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Fiber tracking: principles and strategies – a technical review
Open accessAbstract
The state of the art of reconstruction of the axonal tracts in the central nervous system (CNS) using diffusion tensor imaging (DTI) is reviewed. This relatively new technique has generated much enthusiasm and high expectations because it presently is the only approach available to non‐invasively study the three‐dimensional architecture of white matter tracts. While there is no doubt that DTI fiber tracking is providing exciting new opportunities to study CNS anatomy, it is very important to understand its limitations. In this review we therefore assess the basic principles and the assumptions that need to be made for each step of the study, including both data acquisition and the elaborate fiber reconstruction algorithms. Special attention is paid to situations where complications may arise, and possible solutions are reviewed. Validation issues and potential future directions and improvements are also discussed. Copyright © 2002 John Wiley & Sons, Ltd.
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Metadata
- Authors
- Mori, S., & van Zijl, P. C. M.
- Venue
- NMR in Biomedicine
- Publisher
- Wiley
- Published
- 2002-11
- Volume
- 15
- Issue
- 7-8
- Pages
- 468-480
- ISSN
- 0952-3480 (ISSN-L)
- 1099-1492
- OpenAlex
- W2036785860
- Cited by
- 2,024
- References
- 5
- FWCI
- 30.44
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
