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 language | English |
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Title of host publication | Proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2014), Part III |
Editors | Polina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe |
Publisher | Springer |
Publication date | 2014 |
Pages | 265-272 |
ISBN (Print) | 978-3-319-10442-3 |
ISBN (Electronic) | 978-3-319-10443-0 |
DOIs | |
Publication status | Published - 2014 |
Event | 17th International Conference on Medical Image Computing and Computer Assisted Intervention - Massachusetts Institute of Technology, Cambridge, MA, Boston, United States Duration: 14 Sep 2014 → 18 Sep 2014 Conference number: 17 http://miccai2014.org/ http://miccai2014.org/cfp.html |
Conference
Conference | 17th International Conference on Medical Image Computing and Computer Assisted Intervention |
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Number | 17 |
Location | Massachusetts Institute of Technology, Cambridge, MA |
Country/Territory | United States |
City | Boston |
Period | 14/09/2014 → 18/09/2014 |
Internet address |
Series | Lecture Notes in Computer Science |
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Number | 8675 |
ISSN | 0302-9743 |