Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
470-03-088 ISMRM Abstract

FixelBayes: A Bayesian framework for fixel-based analysis of diffusion MRI data

Primary: Neuro - White Matter
Secondary: Diffusion - Diffusion Analysis & Visualization
470-03-088 · Diffusion: Tractography Methods · Tuesday, 12 May, 9:15 AM–10:10 AM · Traditional Posters | Exhibition Hall
Keywords: Psychiatric Disorders White Matter Fixel-based analysis Diffusion-Weighted Imaging Bayes factor
Accepted
Jackson M Lee 1, Charles B Malpas2,3,4, Sila Genc5,6, Joseph Y Yang7,8,9, Andrew Zalesky10,11, Remika Mito1
1Department of Psychiatry, University of Melbourne, Melbourne, Australia
2Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia
3Department of Neuroscience, Monash University, Melbourne, VIC, Australia, Australia
4Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia
5Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, Australia
6Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, Royal Childrens Hospital, Melbourne, Australia
7Department of Paediatrics, University of Melbourne, Melbourne, Australia
8Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), Melbourne, Australia
9Neuroscience Research, Murdoch Children’s Research Institute, Melbourne, Australia
10Departments of Psychiatry and Biomedical Engineering, University of Melbourne, Melbourne, Australia
11University of Melbourne, Melbourne, Australia
Presenting Author: Jackson M Lee

Synopsis

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References

1. Raffelt DA, Tournier JD, Smith RE, Vaughan DN, Jackson G, Ridgway GR, et al. Investigating white matter fibre density and morphology using fixel-based analysis. Neuroimage. 2017;144:58–73.
2. Mito R, Raffelt D, Dhollander T, Vaughan DN, Tournier JD, Salvado O, et al. Fibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment. Brain. 2018;141(3):888–902.
3. Jacobs GR, Coleman MJ, Lewandowski KE, Pasternak O, Cetin-Karayumak S, Mesholam-Gately RI, et al. An introduction to the Human Connectome Project for Early Psychosis. Schizophr Bull. 2024 Jul 20;SBAE123.
4. Tournier JD, Smith R, Raffelt D, Tabbara R, Dhollander T, Pietsch M, et al. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. Neuroimage. 2019;202:116137.
5. Jeurissen B, Tournier JD, Dhollander T, Connelly A, Sijbers J. Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage. 2014;103:411–26.
6. Dhollander T, Connelly A. A novel iterative approach to reap the benefits of multi-tissue CSD from just single-shell (+b=0) diffusion MRI data. Proc ISMRM. 2016;24:3010.
7. Raffelt D, Tournier JD, Fripp J, Crozier S, Connelly A, Salvado O. Symmetric diffeomorphic registration of fibre orientation distributions. Neuroimage. 2011;56(3):1171–80.
8. Raffelt DA, Smith RE, Ridgway GR, Tournier JD, Vaughan DN, Rose S, et al. Connectivity-based fixel enhancement: Whole-brain statistical analysis of diffusion MRI measures in the presence of crossing fibres. Neuroimage. 2015;117:40–55.
9. Morey RD, Rouder JN. BayesFactor: Computation of Bayes Factors for Common Designs. 2023. Available from: https://github.com/richarddmorey/bayesfactor
10. Lee MD, Wagenmakers EJ. Bayesian Cognitive Modeling: A Practical Course. Cambridge: Cambridge University Press; 2014.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/470-03-088