Fast tensor image morphing for elastic registration.

Pew Thian Yap, Guorong Wu, Hongtu Zhu, Weili Lin, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Citations (Scopus)

Abstract

We propose a novel algorithm, called Fast Tensor Image Morphing for Elastic Registration or 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 aligning 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 non-landmark 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. Results indicate that better accuracy can be achieved by F-TIMER, compared with other deformable registration algorithms, with significantly reduced computation time cost of 4-14 folds.

Original languageEnglish
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages721-729
Number of pages9
Volume12
EditionPt 1
Publication statusPublished - 2009 Dec 1

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ASJC Scopus subject areas

  • Medicine(all)

Cite this

Yap, P. T., Wu, G., Zhu, H., Lin, W., & Shen, D. (2009). Fast tensor image morphing for elastic registration. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 1 ed., Vol. 12, pp. 721-729)

Fast tensor image morphing for elastic registration. / Yap, Pew Thian; Wu, Guorong; Zhu, Hongtu; Lin, Weili; Shen, Dinggang.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 12 Pt 1. ed. 2009. p. 721-729.

Research output: Chapter in Book/Report/Conference proceedingChapter

Yap, PT, Wu, G, Zhu, H, Lin, W & Shen, D 2009, Fast tensor image morphing for elastic registration. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 edn, vol. 12, pp. 721-729.
Yap PT, Wu G, Zhu H, Lin W, Shen D. Fast tensor image morphing for elastic registration. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 1 ed. Vol. 12. 2009. p. 721-729
Yap, Pew Thian ; Wu, Guorong ; Zhu, Hongtu ; Lin, Weili ; Shen, Dinggang. / Fast tensor image morphing for elastic registration. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 12 Pt 1. ed. 2009. pp. 721-729
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