Name
Abstract | ||
|---|---|---|
In this study we address the problem of extracting a robust connectivity metric for brain white matter. We defined the connectivity problem as an energy minimization task, by associating the DT-field to a physical system composed of nodes and springs, with their constants defined as a function of local structure. Using a variational approach we formulated a fast and stable map evolution, which utilizes an anisotropic kernel smoothing scheme equivalent to a diffusion PDE. The proposed method provides connectivity maps that correlate with normal anatomy on real patient data. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11566465_27 | MICCAI |
Keywords | Field | DocType |
connectivity problem,diffusion pde,connectivity map,physical system,brain white matter,normal anatomy,physical model,connectivity map computation,energy minimization task,local structure,anisotropic kernel,energy minimization,kernel smoothing | Topology,Kernel smoother,Anisotropy,Stable map,Physical system,Computer science,Local structure,Brain White Matter,Computation,Energy minimization | Conference |
Volume | Issue | ISSN |
8 | Pt 1 | 0302-9743 |
ISBN | Citations | PageRank |
3-540-29327-2 | 3 | 0.44 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erdem Yörük | 1 | 126 | 8.73 |
| Burak Acar | 2 | 326 | 27.19 |
| Roland Bammer | 3 | 43 | 5.54 |