@article {2232,
	title = {Multi-tissue spherical deconvolution of tensor-valued diffusion MRI.},
	journal = {Neuroimage},
	volume = {245},
	year = {2021},
	month = {2021 12 15},
	pages = {118717},
	abstract = {Multi-tissue constrained spherical deconvolution (MT-CSD) leverages the characteristic b-value dependency of each tissue type to estimate both the apparent tissue densities and the white matter fiber orientation distribution function from diffusion MRI data. In this work, we generalize MT-CSD to tensor-valued diffusion encoding with arbitrary b-tensor shapes. This enables the use of data encoded with mixed b-tensors, rather than being limited to the subset of linear (conventional) b-tensors. Using the complete set of data, including all b-tensor shapes, provides a categorical improvement in the estimation of apparent tissue densities, fiber ODF, and resulting tractography. Furthermore, we demonstrate that including multiple b-tensor shapes in the analysis provides improved contrast between tissue types, in particular between gray matter and white matter. We also show that our approach provides high-quality apparent tissue density maps and high-quality fiber tracking from data, even with sparse sampling across b-tensors that yield whole-brain coverage at 2~mm isotropic resolution in approximately 5:15~min.},
	keywords = {Brain Mapping, diffusion tensor imaging, Healthy Volunteers, Humans, Image Processing, Computer-Assisted, white matter},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2021.118717},
	author = {Ben Jeurissen and Szczepankiewicz, Filip}
}
@mastersthesis {1337,
	title = {Improved analysis of brain connectivity using high angular resolution diffusion MRI},
	volume = {PhD in Sciences},
	year = {2012},
	month = {03/2012},
	pages = {208},
	school = {University of Antwerp},
	type = {PhD thesis},
	keywords = {complex WM architecture, constrained spherical deconvolution, crossing fibers, CSD, Diffusion MRI, diffusion tensor imaging, DTI, HARDI, high angular resolution diffusion imaging, Magnetic Resonance Imaging, MRI, probabilistic tractography, Spherical deconvolution, Tractography, white matter, WM},
	author = {Ben Jeurissen}
}
@conference {Kudzinava_2011_WMSG,
	title = {Diffusion and kurtosis parameters in white matter of premature newborns},
	year = {2011},
	month = {August},
	pages = {21},
	address = {Reykjavik, Iceland},
	abstract = {Diffusion Tensor Imaging (DTI) is often used to study brain maturation processes and white matter (WM) injuries in premature newborns. However, DTI assumes that water diffusion in biological tissues is free. In reality, there is always structural hindrance in WM, which only increases with age due to myelination. Diffusional Kurtosis Imaging (DKI) relaxes the assumption of free diffusion and allows estimation of conventional diffusion parameters plus new kurtosis measures, which are related to tissue complexity. In this work, we present and discuss the first statistics of DKI parameters in WM of two prematurely born infants.},
	keywords = {anisotropy, diffusion, kurtosis, premature newborns, white matter},
	author = {Maryna Kudzinava and A. Plaisier and J. Dudink and Jan Sijbers}
}
