Fuzzy fibers: uncertainty in dMRI tractography

Thomas Schultz, Anna Vilanova, Ralph Brecheisen, Gordon Kindlmann

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

5 Citations (Scopus)

Abstract

Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research.

Original languageEnglish
Title of host publicationScientific visualization
Subtitle of host publicationuncertainty, multifield, biomedical, and scalable visualization
EditorsCharles D. Hansen, Min Chen, Christopher R. Johnson, Arie E. Kaufman, Hans Hagen
Place of PublicationLondon
PublisherSpringer
Chapter8
Pages79-92
Number of pages14
ISBN (Electronic)978-1-4471-6497-5
ISBN (Print)978-1-4471-6496-8
DOIs
Publication statusPublished - 1 Jan 2014

Publication series

NameMathematics and Visualization
ISSN (Print)1612-3786

Fingerprint Dive into the research topics of 'Fuzzy fibers: uncertainty in dMRI tractography'. Together they form a unique fingerprint.

  • Cite this

    Schultz, T., Vilanova, A., Brecheisen, R., & Kindlmann, G. (2014). Fuzzy fibers: uncertainty in dMRI tractography. In C. D. Hansen, M. Chen, C. R. Johnson, A. E. Kaufman, & H. Hagen (Eds.), Scientific visualization: uncertainty, multifield, biomedical, and scalable visualization (pp. 79-92). (Mathematics and Visualization). London: Springer. https://doi.org/10.1007/978-1-4471-6497-5_8