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. © 2014 Springer International Publishing.
CITATION STYLE
Schober, M., Kasenburg, N., Feragen, A., Hennig, P., & Hauberg, S. (2014). Probabilistic shortest path tractography in DTI using Gaussian process ODE solvers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8675 LNCS, pp. 265–272). Springer Verlag. https://doi.org/10.1007/978-3-319-10443-0_34
Mendeley helps you to discover research relevant for your work.