Dr Chantal Tax

2025

• Verschuur, A. S. et al. 2025. Trends in term-equivalent age brain volumes in infants born across the gestational age spectrum. Children 12, article number: 1026. (10.3390/children12081026)
• Schilling, K. G. et al. 2025. White matter geometry confounds Diffusion Tensor Imaging Along Perivascular Space (DTI‐ALPS) measures. Human Brain Mapping 46(10), article number: e70282. (10.1002/hbm.70282)
• Arends, G. C. et al. 2025. Feasibility of strong diffusion encoding and fast readout using a plug‐and‐play head gradient insert at 7 T. Magnetic Resonance in Medicine (10.1002/mrm.30613)
• Verschuur, A. S. et al. 2025. Diffusion MRI tractography with along-tract profiling reveals subtle neurodevelopmental differences between moderate and late preterm infants.. European Journal of Radiology 187, article number: 112098. (10.1016/j.ejrad.2025.112098)
• Schilling, K. G. et al. 2025. The relationship of white matter tract orientation to vascular geometry in the human brain. Scientific Reports 15(1), article number: 18396. (10.1038/s41598-025-99724-z)
• Genc, S. et al. 2025. MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression. Nature Communications 16, article number: 3317. (10.1038/s41467-025-58604-w)
• Molendowska, M., Mueller, L., Fasano, F., Jones, D. K., Tax, C. and Engel, M. 2025. Giving the prostate the boost it needs: Spiral diffusion MRI using a high-performance whole-body gradient system for high b-values at short echo times. Magnetic Resonance in Medicine 93(3), pp. 1256-1272. (10.1002/mrm.30351)
• Verschuur, A. S., King, R., Tax, C. M. W., Boomsma, M. F., van Wezel-Meijler, G., Leemans, A. and Leijser, L. M. 2025. Methodological considerations on diffusion MRI tractography in infants aged 0-2 years: a scoping review. Pediatric Research 97, pp. 880-897. (10.1038/s41390-024-03463-2)
• Canales-Rodríguez, E. J., Tax, C. M. W., Fischi-Gomez, E., Jones, D. K., Thiran, J. and Rafael-Patiño, J. 2025. A diffusion MRI model for random walks confined on cylindrical surfaces: towards non-invasive quantification of myelin sheath radius. Frontiers in Physics 13, article number: 1516630. (10.3389/fphy.2025.1516630)

2024

• Fokkinga, E., Hernandez-Tamames, J. A., Ianus, A., Nilsson, M., Tax, C. M. W., Perez-Lopez, R. and Grussu, F. 2024. Advanced diffusion-weighted MRI for cancer microstructure assessment in body imaging, and its relationship with histology. Journal of Magnetic Resonance Imaging 60(4), pp. 1278-1304. (10.1002/jmri.29144)
• Genc, S., Schiavi, S., Chamberland, M., Tax, C. M., Raven, E. P., Daducci, A. and Jones, D. K. 2024. Developmental differences in canonical cortical networks: insights from microstructure-informed tractography. Network Neuroscience 8(3), pp. 946-964. (10.1162/netn_a_00378)
• MacIver, C. L., Jones, D., Green, K., Szewczyk-Krolikowski, K., Doring, A., Tax, C. M. and Peall, K. J. 2024. White matter microstructural changes using ultra-strong diffusion gradient MRI in adult-onset idiopathic focal cervical dystonia. Neurology 103(4), article number: e209695. (10.1212/WNL.0000000000209695)
• Molendowska, M. et al. 2024. Diffusion MRI in prostate cancer with ultra-strong whole body gradients. NMR in Biomedicine (10.1002/nbm.5229)
• Verschuur, A. S. et al. 2024. Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data. Frontiers in Radiology 4, article number: 1416672. (10.3389/fradi.2024.1416672)
• Planchuelo-Gómez, ?., Descoteaux, M., Larochelle, H., Hutter, J., Jones, D. K. and Tax, C. M. 2024. Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning. Medical Image Analysis 94, article number: 103134. (10.1016/j.media.2024.103134)
• Ligneul, C. et al. 2024. Diffusion‐weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling. Magnetic Resonance in Medicine 91(3), pp. 860-885. (10.1002/mrm.29877)

2023

• Davies Jenkins, C. W. et al. 2023. Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients. Frontiers in Neuroscience 17, article number: 1258408. (10.3389/fnins.2023.1258408)
• MacIver, C. et al. 2023. Macro- and micro-structural Insights into primary dystonia A UK Biobank study. Journal of Neurology (10.1007/s00415-023-12086-2)
• Kleban, E., Jones, D. and Tax, C. 2023. The impact of head orientation with respect to B0 on diffusion tensor MRI measures. Imaging Neuroscience 1, pp. 1-17. (10.1162/imag_a_00012)
• Barakovic, M. et al. 2023. Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology. Frontiers in Neuroscience 17, article number: 1209521. (10.3389/fnins.2023.1209521)
• Tax, C. M. W. et al. 2023. Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders. NeuroImage: Clinical 38, article number: 103419. (10.1016/j.nicl.2023.103419)
• Soliman, R. K., Tax, C. M., Abo-Elfetoh, N., Zaitoun, M. M. and Khedr, E. M. 2023. Constrained spherical deconvolution -based tractography of major language tracts reveals post-stroke bilateral white matter changes correlated to aphasia.. Magnetic Resonance Imaging 95, pp. 19-26. (10.1016/j.mri.2022.10.004)

2022

• MacIver, C. L., Tax, C. M. W., Jones, D. K. and Peall, K. J. 2022. Structural magnetic resonance imaging in dystonia: A systematic review of methodological approaches and findings. European Journal of Neurology 29(11), pp. 3418-3448. (10.1111/ene.15483)
• Shastin, D. et al. 2022. Surface-based tracking for short association fibre tractography. NeuroImage 260, article number: 119423. (10.1016/j.neuroimage.2022.119423)
• Fan, Q. et al. 2022. Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: methodological advances and scientific impact. NeuroImage 254, article number: 118958. (10.1016/j.neuroimage.2022.118958)
• Molendowska, M. et al. 2022. Physiological effects of human body imaging with 300 mT/m gradients. Magnetic Resonance in Medicine 87(5), pp. 2512-2520. (10.1002/mrm.29118)
• Verschuur, A. et al. 2022. Improved segmentation of neonatal brain MRI scans by addressing motion artifacts with data interpolation. Presented at: Proceedings of the 13th International Newborn Brain Conference: Neuro-imaging studies, 10-12/02/2022. IOS Press, (10.3233/NPM-229001)
• Tax, C. M., Bastiani, M., Veraart, J., Garyfallidis, E. and Okan Irfanoglu, M. 2022. What's new and what's next in diffusion MRI preprocessing. NeuroImage 249, article number: 118830. (10.1016/j.neuroimage.2021.118830)
• Schilling, K. G., Tax, C. M. W., Rheault, F., Landman, B. A., Anderson, A. W., Descoteaux, M. and Petit, L. 2022. Prevalence of white matter pathways coming into a single white matter voxel orientation: The bottleneck issue in tractography. Human Brain Mapping 43(4), pp. 1196-1213. (10.1002/hbm.25697)

2021

• Guo, F., Tax, C. M. W., De Luca, A., Viergever, M. A., Heemskerk, A. and Leemans, A. 2021. Fiber orientation distribution from diffusion MRI: Effects of inaccurate response function calibration. Journal of Neuroimaging 31(6), pp. 1082-1098. (10.1111/jon.12901)
• Schilling, K. G. et al. 2021. Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?. NeuroImage 243, article number: 118502. (10.1016/j.neuroimage.2021.118502)
• Schilling, K. G. et al. 2021. Fiber tractography bundle segmentation depends on scanner effects, vendor effects, acquisition resolution, diffusion sampling scheme, diffusion sensitization, and bundle segmentation workflow. NeuroImage 242, article number: 118451. (10.1016/j.neuroimage.2021.118451)
• Chamberland, M. et al. 2021. Detecting microstructural deviations in individuals with deep diffusion MRI tractometry. Nature Computational Science 1, pp. 598-606. (10.1038/s43588-021-00126-8)
• Tax, C. M. W., Kleban, E., Chamberland, M., Baraković, M., Rudrapatna, U. and Jones, D. K. 2021. Measuring compartmental T2-orientational dependence in human brain white matter using a tiltable RF coil and diffusion-T2 correlation MRI. NeuroImage 236, article number: 117967. (10.1016/j.neuroimage.2021.117967)
• Barakovic, M. et al. 2021. Resolving bundle-specific intra-axonal T2 values within a voxel using diffusion-relaxation tract-based estimation. NeuroImage 227, article number: 117617. (10.1016/j.neuroimage.2020.117617)
• Tax, C. M. W., Kleban, E., Barakovic, M., Chamberland, M. and Jones, D. K. 2021. Magnetic resonance imaging of T2 - and diffusion snisotropy using a tiltable receive coil. Presented at: Visualization and Processing of Anisotropy in Imaging, Geometry, and Astronomy, Dagstuhl, Germany, 28 Oct–2 Nov 2018 Presented at Ozarslan, E. et al. eds.Anisotropy Across Fields and Scales. Mathematics and Visualization Springer pp. 247-262., (10.1007/978-3-030-56215-1_12)
• de Almeida Martins, J. P., Tax, C. M. W., Reymbaut, A., Szczepankiewicz, F., Chamerland, M., Jones, D. K. and Topgaard, D. 2021. Computing and visualising intra-voxel orientation-specific relaxation-diffusion features in the human brain. Human Brain Mapping 42(2), pp. 310-328. (10.1002/hbm.25224)
• Guo, F., De Luca, A., Parker, G., Jones, D. K., Viergever, M. A., Leemans, A. and Tax, C. M. W. 2021. The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion MRI data. Human Brain Mapping 42(2), pp. 367-383. (10.1002/hbm.25228)
• Koller, K. et al. 2021. MICRA: Microstructural Image Compilation with Repeated Acquisitions. NeuroImage 225, article number: 117406. (10.1016/j.neuroimage.2020.117406)
• Gholam, J. A. et al. 2021. aDWI-BIDS: advanced diffusion weighted imaging metadata for the brain imaging data structure. Presented at: ISMRM & SMRT Annual Meeting & Exhibition, Virtual, 15-20 May 2021.

2020

• Ning, L. et al. 2020. Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: algorithms and result. NeuroImage 221, article number: 117128. (10.1016/j.neuroimage.2020.117128)
• Tong, Q. et al. 2020. A deep learning–based method for improving reliability of multicenter diffusion kurtosis imaging with varied acquisition protocols. Magnetic Resonance Imaging 73, pp. 31-44. (10.1016/j.mri.2020.08.001)
• Pizzolato, M. et al. 2020. Acquiring and predicting multidimensional diffusion (MUDI) data: an open challenge. Presented at: MICCAI Workshop, Shenzhen, China, Oct 2019 Presented at Bonet-Carne, E. et al. eds.Computational Diffusion MRI. Mathematics and Visualization Springer pp. 195-208., (10.1007/978-3-030-52893-5_17)
• St-Jean, S., De Luca, A., Tax, C. M., Viergever, M. A. and Leemans, A. 2020. Automated characterization of noise distributions in diffusion MRI data. Medical Image Analysis 65, article number: 101758. (10.1016/j.media.2020.101758)
• Moyer, D., Ver Steeg, G., Tax, C. M. W. and Thompson, P. M. 2020. Scanner invariant representations for diffusion MRI harmonization. Magnetic Resonance in Medicine 84(4), pp. 2174-2189. (10.1002/mrm.28243)
• Kleban, E., Tax, C. M., Rudrapatna, U. S., Jones, D. K. and Bowtell, R. 2020. Strong diffusion gradients allow the separation of intra- and extra-axonal gradient-echo signals in the human brain. NeuroImage 217, article number: 116793. (10.1016/j.neuroimage.2020.116793)
• Tax, C. M. W. 2020. Estimating chemical and microstructural heterogeneity by correlating relaxation and diffusion. In: Topgaard, D. ed. Advanced Diffusion Encoding Methods in MRI. Royal Society of Chemistry, pp. 186-227., (10.1039/9781788019910-00186)
• Genc, S., Tax, C. M. W., Raven, E. P., Chamberland, M., Parker, G. D. and Jones, D. K. 2020. Impact of b-value on estimates of apparent fibre density. Human Brain Mapping 41(10), pp. 2583-2595. (10.1002/hbm.24964)
• Rheault, F. et al. 2020. Tractostorm: the what, why, and how of tractography dissection reproducibility. Human Brain Mapping 41(7), pp. 1859-1874. (10.1002/hbm.24917)
• Tax, C., Sczepankiewicz, F., Nilsson, M. and Jones, D. K. 2020. The dot-compartment revealed? Diffusion MRI with ultra-strong gradients and spherical tensor encoding in the living human brain. NeuroImage 210, article number: 116534. (10.1016/j.neuroimage.2020.116534)
• Martins, J. P. d. A., Tax, C. M. W., Szczepankewicz, F., Jones, D. K., Westin, C. and Topgaard, D. 2020. Transferring principles of solid-state and Laplace NMR to the field of in vivo brain MRI. Magnetic Resonance 1, pp. 27-43. (10.5194/mr-1-27-2020)
• Harrison, J. R., Bhatia, S., Tan, Z. X., Mirza-Davies, A., Benkert, H., Tax, C. M. and Jones, D. K. 2020. Imaging Alzheimer's genetic risk using Diffusion MRI: a systematic review. NeuroImage: Clinical 27, article number: 102359. (10.1016/j.nicl.2020.102359)
• Chamberland, M. et al. 2020. Tractometry-based anomaly detection for single-subject white matter analysis. Presented at: Medical Imaging with Deep Learning (MIDL 2020), Montréal, Canada, 6-9 July 2020.
• Jenkins, C. et al. 2020. DW-MRS with ultra-strong diffusion gradients. Presented at: ISMRM & SMRT Virtual Conference & Exhibition 2020, Online, 8-14 August 2020.

2019

• Chamberland, M. et al. 2019. Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain. NeuroImage 200, pp. 89-100. (10.1016/j.neuroimage.2019.06.020)
• Tax, C. M. W. et al. 2019. Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms. NeuroImage 195, pp. 285-299. (10.1016/j.neuroimage.2019.01.077)
• Afzali Deligani, M., Tax, C. M., Chatziantoniou, C. and Jones, D. K. 2019. Comparison of different tensor encoding combinations in microstructural parameter estimation. Presented at: IEEE International Symposium on Biomedical Imaging, Venice, Italy, 8-11 Apr 20192019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). IEEE pp. 1471-1474., (10.1109/ISBI.2019.8759100)
• Ning, L. et al. 2019. Muti-shell diffusion MRI harmonisation and enhancement challenge (MUSHAC): Progress and results. Presented at: MICCAI 2018, Granada, Spain, 16-20 September 2018 Presented at Bonet-Carne, E. et al. eds.Computational Diffusion MRI, Vol. 1. Mathematics and Visualization Cham: Springer pp. 217-224., (10.1007/978-3-030-05831-9_18)
• Chamberland, M., St-Jean, S., Tax, C. M. W. and Jones, D. K. 2019. Obtaining representative core streamlines for white matter tractometry of the human brain. Presented at: International MICCAI Workshop, Granada, Spain, Sep 2018 Presented at Bonet-Carne, E. et al. eds.Computational Diffusion MRI. Mathematics and Visualization Cham: Springer pp. 359-366., (10.1007/978-3-030-05831-9_28)
• Blumberg, S. B., Palombo, M., Khoo, C. S., Tax, C. M. W., Tanno, R. and Alexander, D. C. 2019. Multi-stage prediction networks for data harmonization. Presented at: Medical Image Computing and Computer Assisted Intervention – MICCAI, Shenzhen, China, 13-17 Oct 2019Medical Image Computing and Computer Assisted Intervention – MICCAI Proceedings, Vol. 11767. Lecture Notes in Computer Science Springer pp. 411-419., (10.1007/978-3-030-32251-9_45)

2018

• Chamberland, M., Tax, C. M. W. and Jones, D. K. 2018. Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware. NeuroImage: Clinical 20, pp. 458-465. (10.1016/j.nicl.2018.08.021)
• Jones, D. K. et al. 2018. Microstructural imaging of the human brain with a 'super-scanner': 10 key advantages of ultra-strong gradients for diffusion MRI. NeuroImage 182, pp. 8-38. (10.1016/j.neuroimage.2018.05.047)
• Albi, A. et al. 2018. Image registration to compensate for EPI distortion in patients with brain tumors: an evaluation of tract-specific effects. Journal of Neuroimaging 28(2), pp. 173-182. (10.1111/jon.12485)

2017

• Maier-Hein, K. H. et al. 2017. The challenge of mapping the human connectome based on diffusion tractography. Nature Communications 8(1), article number: 1349. (10.1038/s41467-017-01285-x)
• Vos, S. B., Tax, C. M. W., Luijten, P. R., Ourselin, S., Leemans, A. and Froeling, M. 2017. The importance of correcting for signal drift in diffusion MRI. Magnetic Resonance in Medicine 77(1), pp. 285-299. (10.1002/mrm.26124)

2016

• Tax, C. M. W., Dela Haije, T., Fuster, A., Westin, C., Viergever, M. A., Florack, L. and Leemans, A. 2016. Sheet Probability Index (SPI): Characterizing the geometrical organization of the white matter with diffusion MRI. NeuroImage 142, pp. 260-279. (10.1016/j.neuroimage.2016.07.042)

2015

• Tax, C. M. W. et al. 2015. Seeing more by showing less: orientation-dependent transparency rendering for fiber tractography visualization. PLOS ONE 10(10), article number: e0139434. (10.1371/journal.pone.0139434)

2014

• Bach, M., Laun, F. B., Leemans, A., Tax, C. M. W., Biessels, G. J., Stieltjes, B. and Maier-Hein, K. H. 2014. Methodological considerations on tract-based spatial statistics (TBSS). NeuroImage 100, pp. 358-369. (10.1016/j.neuroimage.2014.06.021)