Name
Title | ||
|---|---|---|
Left-invariant metrics for diffeomorphic image registration with spatially-varying regularisation. |
Abstract | ||
|---|---|---|
We present a new framework for diffeomorphic image registration which supports natural interpretations of spatially-varying metrics. This framework is based on left-invariant diffeomorphic metrics (LIDM) and is closely related to the now standard large deformation diffeomorphic metric mapping (LDDMM). We discuss the relationship between LIDM and LDDMM and introduce a computationally convenient class of spatially-varying metrics appropriate for both frameworks. Finally, we demonstrate the effectiveness of our method on a 2D toy example and on the 40 3D brain images of the LPBA40 dataset. |
Year | Venue | DocType |
|---|---|---|
2013 | Lecture Notes in Computer Science | Conference |
Volume | Issue | ISSN |
8149 | Pt 1 | 0302-9743 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tanya Schmah | 1 | 46 | 3.97 |
| Laurent Risser | 2 | 241 | 18.63 |
| François-Xavier Vialard | 3 | 172 | 15.44 |