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Magnetic Resonance Imaging

Magnetic resonance imaging and derived modalities.

A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images

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.

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Optimal experimental design for Diffusion Kurtosis Imaging

D. H. J. Poot, den Dekker, A. J., Achten, E., Verhoye, M., and Sijbers, J., “Optimal experimental design for Diffusion Kurtosis Imaging”, IEEE Transactions on Medical Imaging, vol. 29, pp. 819-829, 2010.

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Quantitative Evaluation of 10 Tractography Algorithms on a Realistic Diffusion MR Phantom

P. Fillard, Descoteaux, M., Goh, A., Gouttard, S., Jeurissen, B., Malcolm, J., Ramirez-Manzanares, A., Reisert, M., Sakaie, K., Tensaouti, F., Yo, T. - S., Mangin, J. - F., and Poupon, C., “Quantitative Evaluation of 10 Tractography Algorithms on a Realistic Diffusion MR Phantom”, NeuroImage, vol. 56, pp. 220-234, 2011.

Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis

A. Smolders, Martino, D. F., Staeren, N., Scheunders, P., Sijbers, J., Goebel, R., and Formisano, E., “Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis”, Magnetic Resonance Imaging, vol. 25, pp. 860-868, 2007.

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Automatic estimation of the noise variance from the histogram of a magnetic resonance image

J. Sijbers, Poot, D. H. J., den Dekker, A. J., and Pintjens, W., “Automatic estimation of the noise variance from the histogram of a magnetic resonance image”, Physics in Medicine and Biology, vol. 52, pp. 1335-1348, 2007.

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Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study

W. Van Hecke, Leemans, A., De Backer, S., Jeurissen, B., Parizel, P. M., and Sijbers, J., “Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study”, Human Brain Mapping, vol. 31, pp. 98-114, 2010.

Improved B0 field map estimation for high field EPI

D. H. J. Poot, Pintjens, W., Verhoye, M., Van Der Linden, A., and Sijbers, J., “Improved B0 field map estimation for high field EPI”, Magnetic Resonance Imaging, vol. 28, pp. 441-450, 2010.

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On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods

W. Van Hecke, Sijbers, J., De Backer, S., Poot, D. H. J., Parizel, P. M., and Leemans, A., “On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods”, NeuroImage, vol. 46, pp. 692-707, 2009.

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Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study

A. J. den Dekker, Poot, D. H. J., Bos, R., and Sijbers, J., “Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study”, IEEE Transactions on Medical Imaging, vol. 28, pp. 287-296, 2009.

On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain

W. Van Hecke, Sijbers, J., D'Agostino, E., Maes, F., De Backer, S., Vandervliet, E., Parizel, P. M., and Leemans, A., “On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain”, NeuroImage, vol. 43, pp. 69-80, 2008.

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