Name
Abstract | ||
|---|---|---|
We investigate the use of anatomical priors in a Bayesian framework for diffusion tractography. We compare priors that utilize different types of information on the white-matter pathways to be reconstructed. This information includes manually labeled paths from a set of training subjects and anatomical segmentation labels obtained from T1-weighted MR images of the same subjects. Our results indicate that the use of prior information increases robustness to end-point ROI size and yields solutions that agree with expert-drawn manual labels, obviating the need for manual intervention on any new test subjects. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISBI.2009.5193126 | ISBI |
Keywords | Field | DocType |
anatomical prior,anatomical segmentation,bayesian framework,t1-weighted mr image,diffusion tractography,manual intervention,expert-drawn manual label,prior information increases robustness,different type,global probabilistic diffusion tractography,roi size,image reconstruction,probabilistic logic,spline,labeling,magnetic resonance image,data mining,magnetic resonance imaging,image segmentation | Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Diffusion Tractography,Image segmentation,Robustness (computer science),Artificial intelligence,Probabilistic logic,Prior probability,Anatomical segmentation,Bayesian probability | Conference |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anastasia Yendiki | 1 | 188 | 13.22 |
| Allison Stevens | 2 | 160 | 9.42 |
| Jean Augustinack | 3 | 153 | 8.75 |
| David Salat | 4 | 213 | 14.91 |
| Lilla Zollei | 5 | 337 | 24.45 |
| Fischl Bruce | 6 | 4131 | 219.39 |