Probabilistic shortest path tractography in DTI using gaussian process ODE solvers

Michael Schober, Niklas Kasenburg, Aasa Feragen, Philipp Hennig, Søren Hauberg

20 Citations (Scopus)

Abstract

Tractography in diffusion tensor imaging estimates connectivity in the brain through observations of local diffusivity. These observations are noisy and of low resolution and, as a consequence, connections cannot be found with high precision. We use probabilistic numerics to estimate connectivity between regions of interest and contribute a Gaussian Process tractography algorithm which allows for both quantification and visualization of its posterior uncertainty. We use the uncertainty both in visualization of individual tracts as well as in heat maps of tract locations. Finally, we provide a quantitative evaluation of different metrics and algorithms showing that the adjoint metric [8] combined with our algorithm produces paths which agree most often with experts.

Original languageEnglish
Title of host publicationMedical image computing and computer-assisted intervention – MICCAI 2014 : 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part III
EditorsPolina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe
Number of pages8
PublisherSpringer
Publication date2014
Pages265-272
Chapter34
ISBN (Print)978-3-319-10442-3
DOIs
Publication statusPublished - 2014
EventInternational Conference, MICCAI 2014 - Boston, United States
Duration: 14 Sept 201418 Sept 2014
Conference number: 17

Conference

ConferenceInternational Conference, MICCAI 2014
Number17
Country/TerritoryUnited States
CityBoston
Period14/09/201418/09/2014
SeriesLecture notes in computer science
Volume8675
ISSN0302-9743

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