Model-based analysis of multishell diffusion MR data for tractography: how to get over fitting problems
Open accessAbstract
In this article, we highlight an issue that arises when using multiple b ‐values in a model‐based analysis of diffusion MR data for tractography. The non‐monoexponential decay, commonly observed in experimental data, is shown to induce overfitting in the distribution of fiber orientations when not considered in the model. Extra fiber orientations perpendicular to the main orientation arise to compensate for the slower apparent signal decay at higher b ‐values. We propose a simple extension to the ball and stick model based on a continuous gamma distribution of diffusivities, which significantly improves the fitting and reduces the overfitting. Using in vivo experimental data, we show that this model outperforms a simpler, noise floor model, especially at the interfaces between brain tissues, suggesting that partial volume effects are a major cause of the observed non‐monoexponential decay. This model may be helpful for future data acquisition strategies that may attempt to combine multiple shells to improve estimates of fiber orientations in white matter and near the cortex. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
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HCP developed novel fiber reconstruction algorithms optimized for multi-shell diffusion data.
“HCP has developed novel fiber reconstruction algorithms that are optimized for multi-shell data (Jbabdi et al. 2012).”
From The WU-Minn Human Connectome Project: An overview (2013) · cites this paper as Jbabdi et al. 2012
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- Authors
- Jbabdi, S., Sotiropoulos, S. N., Savio, A. M., Graña, M., & Behrens, T. E. J.
- Affiliations
- University of Oxford (GB)
- University of the Basque Country (ES)
- Wellcome Centre for Human Neuroimaging (GB)
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2012-02-14
- Volume
- 68
- Issue
- 6
- Pages
- 1846-1855
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- PMC
- PMC3359399
- OpenAlex
- W2130801245
- Cited by
- 399
- References
- 44
- Citations by year
- 2026: 19 · 2025: 37 · 2024: 39 · 2023: 39 · 2022: 36 · 2021: 45 · 2020: 34 · 2019: 23 · 2018: 23 · 2017: 28 · 2016: 20 · 2015: 28 · 2014: 12 · 2013: 13 · 2012: 2
- FWCI
- 13.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Magnetic Resonance in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (1U54MH091657, WT088312AIA)
- National Institutes of Health (5u54mh091657-05, 1U54‐MH‐091657)
- Medical Research Council (1U54MH091657, G0800578)
- National Institute of Mental Health (1U54-MH091657-01, U54-MH091657)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
- Keywords
- diffusion MRI, tractography, overfitting, ball-and-stick model, fiber orientation distribution, partial volume effect, white matter
- MeSH terms
- Algorithms, Brain, Computer Simulation, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Models, Anatomic, Models, Neurological, Nerve Fibers, Myelinated, Pattern Recognition, Automated, Sensitivity and Specificity, Subtraction Technique, Reproducibility of Results, Diffusion Tensor Imaging
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