Estimating diffusion properties in complex fiber configurations based on structure-adaptive multi-valued tensor-field filtering

Jianfei Yang, Dirk H.J. Poot, Georgius A.M. Arkesteijn, Matthan W. Caan, Lucas J. Van Vliet, Frans M. Vos

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Conventionally, a single rank-2 tensor is used to assess the white matter integrity in diffusion imaging of the human brain. However, a single tensor fails to describe the diffusion in fiber crossings. Although a dual tensor model is able to do so, the low signal-to-noise ratio hampers reliable parameter estimation as the number of parameters is doubled. We present a framework for structure-adaptive tensor field filtering to enhance the statistical analysis in complex fiber structures. In our framework, a tensor model will be fitted based on an automated relevance determination method. Particularly, a single tensor model is applied to voxels in which the data seems to represent a single fiber and a dualtensor model to voxels appearing to contain crossing fibers. To improve the estimation of the model parameters we propose a structure-adaptive tensor filter that is applied to tensors belonging to the same fiber compartment only. It is demonstrated that the structure-adaptive tensor-field filter improves the continuity and regularity of the estimated tensor field. It outperforms an existing denoising approach called LMMSE, which is applied to the diffusion-weighted images. Track-based spatial statistics analysis of fiber-specific FA maps show that the method sustains the detection of more subtle changes in white matter tracts than the classical single-tensor-based analysis. Thus, the filter enhances the applicability of the dual-tensor model in diffusion imaging research. Specifically, the reliable estimation of two tensor diffusion properties facilitates fiber-specific extraction of diffusion features.

Original languageEnglish
Title of host publicationMedical Imaging 2015
Subtitle of host publicationImage Processing
EditorsMartin A. Styner, Sebastien Ourselin
PublisherSPIE
Number of pages7
ISBN (Electronic)9781628415032
DOIs
Publication statusPublished - 2015
EventMedical Imaging 2015: Image Processing - Orlando, United States
Duration: 24 Feb 201526 Feb 2015

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9413

Conference

ConferenceMedical Imaging 2015: Image Processing
Country/TerritoryUnited States
CityOrlando
Period24/02/201526/02/2015

Keywords

  • DTI filtering
  • maximum likelihood estimation
  • tensor filtering
  • tract-based spatial statistics

Cite this