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 |
---|---|
Title of host publication | Medical image computing and computer-assisted intervention – MICCAI 2014 : 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part III |
Editors | Polina Golland, Nobuhiko Hata, Christian Barillot, Joachim Hornegger, Robert Howe |
Number of pages | 8 |
Publisher | Springer |
Publication date | 2014 |
Pages | 265-272 |
Chapter | 34 |
ISBN (Print) | 978-3-319-10442-3 |
DOIs | |
Publication status | Published - 2014 |
Event | International Conference, MICCAI 2014 - Boston, United States Duration: 14 Sept 2014 → 18 Sept 2014 Conference number: 17 |
Conference
Conference | International Conference, MICCAI 2014 |
---|---|
Number | 17 |
Country/Territory | United States |
City | Boston |
Period | 14/09/2014 → 18/09/2014 |
Series | Lecture notes in computer science |
---|---|
Volume | 8675 |
ISSN | 0302-9743 |