The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection
Open accessAbstract
Several approaches have been used to trace axonal trajectories from diffusion MRI data. If such techniques were first developed in a deterministic framework reducing the diffusion information to one single main direction, more recent approaches emerged that were statistical in nature and that took into account the whole diffusion information. Based on diffusion tensor MRI data coming from normal brains, this paper presents how brain connectivity could be modelled globally by means of a random walk algorithm. The mass of connections thus generated was then virtually dissected to uncover different tracts. Corticospinal, corticobulbar, and corticothalamic tracts, the corpus callosum, the limbic system, several cortical association bundles, the cerebellar peduncles, and the medial lemniscus were all investigated. The results were then displayed in the form of an in vivo brain connectivity atlas. The connectivity pattern and the individual fibre tracts were then compared to known anatomical data; a good matching was found.
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“Diffusion MRI became a foundational tool for the Human Connectome era because it offered a scalable route to individual structural connectivity (Assaf et al., 2019; Hagmann et al., 2003).”
From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Hagmann et al., 2003
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“Probabilistic approaches have also been used to create the first atlases of large-scale brain connections (Behrens et al., 2003; Hagmann et al., 2003; Parker et al., 2003).”
From 40 Years of diffusion MRI in the brain: From history to emerging frontiers (2026) · cites this paper as Hagmann et al., 2003
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Metadata
- Authors
- Hagmann, P., Thiran, J.-P., Jonasson, L., Vandergheynst, P., Clarke, S., Maeder, P., & Meuli, R.
- Affiliations
- Centre Hospitalier Universitaire Vaudois (CH)
- École Polytechnique Fédérale de Lausanne (CH)
- Corresponding author
- Hagmann, P.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2003-07
- Volume
- 19
- Issue
- 3
- Pages
- 545-554
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2131478329
- Cited by
- 326
- References
- 39
- Citations by year
- 2026: 3 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 4 · 2021: 5 · 2020: 12 · 2019: 9 · 2018: 10 · 2017: 8 · 2016: 9 · 2015: 8 · 2014: 16 · 2013: 30 · 2012: 20
- FWCI
- 16.56
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- 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 › Anatomy › Classical Anatomy and Histology
- Keywords
- diffusion tensor imaging, brain connectivity, random walk algorithm, virtual dissection, corticospinal tract, corticobulbar tract, corpus callosum, limbic system, cerebellar peduncles, medial lemniscus, axonal trajectories
- MeSH terms
- Algorithms, Axons, Brain, Brain Mapping, Cerebellum, Cerebral Cortex, Computer Graphics, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Nerve Fibers, Neural Pathways, Pyramidal Tracts, Thalamus
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