Probabilistic shortest path tractography in DTI using Gaussian Process ODE solvers

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

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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 publicationProceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014), Part III
EditorsPolina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe
PublisherSpringer
Publication date2014
Pages265-272
ISBN (Print)978-3-319-10442-3
ISBN (Electronic)978-3-319-10443-0
DOIs
Publication statusPublished - 2014
Event17th International Conference on Medical Image Computing and Computer Assisted Intervention - Massachusetts Institute of Technology, Cambridge, MA, Boston, United States
Duration: 14 Sep 201418 Sep 2014
Conference number: 17
http://miccai2014.org/
http://miccai2014.org/cfp.html

Conference

Conference17th International Conference on Medical Image Computing and Computer Assisted Intervention
Number17
LocationMassachusetts Institute of Technology, Cambridge, MA
CountryUnited States
CityBoston
Period14/09/201418/09/2014
Internet address
SeriesLecture Notes in Computer Science
Number8675
ISSN0302-9743

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