Abstract
We propose a novel diffusion tensor imaging (DTI) registration algorithm, called fast tensor image morphing for elastic registration (F-TIMER). F-TIMER leverages multiscale tensor regional distributions and local boundaries for hierarchically driving deformable matching of tensor image volumes. Registration is achieved by utilizing a set of automatically determined structural landmarks, via solving a soft correspondence problem. Based on the estimated correspondences, thin-plate splines are employed to generate a smooth, topology preserving, and dense transformation, and to avoid arbitrary mapping of nonlandmark voxels. To mitigate the problem of local minima, which is common in the estimation of high dimensional transformations, we employ a hierarchical strategy where a small subset of voxels with more distinctive attribute vectors are first deployed as landmarks to estimate a relatively robust low-degrees-of-freedom transformation. As the registration progresses, an increasing number of voxels are permitted to participate in refining the correspondence matching. A scheme as such allows less conservative progression of the correspondence matching towards the optimal solution, and hence results in a faster matching speed. Compared with its predecessor TIMER, which has been shown to outperform state-of-the-art algorithms, experimental results indicate that F-TIMER is capable of achieving comparable accuracy at only a fraction of the computation cost.
| Original language | English |
|---|---|
| Article number | 5433042 |
| Pages (from-to) | 1192-1203 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Medical Imaging |
| Volume | 29 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2010 May 1 |
| Externally published | Yes |
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Keywords
- Diffusion tensor imaging (DTI)
- Elastic registration
- Log-Euclidean manifold
- Tensor boundaries
- Tensor regional distributions
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Computer Science Applications
- Radiological and Ultrasound Technology
- Software
Cite this
F-TIMER : Fast tensor image morphing for elastic registration. / Yap, Pew Thian; Wu, Guorong; Zhu, Hongtu; Lin, Weili; Shen, Dinggang.
In: IEEE Transactions on Medical Imaging, Vol. 29, No. 5, 5433042, 01.05.2010, p. 1192-1203.Research output: Contribution to journal › Article
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TY - JOUR
T1 - F-TIMER
T2 - Fast tensor image morphing for elastic registration
AU - Yap, Pew Thian
AU - Wu, Guorong
AU - Zhu, Hongtu
AU - Lin, Weili
AU - Shen, Dinggang
PY - 2010/5/1
Y1 - 2010/5/1
N2 - We propose a novel diffusion tensor imaging (DTI) registration algorithm, called fast tensor image morphing for elastic registration (F-TIMER). F-TIMER leverages multiscale tensor regional distributions and local boundaries for hierarchically driving deformable matching of tensor image volumes. Registration is achieved by utilizing a set of automatically determined structural landmarks, via solving a soft correspondence problem. Based on the estimated correspondences, thin-plate splines are employed to generate a smooth, topology preserving, and dense transformation, and to avoid arbitrary mapping of nonlandmark voxels. To mitigate the problem of local minima, which is common in the estimation of high dimensional transformations, we employ a hierarchical strategy where a small subset of voxels with more distinctive attribute vectors are first deployed as landmarks to estimate a relatively robust low-degrees-of-freedom transformation. As the registration progresses, an increasing number of voxels are permitted to participate in refining the correspondence matching. A scheme as such allows less conservative progression of the correspondence matching towards the optimal solution, and hence results in a faster matching speed. Compared with its predecessor TIMER, which has been shown to outperform state-of-the-art algorithms, experimental results indicate that F-TIMER is capable of achieving comparable accuracy at only a fraction of the computation cost.
AB - We propose a novel diffusion tensor imaging (DTI) registration algorithm, called fast tensor image morphing for elastic registration (F-TIMER). F-TIMER leverages multiscale tensor regional distributions and local boundaries for hierarchically driving deformable matching of tensor image volumes. Registration is achieved by utilizing a set of automatically determined structural landmarks, via solving a soft correspondence problem. Based on the estimated correspondences, thin-plate splines are employed to generate a smooth, topology preserving, and dense transformation, and to avoid arbitrary mapping of nonlandmark voxels. To mitigate the problem of local minima, which is common in the estimation of high dimensional transformations, we employ a hierarchical strategy where a small subset of voxels with more distinctive attribute vectors are first deployed as landmarks to estimate a relatively robust low-degrees-of-freedom transformation. As the registration progresses, an increasing number of voxels are permitted to participate in refining the correspondence matching. A scheme as such allows less conservative progression of the correspondence matching towards the optimal solution, and hence results in a faster matching speed. Compared with its predecessor TIMER, which has been shown to outperform state-of-the-art algorithms, experimental results indicate that F-TIMER is capable of achieving comparable accuracy at only a fraction of the computation cost.
KW - Diffusion tensor imaging (DTI)
KW - Elastic registration
KW - Log-Euclidean manifold
KW - Tensor boundaries
KW - Tensor regional distributions
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UR - http://www.scopus.com/inward/citedby.url?scp=77951818972&partnerID=8YFLogxK
U2 - 10.1109/TMI.2010.2043680
DO - 10.1109/TMI.2010.2043680
M3 - Article
C2 - 20304728
AN - SCOPUS:77951818972
VL - 29
SP - 1192
EP - 1203
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
SN - 0278-0062
IS - 5
M1 - 5433042
ER -