Name
Abstract | ||
|---|---|---|
Abstract To compare and integrate brain data, data from multiple subjects are typically mapped,into a canonical space. One method to do this is to conformally map cortical surfaces to the sphere. It is well known,that any genus zero Riemann surface can be mapped,conformally to a sphere. Since the cortical surface of the brain is a genus zero surface, con- formal mapping,offers a convenient method,to parameter- ize cortical surfaces without angular distortion, generating an orthogonal grid on the cortex that locally preserves the metric. To compare cortical surfaces more effectively, it is advantageous,to adjust the conformal parameterizations to match consistent anatomical features across subjects. This matching,of cortical patterns improves,the alignment of data across subjects, although it is more challenging to cre- ate a consistent conformal (orthogonal) parameterization of anatomy,across subjects when,landmarks,are constrained to lie at specific locations in the spherical parameter space. Here we propose a new method, based on a new energy functional, to optimize the conformal parameterization of cortical surfaces by using landmarks. Experimental results |
Year | Venue | Keywords |
|---|---|---|
2005 | Computer Graphics and Imaging | parameter space,conformal map,riemann surface |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yalin Wang | 1 | 1042 | 79.53 |
| Lok Ming Lui | 2 | 332 | 30.16 |
| Tony F. Chan | 3 | 8733 | 659.77 |
| Paul Thompson | 4 | 3860 | 321.32 |