Name
Abstract | ||
|---|---|---|
As image registration becomes more and more central to many biomedical imaging applications, the efficiency of the algorithms becomes a key issue. Image registration is classically performed by optimizing a similarity criterion over a given spatial transformation space. Even if this problem is considered as almost solved for linear registration, we show in this paper that some tools that have recently been developed in the field of vision-based robot control can outperform classical solutions. The adequacy of these tools for linear image registration leads us to revisit non-linear registration and allows us to provide interesting theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage to the symmetric forces variant of the demons algorithm. We show that, on controlled experiments, this advantage is confirmed, and yields a faster convergence. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73273-0_41 | IPMI |
Keywords | Field | DocType |
efficient image registration technique,demons algorithm,interesting theoretical root,theoretical advantage,linear registration,classical solution,controlled experiment,image registration,non-linear registration,biomedical imaging application,linear image registration,robot control,biomedical imaging | Convergence (routing),Robot control,Computer vision,Medical imaging,Computer science,Similarity criterion,Algorithm,Spatial transformation,Artificial intelligence,Image registration | Conference |
Volume | ISSN | Citations |
20 | 1011-2499 | 27 |
PageRank | References | Authors |
1.61 | 9 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tom Vercauteren | 1 | 1956 | 108.68 |
| Xavier Pennec | 2 | 5021 | 357.08 |
| Ezio Malis | 3 | 1322 | 80.65 |
| Aymeric Perchant | 4 | 818 | 39.78 |
| Nicholas Ayache | 5 | 10804 | 1654.36 |