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 proceedingConference contribution

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 [1, 2], with significantly reduced computation time cost of 4-14 folds.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages721-729
Number of pages9
Volume5761 LNCS
EditionPART 1
DOIs
Publication statusPublished - 2009 Dec 1
Externally publishedYes
Event12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom
Duration: 2009 Sep 202009 Sep 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5761 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
CountryUnited Kingdom
CityLondon
Period09/9/2009/9/24

Fingerprint

Morphing
Registration
Tensors
Voxel
Tensor
Correspondence
Landmarks
Correspondence Problem
Thin-plate Spline
Splines
Refining
Progression
Local Minima
Topology
Leverage
Fast Algorithm
Fold
High-dimensional
Optimal Solution
Degree of freedom

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Yap, P. T., Wu, G., Zhu, H., Lin, W., & Shen, D. (2009). Fast tensor image morphing for elastic registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 5761 LNCS, pp. 721-729). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5761 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-04268-3_89

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

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5761 LNCS PART 1. ed. 2009. p. 721-729 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5761 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yap, PT, Wu, G, Zhu, H, Lin, W & Shen, D 2009, Fast tensor image morphing for elastic registration. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 edn, vol. 5761 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 5761 LNCS, pp. 721-729, 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, London, United Kingdom, 09/9/20. https://doi.org/10.1007/978-3-642-04268-3_89
Yap PT, Wu G, Zhu H, Lin W, Shen D. Fast tensor image morphing for elastic registration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 1 ed. Vol. 5761 LNCS. 2009. p. 721-729. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-04268-3_89
Yap, Pew Thian ; Wu, Guorong ; Zhu, Hongtu ; Lin, Weili ; Shen, Dinggang. / Fast tensor image morphing for elastic registration. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 5761 LNCS PART 1. ed. 2009. pp. 721-729 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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