Name
Abstract | ||
|---|---|---|
This paper presents a novel method for creating an unbiased and geometrically centered average from a group of images. The morphological variability of the group is modeled as a set of deformation fields which encode differences between the group average and individual members. We demonstrate the algorithm on a group of 27 MR images of mouse brains. The average image is highly resolved as a result of excellent groupwise registration. Local and global groupwise variability estimates are discussed. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-30135-6_75 | Lecture Notes in Computer Science |
Field | DocType | Volume |
ENCODE,Computer vision,Pattern recognition,Computer science,Artificial intelligence,Deformation (mechanics) | Conference | 3216 |
ISSN | Citations | PageRank |
0302-9743 | 6 | 0.77 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Natasa Kovacevic | 1 | 80 | 9.45 |
| Josette Chen | 2 | 31 | 3.89 |
| John G. Sled | 3 | 688 | 191.06 |
| Jeff Henderson | 4 | 6 | 1.10 |
| Mark Henkelman | 5 | 13 | 1.99 |