Abstract
In this paper, a novel intermediate templates guided image registration algorithm is proposed to achieve accurate registration results with a more appropriate strategy for intermediate template selection. We first demonstrate that registration directions and paths play a key role in the intermediate template guided registration methods. In light of this, a directed graph is built based on the asymmetric distances defined on all ordered image-pairs in the dataset. The allocated directed path can be used to guide the pairwise registration by successively registering the underlying subject towards the template through all intermediate templates on the path. Moreover, for the groupwise registration, a minimum spanning arborescence (MSA) is built with both the template (the root) and the directed paths (from all images to the template) determined simultaneously. Experiments on synthetic and real datasets show that our method can achieve more accurate registration results than both the traditional pairwise registration and the undirected graph based registration methods.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 175-183 |
| Number of pages | 9 |
| Volume | 7009 LNCS |
| DOIs | |
| Publication status | Published - 2011 Oct 17 |
| Externally published | Yes |
| Event | 2nd International Workshop on Machine Learning in Medical Imaging, MLMI 2011, in Conjunction with the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - Toronto, ON, Canada Duration: 2011 Sep 18 → 2011 Sep 18 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 7009 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 2nd International Workshop on Machine Learning in Medical Imaging, MLMI 2011, in Conjunction with the 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 |
|---|---|
| Country | Canada |
| City | Toronto, ON |
| Period | 11/9/18 → 11/9/18 |
Fingerprint
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
Cite this
Directed graph based image registration. / Jia, Hongjun; Wu, Guorong; Wang, Qian; Wang, Yaping; Kim, Minjeong; Shen, Dinggang.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7009 LNCS 2011. p. 175-183 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7009 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Directed graph based image registration
AU - Jia, Hongjun
AU - Wu, Guorong
AU - Wang, Qian
AU - Wang, Yaping
AU - Kim, Minjeong
AU - Shen, Dinggang
PY - 2011/10/17
Y1 - 2011/10/17
N2 - In this paper, a novel intermediate templates guided image registration algorithm is proposed to achieve accurate registration results with a more appropriate strategy for intermediate template selection. We first demonstrate that registration directions and paths play a key role in the intermediate template guided registration methods. In light of this, a directed graph is built based on the asymmetric distances defined on all ordered image-pairs in the dataset. The allocated directed path can be used to guide the pairwise registration by successively registering the underlying subject towards the template through all intermediate templates on the path. Moreover, for the groupwise registration, a minimum spanning arborescence (MSA) is built with both the template (the root) and the directed paths (from all images to the template) determined simultaneously. Experiments on synthetic and real datasets show that our method can achieve more accurate registration results than both the traditional pairwise registration and the undirected graph based registration methods.
AB - In this paper, a novel intermediate templates guided image registration algorithm is proposed to achieve accurate registration results with a more appropriate strategy for intermediate template selection. We first demonstrate that registration directions and paths play a key role in the intermediate template guided registration methods. In light of this, a directed graph is built based on the asymmetric distances defined on all ordered image-pairs in the dataset. The allocated directed path can be used to guide the pairwise registration by successively registering the underlying subject towards the template through all intermediate templates on the path. Moreover, for the groupwise registration, a minimum spanning arborescence (MSA) is built with both the template (the root) and the directed paths (from all images to the template) determined simultaneously. Experiments on synthetic and real datasets show that our method can achieve more accurate registration results than both the traditional pairwise registration and the undirected graph based registration methods.
UR - http://www.scopus.com/inward/record.url?scp=80053999033&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053999033&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24319-6_22
DO - 10.1007/978-3-642-24319-6_22
M3 - Conference contribution
AN - SCOPUS:80053999033
SN - 9783642243189
VL - 7009 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 175
EP - 183
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -