Name
Abstract | ||
|---|---|---|
In this paper we develop a modified ray-tracing algorithm for geodesic tractography in the context of brain Diffusion Tensor Imaging (DTI). Our technique is based on computing multi-valued geodesics connecting two given points and tracking the evolution of adjacent geodesics. In order to do so we introduce a new Riemannian metric given by the adjugate sharpened diffusion tensor, combined with a constraint on the tracts outcome based on the geodesic deviation. We present tractography results, and compare our method with the existing ray-tracing approach and deterministic streamlining. Our preliminary results show an improved performance of modified ray-tracing regarding false positive fibers. We also show experiments on subcortical short association U-fibers, whose reconstruction is well-known to be hard in a DTI setting. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ISBI.2016.7493314 | 2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI) |
Field | DocType | ISSN |
Geodesic deviation,Computer vision,Diffusion MRI,Computer science,Ray tracing (graphics),Artificial intelligence,Adjugate matrix,Tractography,Geodesic | Conference | 1945-7928 |
Citations | PageRank | References |
0 | 0.34 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Neda Sepasian | 1 | 12 | 2.32 |
| J. H. Thije Boonkkamp | 2 | 23 | 7.77 |
| Laura Astola | 3 | 32 | 4.42 |
| Marcel Breeuwer | 4 | 323 | 26.34 |
| Andrea Fuster | 5 | 35 | 7.45 |