q. Collier, Veraart, J., den Dekker, A. J., Vanhevel, F., Parizel, P. M., and Sijbers, J., “Solving the Free Water Elimination Estimation Problem by Incorporating T2 Relaxation Properties”, International Society of Magnetic Resonance in Medicine. 2017.

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Denoising of diffusion MRI using random matrix theory

J. Veraart, Novikov, D. S., Daan, C., Ades-Aron, B., Sijbers, J., and Fieremans, E., “Denoising of diffusion MRI using random matrix theory”, NeuroImage, vol. 142, pp. 384-396, 2016.

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