Tensor-based morphometry of fibrous structures with application to human brain white matter

Hui Zhang; Paul A. Yushkevich; Daniel Rueckert; James C. Gee

doi:10.1007/978-3-642-04271-3_57

Tensor-based morphometry of fibrous structures with application to human brain white matter

Hui Zhang, Paul A. Yushkevich, Daniel Rueckert, James C. Gee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

Tensor-based morphometry (TBM) is a powerful approach for examining shape changes in anatomy both across populations and in time. Our work extends the standard TBM for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. It leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. In this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. Our results show that additional insights can be gained with the proposed analysis.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings
Pages	466-473
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-04271-3_57
State	Published - 2009
Externally published	Yes
Event	12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009 - London, United Kingdom Duration: 20 Sep 2009 → 24 Sep 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5762 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Country/Territory	United Kingdom
City	London
Period	20/09/09 → 24/09/09

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10.1007/978-3-642-04271-3_57

Cite this

Zhang, H., Yushkevich, P. A., Rueckert, D., & Gee, J. C. (2009). Tensor-based morphometry of fibrous structures with application to human brain white matter. In Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings (PART 2 ed., pp. 466-473). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5762 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-04271-3_57

Zhang, Hui ; Yushkevich, Paul A. ; Rueckert, Daniel et al. / Tensor-based morphometry of fibrous structures with application to human brain white matter. Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. PART 2. ed. 2009. pp. 466-473 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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Zhang, H, Yushkevich, PA, Rueckert, D & Gee, JC 2009, Tensor-based morphometry of fibrous structures with application to human brain white matter. in Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5762 LNCS, pp. 466-473, 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009, London, United Kingdom, 20/09/09. https://doi.org/10.1007/978-3-642-04271-3_57

Tensor-based morphometry of fibrous structures with application to human brain white matter. / Zhang, Hui; Yushkevich, Paul A.; Rueckert, Daniel et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. PART 2. ed. 2009. p. 466-473 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5762 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Tensor-based morphometry (TBM) is a powerful approach for examining shape changes in anatomy both across populations and in time. Our work extends the standard TBM for quantifying local volumetric changes to establish both rich and intuitive descriptors of shape changes in fibrous structures. It leverages the data from diffusion tensor imaging to determine local spatial configuration of fibrous structures and combines this information with spatial transformations derived from image registration to quantify fibrous structure-specific changes, such as local changes in fiber length and in thickness of fiber bundles. In this paper, we describe the theoretical framework of our approach in detail and illustrate its application to study brain white matter. Our results show that additional insights can be gained with the proposed analysis.

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Zhang H, Yushkevich PA, Rueckert D, Gee JC. Tensor-based morphometry of fibrous structures with application to human brain white matter. In Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings. PART 2 ed. 2009. p. 466-473. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-04271-3_57

Tensor-based morphometry of fibrous structures with application to human brain white matter

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