The DOI matches its Crossref record; 45 of the 47 references it cites were found in a registry or an index.
Flow-based fiber tracking with diffusion tensor and q-ball data: Validation and comparison to principal diffusion direction techniques
Abstract
In this study, we evaluate the performance of a flow-based surface evolution fiber tracking algorithm by means of a physical anisotropic diffusion phantom with known connectivity. We introduce a novel speed function for surface evolution that is derived from either diffusion tensor (DT) data, high angular resolution diffusion (HARD) data, or a combined DT-HARD hybrid approach. We use the model-free q-ball imaging (QBI) approach for HARD reconstruction. The anisotropic diffusion phantom allows us to compare and evaluate the performance of different fiber tracking approaches in the presence of real imaging artifacts, noise, and subvoxel partial volume averaging of fiber directions. The surface evolution approach, using the full diffusion tensor as opposed to the principal diffusion direction (PDD) only, is compared to PDD-based line propagation fiber tracking. Additionally, DT reconstruction is compared to HARD reconstruction for fiber tracking, both using surface evolution. We show the potential for surface evolution using the full diffusion tensor to map connections in regions of subvoxel partial volume averaging of fiber directions, which can be difficult to map with PDD-based methods. We then show that the fiber tracking results can be improved by using high angular resolution reconstruction of the diffusion orientation distribution function in cases where the diffusion tensor model fits the data poorly.
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“Ex vivo imaging and tracing17–23 or physically24–30 and numerically simulated phantoms31–34 allow validation to some extent, and in specific circumstances such as basic fiber configurations.”
From Tractography-based connectomes are dominated by false-positive connections (2016) · cites this paper as [18]
Citations
Cites
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · Cited by 15,411
Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
Osher, S., & Sethian, J. A. (1988) · Journal of Computational Physics · doi:10.1016/0021-9991(88)90002-2 · Cited by 14,196
Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo
Basser, P. J., Mattiello, J., & Bihan, D. L. (1994) · Journal of Magnetic Resonance Series B · doi:10.1006/jmrb.1994.1037 · Cited by 3,656
Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging
Mori, S., Crain, B. J., Chacko, V. P., & van Zijl, P. C. M. (1999) · Annals of Neurology · doi:10.1002/1531-8249(199902)45:2 · Cited by 3,513
Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space
Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199403000-00005 · Cited by 3,431 · cited 2×
“The b = 1300 s/mm2 and b = 3000 s/mm2 datasets were acquired in separate sessions and were subsequently registered using semi-automatic techniques (Collins et al., 1994).”
MethodCharacterization and propagation of uncertainty in diffusion-weighted MR imaging
Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen‐Berg, H., Nunes, R. G., Clare, S., Matthews, P. M., Brady, J. M., & Smith, S. M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10609 · Cited by 3,038
Toward a quantitative assessment of diffusion anisotropy
Pierpaoli, C. M., & Basser, P. J. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910360612 · Cited by 2,392
Fiber Tract–based Atlas of Human White Matter Anatomy
Wakana, S., Jiang, H., Nagae‐Poetscher, L. M., van Zijl, P. C. M., & Mori, S. (2004) · Radiology · doi:10.1148/radiol.2301021640 · Cited by 2,023
Tracking neuronal fiber pathways in the living human brain
Conturo, T. E., Lori, N. F., Cull, T. S., Akbudak, E., Snyder, A. Z., Shimony, J. S., McKinstry, R. C., Burton, H., & Raichle, M. E. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.18.10422 · Cited by 1,774
High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity
Tuch, D. S., Reese, T. G., Wiegell, M. R., Makris, N., Belliveau, J. W., & Wedeen, V. J. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10268 · Cited by 1,548 · cited 4×
“…high angular resolution (Alexander et al., 2002; Frank, 2002; Zhan et al., 2003), however, the maxima of the ADC profile do not necessarily coincide with fiber directions (Tuch et al., 2002; von dem Hagen and Henkelman, 2001), hence further processing is necessary for fiber tracking applications.”
BackgroundMethodInfluential
Research works printed but not linked: 1
- Press, 1992
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Sorted by citations
Tractography-based connectomes are dominated by false-positive connections
Maier-Hein, K. H., Neher, P., Houde, J.-C., Côté, M.-A., Garyfallidis, E., Zhong, J., Chamberland, M., Yeh, F.-C., Lin, Y.-C., Ji, Q., et al. (2016) · doi:10.1101/084137 · Cited by 1,376
Diffusion tensor imaging and beyond
Tournier, J., Mori, S., & Leemans, A. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22924 · Cited by 921
Regularized, fast, and robust analytical Q-ball imaging
Descoteaux, M., Angelino, E., Fitzgibbons, S., & Deriche, R. (2007) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21277 · Cited by 850
Deterministic and probabilistic tractography based on complex fibre orientation distributions
Descoteaux, M., Deriche, R., Knosche, T. R., & Anwander, A. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2004424 · Cited by 698
Diffusion MRI fiber tractography of the brain
Jeurissen, B., Descoteaux, M., Mori, S., & Leemans, A. (2019) · NMR in Biomedicine · doi:10.1002/nbm.3785 · Cited by 574
Metadata
- Authors
- Campbell, J. S. W., Siddiqi, K., Rymar, V. V., Sadikot, A. F., & Pike, G. B.
- Affiliations
- McGill University (CA)
- Corresponding author
- Campbell, Jennifer S.W.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2005-10
- Volume
- 27
- Issue
- 4
- Pages
- 725-736
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2156127840
- Cited by
- 177
- References
- 47
- Citations by year
- 2025: 3 · 2024: 2 · 2023: 3 · 2022: 1 · 2021: 3 · 2020: 1 · 2019: 2 · 2018: 4 · 2017: 13 · 2016: 6 · 2015: 10 · 2014: 12 · 2013: 15 · 2012: 4
- FWCI
- 11.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- tractography, surface evolution, diffusion tensor imaging, Q-ball imaging, high angular resolution diffusion MRI, orientation distribution function, white matter connectivity
- MeSH terms
- Algorithms, Brain, Humans, Image Processing, Computer-Assisted, Manikins, Nerve Fibers, Reproducibility of Results, Models, Statistical, Anisotropy, Diffusion Magnetic Resonance Imaging
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