Diffusion tensor image registration using tensor geometry and orientation features

Jinzhong Yang, Dinggang Shen, Christos Davatzikos, Ragini Verma

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

68 Citations (Scopus)

Abstract

This paper presents a method for deformable registration of diffusion tensor (DT) images that integrates geometry and orientation features into a hierarchical matching framework. The geometric feature is derived from the structural geometry of diffusion and characterizes the shape of the tensor in terms of prolateness, oblateness, and sphericity of the tensor. Local spatial distributions of the prolate, oblate, and spherical geometry are used to create an attribute vector of geometric feature for matching. The orientation feature improves the matching of the WM fiber tracts by taking into account the statistical information of underlying fiber orientations. These features are incorporated into a hierarchical deformable registration framework to develop a diffusion tensor image registration algorithm. Extensive experiments on simulated and real brain DT data establish the superiority of this algorithm for deformable matching of diffusion tensors, thereby aiding in atlas creation. The robustness of the method makes it potentially useful for group-based analysis of DT images acquired in large studies to identify disease-induced and developmental changes.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2008 - 11th International Conference, Proceedings
Pages905-913
Number of pages9
EditionPART 2
DOIs
Publication statusPublished - 2008
Event11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008 - New York, NY, United States
Duration: 2008 Sep 62008 Sep 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5242 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008
CountryUnited States
CityNew York, NY
Period08/9/608/9/10

Keywords

  • Attribute vector
  • Deformable registration
  • Diffusion tensor imaging
  • Structural geometry
  • Tensor orientation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yang, J., Shen, D., Davatzikos, C., & Verma, R. (2008). Diffusion tensor image registration using tensor geometry and orientation features. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 - 11th International Conference, Proceedings (PART 2 ed., pp. 905-913). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5242 LNCS, No. PART 2). https://doi.org/10.1007/978-3-540-85990-1-109