@article {2235,
	title = {Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model},
	journal = {NeuroImage},
	volume = {256},
	year = {2022},
	pages = {119219},
	doi = {https://doi.org/10.1016/j.neuroimage.2022.119219},
	author = {Vincenzo Anania and Quinten Collier and Jelle Veraart and Annemieke Eline Buikema and Floris Vanhevel and Thibo Billiet and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@article {1820,
	title = {Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach},
	journal = {Magnetic Resonance in Medicine},
	volume = {80},
	year = {2018},
	pages = {802-813},
	doi = {10.1002/mrm.27075},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Floris Vanhevel and Pim Pullens and Paul M Parizel and Arnold Jan den Dekker and Jan Sijbers}
}
@mastersthesis {1911,
	title = {Robust estimation of diffusion tensor and diffusion kurtosis imaging parameters},
	volume = {PhD in Sciences/Physics},
	year = {2018},
	month = {Oct/2018},
	school = {University of Antwerp},
	type = {PhD thesis},
	address = {Antwerp},
	author = {Quinten Collier}
}
@conference {1764,
	title = {Solving the Free Water Elimination Estimation Problem by Incorporating T2 Relaxation Properties},
	year = {2017},
	author = {Quinten Collier and Jelle Veraart and Arnold Jan den Dekker and Floris Vanhevel and Paul M Parizel and Jan Sijbers}
}
@article {1763,
	title = {Denoising of diffusion MRI using random matrix theory},
	journal = {NeuroImage},
	volume = {142},
	year = {2016},
	pages = {384-396},
	doi = {10.1016/j.neuroimage.2016.08.016},
	author = {Jelle Veraart and Dmitry S. Novikov and Christiaens Daan and Ades-Aron, Benjamin and Jan Sijbers and Els Fieremans}
}
@inbook {1673,
	title = {Diffusion Kurtosis Imaging},
	booktitle = { Diffusion Tensor Imaging: a practical handbook},
	year = {2016},
	pages = {407-418},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	chapter = {Diffusion Kurtosis Imaging},
	address = {New York},
	issn = {ISBN 978-1-4939-3118-7},
	doi = {10.1007/978-1-4939-3118-7},
	author = {Jelle Veraart and Jan Sijbers}
}
@article {1620,
	title = {Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination},
	journal = {NeuroImage},
	volume = {125},
	year = {2016},
	pages = {363{\textendash}377},
	doi = {10.1016/j.neuroimage.2015.10.052},
	author = {Caroline Guglielmetti and Jelle Veraart and Ella Roelant and Zhenhua Mai and Jasmijn Daans and Johan Van Audekerke and Maarten Naeyaert and Greetje Vanhoutte and Rafael  Delgado Y Palacios and Jelle Praet and Els Fieremans and Peter Ponsaerts and Jan Sijbers and Annemie Van Der Linden and Marleen Verhoye}
}
@article {1536,
	title = {Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations},
	journal = {Magnetic Resonance in Medicine},
	volume = {75},
	year = {2016},
	pages = {181-195},
	doi = {10.1002/mrm.25597},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/mrm.25597/abstract},
	author = {Gwendolyn Van Steenkiste and Ben Jeurissen and Jelle Veraart and Arnold Jan den Dekker and Paul M Parizel and Dirk H J Poot and Jan Sijbers}
}
@conference {1624,
	title = {CSF partial volume modeling in diffusion kurtosis imaging: a comparative parameter estimation study},
	year = {2015},
	month = {11/2015},
	doi = {10.3389/conf.fninf.2015.19.00039},
	url = {http://www.frontiersin.org/myfrontiers/events/abstractdetails.aspx?abs_doi=10.3389/conf.fninf.2015.19.00039},
	author = {Quinten Collier and Jelle Veraart and Arnold Jan den Dekker and Ben Jeurissen and Jan Sijbers}
}
@article {1604,
	title = {Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?},
	journal = {Journal of Alzheimer{\textquoteright}s Disease},
	volume = {48},
	number = {4},
	year = {2015},
	pages = {937-948},
	doi = {10.3233/JAD-150253},
	author = {Hanna Struyfs and Wim Van Hecke and Jelle Veraart and Jan Sijbers and Sylvie Slaets and Maya De Belder and Laura Wuyts and Benjamin Peters and Kristel Sleegers and Caroline Robberecht and Van Broeckhoven, Christine and Frank De Belder and Paul M Parizel and Sebastiaan Engelborghs}
}
@conference {1594,
	title = {Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone-induced demyelination and spontaneous remyelination},
	volume = {23},
	number = {4332},
	year = {2015},
	author = {Caroline Guglielmetti and Jelle Veraart and Ella Roelant and Zhenhua Mai and Jasmijn Daans and Johan Van Audekerke and Jelle Praet and Peter Ponsaerts and Jan Sijbers and Annemie Van Der Linden and Marleen Verhoye}
}
@conference {1597,
	title = {Gibbs ringing removal in diffusion MRI using second order total variation minimization},
	volume = {23},
	year = {2015},
	pages = {2809},
	author = {Jelle Veraart and Florian Knoll and Jan Sijbers and Els Fieremans and Dmitry S. Novikov}
}
@article {1492,
	title = {Iterative Reweighted Linear Least Squares for Accurate, Fast, and Robust Estimation of Diffusion Magnetic Resonance Parameters},
	journal = {Magnetic Resonance in Medicine},
	volume = {73},
	year = {2015},
	pages = {2174{\textendash}2184},
	abstract = {Purpose: Diffusion-weighted magnetic resonance imaging suffers from physiological noise, such as artifacts caused by motion or system instabilities. Therefore, there is a need for robust diffusion parameter estimation techniques. In the past, several techniques have been proposed, including RESTORE and iRESTORE. However, these techniques are based on nonlinear estimators and are consequently computationally intensive.
Method: In this work, we present a new, robust, iteratively reweighted linear least squares (IRLLS) estimator. IRLLS performs a voxel-wise identification of outliers in diffusion-weighted magnetic resonance images, where it exploits the natural skewness of the data distribution to become more sensitive to both signal hyperintensities and signal dropouts. 
Results: Both simulations and real data experiments were conducted to compare IRLLS with other state-of-the-art techniques. While IRLLS showed no significant loss in accuracy or precision, it proved to be substantially faster than both RESTORE and iRESTORE. In addition, IRLLS proved to be even more robust when considering the overestimation of the noise level or when the signal-to-noise ratio is low. 
Conclusion: The substantially shortened calculation time in combination with the increased robustness and accuracy, make IRLLS a practical and reliable alternative to current state-of-theart
techniques for the robust estimation of diffusion-weighted magnetic resonance parameters.},
	keywords = {diffusion tensor imaging, MRI, outlier detection, robust, weighted linear least squares},
	doi = {10.1002/mrm.25351},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1544,
	title = {Theoretical study of the free water elimination model},
	year = {2015},
	pages = {78},
	abstract = {Partial volume effects caused by cerebrospinal fluid are an important issue in diffusion MRI. In this work, we study the free water elimination model by analyzing the Cram{\'e}r-Rao lower bound (CRLB) of its parameters. We show that through optimizing the acquisition protocol by minimizing the trace of the CRLB, a significant gain in the precision of the parameter estimation can be achieved. Moreover, further analysis indicates that regularization and/or constraints are necessary for parameter estimation from voxels with large CSF fractions and/or low FA values. These theoretical findings are confirmed by both simulation and real data experiments.},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1545,
	title = {Theoretical study of the free water elimination model},
	volume = {23},
	year = {2015},
	pages = {2757},
	abstract = {Partial volume effects caused by cerebrospinal fluid are an important issue in diffusion MRI. In this work, we study the free water elimination model by analyzing the Cram{\'e}r-Rao lower bound (CRLB) of its parameters. We show that through optimizing the acquisition protocol by minimizing the trace of the CRLB, a significant gain in the precision of the parameter estimation can be achieved. Moreover, further analysis indicates that regularization and/or constraints are necessary for parameter estimation from voxels with large CSF fractions and/or low FA values. These theoretical findings are confirmed by both simulation and real data experiments.},
	author = {Quinten Collier and Jelle Veraart and Ben Jeurissen and Arnold Jan den Dekker and Jan Sijbers}
}
@conference {1617,
	title = {Post-processing of diffusion-weighted MR data lowers the accuracy of the weighted linear least squares estimator },
	volume = {22},
	year = {2014},
	pages = {2573},
	author = {Jelle Veraart and Jan Sijbers}
}
@article {1402,
	title = {Altered diffusion tensor imaging measurements in aged transgenic Huntington disease rats.},
	journal = {Brain structure \& function},
	volume = {218},
	year = {2013},
	month = {2013 May},
	pages = {767-78},
	abstract = {Rodent models of Huntington disease (HD) are valuable tools for investigating HD pathophysiology and evaluating new therapeutic approaches. Non-invasive characterization of HD-related phenotype changes is important for monitoring progression of pathological processes and possible effects of interventions. The first transgenic rat model for HD exhibits progressive late-onset affective, cognitive, and motor impairments, as well as neuropathological features reflecting observations from HD patients. In this report, we contribute to the anatomical phenotyping of this model by comparing high-resolution ex vivo DTI measurements obtained in aged transgenic HD rats and wild-type controls. By region of interest analysis supplemented by voxel-based statistics, we find little evidence of atrophy in basal ganglia regions, but demonstrate altered DTI measurements in the dorsal and ventral striatum, globus pallidus, entopeduncular nucleus, substantia nigra, and hippocampus. These changes are largely compatible with DTI findings in preclinical and clinical HD patients. We confirm earlier reports that HD rats express a moderate neuropathological phenotype, and provide evidence of altered DTI measures in specific HD-related brain regions, in the absence of pronounced morphometric changes.},
	issn = {1863-2661},
	doi = {10.1007/s00429-012-0427-0},
	author = {Antonsen, Bj{\o}rnar T and Yi Jiang and Jelle Veraart and Qu, Hong and Nguyen, Huu Phuc and Jan Sijbers and Von H{\"o}rsten, Stephan and Allan G Johnson and Trygve B Leergaard}
}
@article {1369,
	title = {Comprehensive framework for accurate diffusion MRI parameter estimation},
	journal = {Magnetic Resonance in Medicine},
	volume = {81},
	year = {2013},
	pages = {972-984},
	doi = {10.1002/mrm.24529},
	author = {Jelle Veraart and Jeny Rajan and Ron R Peeters and Alexander Leemans and Stefan Sunaert and Jan Sijbers}
}
@article {1377,
	title = {Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer{\textquoteright}s disease},
	journal = {Magnetic Resonance in Medicine},
	volume = {69},
	year = {2013},
	pages = {1115{\textendash}1121},
	doi = {10.1002/mrm.24680},
	author = {Greetje Vanhoutte and S. Pereson and Rafael  Delgado Y Palacios and Pieter-Jan Guns and B. Asselbergh and Jelle Veraart and Jan Sijbers and Marleen Verhoye and Van Broeckhoven, Christine and Annemie Van Der Linden}
}
@article {1361,
	title = {Does the use of hormonal contraceptives cause microstructural changes in cerebral white matter? Preliminary results of a DTI and tractography study.},
	journal = {European radiology},
	volume = {23},
	year = {2013},
	month = {2012 Jul 20},
	pages = {57-64},
	abstract = {OBJECTIVE: To evaluate the effect of monophasic combined oral contraceptive pill (COCP) and menstrual cycle phase in healthy young women on white matter (WM) organization using diffusion tensor imaging (DTI). METHODS: Thirty young women were included in the study; 15 women used COCP and 15 women had a natural cycle. All subjects underwent DTI magnetic resonance imaging during the follicular and luteal phase of their cycle, or in different COCP cycle phases. DTI parameters were obtained in different WM structures by performing diffusion tensor fibre tractography. Fractional anisotropy and mean diffusivity were calculated for different WM structures. Hormonal plasma concentrations were measured in peripheral venous blood samples and correlated with the DTI findings. RESULTS: We found a significant difference in mean diffusivity in the fornix between the COCP and the natural cycle group. Mean diffusivity values in the fornix were negatively correlated with luteinizing hormone and estradiol blood concentrations. CONCLUSION: An important part in the limbic system, the fornix, regulates emotional processes. Differences in diffusion parameters in the fornix may contribute to behavioural alternations related to COCP use. This finding also suggests that the use of oral contraceptives needs to be taken into account when designing DTI group studies. KEY POINTS: {\textbullet} Diffusion tensor MRI offers new insights into brain white matter microstructure. {\textbullet} The effects of oral hormonal contraception were examined in young women. {\textbullet} Diffusion tensor images and hormone blood concentrations were evaluated. {\textbullet} Women using hormonal contraception demonstrated higher mean diffusivity in the fornix. {\textbullet} These changes may contribute to behavioural alternations related to contraception use.},
	issn = {1432-1084},
	doi = {10.1007/s00330-012-2572-5},
	author = {De Bondt, Timo and Wim Van Hecke and Jelle Veraart and Alexander Leemans and Jan Sijbers and Stefan Sunaert and Jacquemyn, Yves and Paul M Parizel}
}
@conference {1426,
	title = {Iterative reweighted linear least squares for the accurate, fast, and robust estimation of diffusion magnetic resonance parameters},
	year = {2013},
	author = {Quinten Collier and Jelle Veraart and Jan Sijbers}
}
@mastersthesis {1427,
	title = {Optimal estimation of diffusion MRI parameters},
	volume = {PhD in Sciences: Physics},
	year = {2013},
	month = {10/2013},
	type = {PhD thesis},
	author = {Jelle Veraart}
}
@article {1396,
	title = {Subchronic memantine induced concurrent functional disconnectivity and altered ultra-structural tissue integrity in the rodent brain: revealed by multimodal MRI.},
	journal = {Psychopharmacology},
	volume = {227},
	year = {2013},
	month = {2013 Jun},
	pages = {479-91},
	abstract = {BACKGROUND: An effective NMDA antagonist imaging model may find key utility in advancing schizophrenia drug discovery research. We investigated effects of subchronic treatment with the NMDA antagonist memantine by using behavioural observation and multimodal MRI.

METHODS: Pharmacological MRI (phMRI) was used to map the neuroanatomical binding sites of memantine after acute and subchronic treatment. Resting state fMRI (rs-fMRI) and diffusion MRI were used to study the changes in functional connectivity (FC) and ultra-structural tissue integrity before and after subchronic memantine treatment. Further corroborating behavioural evidences were documented.

RESULTS: Dose-dependent phMRI activation was observed in the prelimbic cortex following acute doses of memantine. Subchronic treatment revealed significant effects in the hippocampus, cingulate, prelimbic and retrosplenial cortices. Decreases in FC amongst the hippocampal and frontal cortical structures (prelimbic, cingulate) were apparent through rs-fMRI investigation, indicating a loss of connectivity. Diffusion kurtosis MRI showed decreases in fractional anisotropy and mean diffusivity changes, suggesting ultra-structural changes in the hippocampus and cingulate cortex. Limited behavioural assessment suggested that memantine induced behavioural effects comparable to other NMDA antagonists as measured by locomotor hyperactivity and that the effects could be reversed by antipsychotic drugs.

CONCLUSION: Our findings substantiate the hypothesis that repeated NMDA receptor blockade with nonspecific, noncompetitive NMDA antagonists may lead to functional and ultra-structural alterations, particularly in the hippocampus and cingulate cortex. These changes may underlie the behavioural effects. Furthermore, the present findings underscore the utility and the translational potential of multimodal MR imaging and acute/subchronic memantine model in the search for novel disease-modifying treatments for schizophrenia.},
	issn = {1432-2072},
	doi = {10.1007/s00213-013-2966-3},
	author = {Sekar, S and Jonckers, E and Marleen Verhoye and Willems, R and Jelle Veraart and Johan Van Audekerke and Couto, J and Giugliano, M and Wuyts, K and Dedeurwaerdere, S and Jan Sijbers and Mackie, C and Ver Donck, L and Steckler, T and Annemie Van Der Linden}
}
@article {1328,
	title = {Super-Resolution for Multislice Diffusion Tensor Imaging},
	journal = {Magnetic Resonance in Medicine},
	volume = {69},
	year = {2013},
	pages = {103{\textendash}113},
	abstract = {Diffusion weighted (DW) magnetic resonance images are often recorded with single shot multislice
imaging sequences, because of their short scanning times and robustness to motion. To minimize
noise and acquisition time, images are generally acquired with either anisotropic or isotropic
low resolution voxels, which impedes subsequent posterior image processing and visualization. In
this paper, we propose a super-resolution method for diffusion weighted imaging that combines
anisotropic multislice images to enhance the spatial resolution of diffusion tensor (DT) data. Each
DW image is reconstructed from a set of arbitrarily oriented images with a low through-plane
resolution. The quality of the reconstructed DW images was evaluated by DT metrics and tractography.
Experiments with simulated data, a hardware DTI phantom, as well as in vivo human
brain data were conducted. Our results show a significant increase in spatial resolution of the DT
data while preserving high signal to noise ratio.},
	doi = {10.1002/mrm.24233},
	author = {Dirk H J Poot and Ben Jeurissen and Yannick Bastiaensen and Jelle Veraart and Wim Van Hecke and Paul M Parizel and Jan Sijbers}
}
@article {1397,
	title = {Weighted linear least squares estimation of diffusion MRI parameters: Strengths, limitations, and pitfalls.},
	journal = {NeuroImage},
	volume = {81},
	year = {2013},
	month = {2013 May 16},
	pages = {335-346},
	abstract = {PURPOSE: Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although adding proper weights is necessary to increase the precision of these linear estimators, there is no consensus on how to practically define them. In this study, the impact of the commonly used weighting strategies on the accuracy and precision of linear diffusion parameter estimators is evaluated and compared with the nonlinear least squares estimation approach. METHODS: Simulation and real data experiments were done to study the performance of the weighted linear least squares estimators with weights defined by (a) the squares of the respective noisy diffusion-weighted signals; and (b) the squares of the predicted signals, which are reconstructed from a previous estimate of the diffusion model parameters. RESULTS: The negative effect of weighting strategy (a) on the accuracy of the estimator was surprisingly high. Multi-step weighting strategies yield better performance and, in some cases, even outperformed the nonlinear least squares estimator. CONCLUSION: If proper weighting strategies are applied, the weighted linear least squares approach shows high performance characteristics in terms of accuracy/precision and may even be preferred over nonlinear estimation methods.},
	issn = {1095-9572},
	doi = {10.1016/j.neuroimage.2013.05.028},
	author = {Jelle Veraart and Jan Sijbers and Stefan Sunaert and Alexander Leemans and Ben Jeurissen}
}
@conference {1558,
	title = {{\textquotedblleft}The weighted linear least squares for estimating diffusion (kurtosis) tensors: Revisited},
	year = {2013},
	address = {Podstrana, Croatia},
	author = {Jelle Veraart and Jan Sijbers and Stefan Sunaert and Alexander Leemans and Ben Jeurissen}
}
@article {CampI.L.N.mverhoyejveraartwvheckeE.S.jsijbersA.avdlinde2011,
	title = {A complementary DTI-histological study in a model of Huntingtons disease},
	journal = {Neurobiology of Aging},
	volume = {33},
	number = {5},
	year = {2012},
	pages = {945-959},
	doi = {http://dx.doi.org/10.1016/j.neurobiolaging.2010.07.001},
	author = {N. Van Camp and Ines Blockx and L. Camon and N. de Vera and Marleen Verhoye and Jelle Veraart and Wim Van Hecke and E. Martinez and Guadelupe S. and Jan Sijbers and A. Planas and Annemie Van Der Linden}
}
@article {1304,
	title = {Diffusion kurtosis imaging in the grading of gliomas},
	journal = {Radiology},
	volume = {2},
	number = {263},
	year = {2012},
	pages = {492-501},
	doi = {10.1148/radiol.12110927},
	author = {Van Cauter, Sofie and Jelle Veraart and Jan Sijbers and Ron R Peeters and U. Himmelreich and S. Van Gool and Van Calenbergh, F. and De Vleeschouwer, S. and Wim Van Hecke and Stefan Sunaert}
}
@article {1349,
	title = {Identification and characterization of Huntington related pathology: an in vivo DKI imaging study},
	journal = {NeuroImage},
	volume = {63},
	year = {2012},
	month = {09/2012},
	pages = {653-662},
	doi = {http://dx.doi.org/10.1016/j.neuroimage.2012.06.032},
	author = {Ines Blockx and Marleen Verhoye and Johan Van Audekerke and Irene  Bergwerf and Jack X Kane and Rafael  Delgado Y Palacios and Jelle Veraart and Ben Jeurissen and Kerstin Raber and Von H{\"o}rsten, Stephan and Peter Ponsaerts and Jan Sijbers and Trygve B Leergaard and Annemie Van Der Linden}
}
@article {1438,
	title = {Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images.},
	journal = {Magnetic resonance imaging},
	volume = {30},
	year = {2012},
	month = {2012 Dec},
	pages = {1512-8},
	abstract = {Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method.},
	keywords = {Algorithms, Animals, Brain, Brain Mapping, Computer Simulation, Fourier Analysis, Image Processing, Computer-Assisted, Likelihood Functions, Magnetic Resonance Imaging, Mice, Models, Statistical, Normal Distribution, Signal-To-Noise Ratio, Stochastic Processes},
	issn = {1873-5894},
	doi = {10.1016/j.mri.2012.04.021},
	author = {Jeny Rajan and Jelle Veraart and Johan Van Audekerke and Marleen Verhoye and Jan Sijbers}
}
@article {1344,
	title = {Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images},
	journal = {Magnetic Resonance Imaging},
	volume = {30},
	year = {2012},
	pages = {1512-1518},
	doi = {10.1016/j.mri.2012.04.021},
	author = {Jeny Rajan and Jelle Veraart and Johan Van Audekerke and Marleen Verhoye and Jan Sijbers}
}
@article {jveraartwvheckejsijbers2011,
	title = {Constrained Maximum Likelihood Estimation of the Diffusion Kurtosis Tensor Using a Rician Noise Model},
	journal = {Magnetic Resonance in Medicine},
	volume = {66},
	number = {3},
	year = {2011},
	pages = {678-686},
	doi = {http://dx.doi.org/doi:10.1002/mrm.22835},
	author = {Jelle Veraart and Wim Van Hecke and Jan Sijbers}
}
@conference {jveraartwvheckedpootjsijbers2011,
	title = {Constrained maximum likelihood estimator for more accurate diffusion kurtosis tensor estimates},
	year = {2011},
	month = {January},
	address = {Hoeven, The Netherlands},
	author = {Jelle Veraart and Wim Van Hecke and Dirk H J Poot and Jan Sijbers}
}
@conference {R.jveraartG.H.mverhoyeP.jsijbersavdlinde2011,
	title = {Diffusion kurtosis abnormalities in pre-symptomatic (alpha)-synycleunopathy mouse model},
	year = {2011},
	month = {January},
	address = {Hoeven, The Netherlands},
	author = {Rafael  Delgado Y Palacios and Jelle Veraart and Greetje Vanhoutte and H. Schell and Marleen Verhoye and P. Kahle and Jan Sijbers and Annemie Van Der Linden}
}
@article {wvheckealeemansC.jveraartjsijbersS.2011,
	title = {The effect of template selection on diffusion tensor voxel based analysis results},
	journal = {NeuroImage},
	volume = {55},
	number = {2},
	year = {2011},
	pages = {566-573},
	author = {Wim Van Hecke and Alexander Leemans and Caroline A Sage and Jelle Veraart and Jan Sijbers and Stefan Sunaert}
}
@conference {1331,
	title = {An extended NLML method for denoising non-central chi distributed data - application to parallel MRI},
	year = {2011},
	pages = {41},
	author = {Jeny Rajan and Johan Van Audekerke and Jelle Veraart and Marleen Verhoye and Jan Sijbers}
}
@inproceedings {1942,
	title = {Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space},
	booktitle = {MICCAI 2011: Medical Image Computing and Computer-Assisted Intervention},
	year = {2011},
	pages = {166-173},
	author = {Thijs Dhollander and Jelle Veraart and Wim Van Hecke and F. Maes and Stefan Sunaert and Jan Sijbers and Paul Suetens}
}
@conference {S.jveraartjsijbersU.R.S.wvhecke2011,
	title = {Mean Kurtosis: a new potential biomarker for brain tumor grading},
	year = {2011},
	month = {January},
	address = {Hoeven, The Netherlands},
	author = {Van Cauter, Sofie and Jelle Veraart and Jan Sijbers and U. Himmelreich and Ron R Peeters and S. Van Gool and Wim Van Hecke}
}
@article {jveraartdpootwvheckeBlockxavdlindemverhoyejsijbers2011,
	title = {More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging},
	journal = {Magnetic Resonance in Medicine},
	volume = {65},
	number = {1},
	year = {2011},
	month = {January},
	pages = {138-145},
	doi = {10.1002/mrm.22603},
	author = {Jelle Veraart and Dirk H J Poot and Wim Van Hecke and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers}
}
@article {jveraartB.T.wvheckeI.bjeurissY.avdlindeA.mverhoyejsijbers2011,
	title = {Population-averaged diffusion tensor imaging atlas of the Sprague Dawley rat brain},
	journal = {NeuroImage},
	volume = {58},
	year = {2011},
	pages = {975-983},
	doi = {10.1016/j.neuroimage.2011.06.063},
	author = {Jelle Veraart and Trygve B Leergaard and Antonsen, Bj{\o}rnar T and Wim Van Hecke and Ines Blockx and Ben Jeurissen and Yi Jiang and Annemie Van Der Linden and Allan G Johnson and Marleen Verhoye and Jan Sijbers}
}
@conference {jveraartAntonsenBlockxwvheckeJiangJohnsonavdlindeLeergaardmverhoyejsijbers2010,
	title = {Construction of a population based diffusion tensor image atlas of the Sprague Dawley rat brain},
	year = {2010},
	month = {May},
	address = {Stockholm, Sweden},
	author = {Jelle Veraart and Antonsen, Bj{\o}rnar T and Ines Blockx and Wim Van Hecke and Yi Jiang and Allan G Johnson and Annemie Van Der Linden and Trygve B Leergaard and Marleen Verhoye and Jan Sijbers}
}
@conference {jveraartwvheckedpootBlockxavdlindemverhoyejsijbers2010,
	title = {A more accurate and b-value independent estimation of diffusion parameters using Diffusion Kurtosis Imaging,},
	year = {2010},
	month = {May},
	address = {Stockholm, Sweden},
	author = {Jelle Veraart and Wim Van Hecke and Dirk H J Poot and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers}
}
@conference {jveraartwvheckedpootBlockxavdlindemverhoyejsijbers2010,
	title = {A more accurate and b-value independent estimation of diffusion parameters using Diffusion Kurtosis Imaging},
	year = {2010},
	month = {January},
	pages = {10},
	address = {Utrecht, the Netherlands},
	author = {Jelle Veraart and Wim Van Hecke and Dirk H J Poot and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers}
}
@inproceedings {jveraartwvheckeBlockxavdlindemverhoyejsijbers2010,
	title = {Non-Rigid coregistration of diffusion kurtosis data},
	booktitle = {Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on},
	year = {2010},
	month = {April},
	pages = {392-395},
	address = {Rotterdam, the Netherlands},
	author = {Jelle Veraart and Wim Van Hecke and Ines Blockx and Annemie Van Der Linden and Marleen Verhoye and Jan Sijbers}
}
@conference {jveraartBlockxwvheckemverhoyeavdlindejsijbers2009,
	title = {Improved non rigid coregistration of diffusion kurtosis images by incorporating diffusion kurtosis tensor information},
	year = {2009},
	month = {October},
	pages = {36},
	address = {Antalya, Turkey},
	author = {Jelle Veraart and Ines Blockx and Wim Van Hecke and Marleen Verhoye and Annemie Van Der Linden and Jan Sijbers}
}
