Effect of data acquisition and analysis method on fiber orientation estimation in diffusion MRI

Bryce Wilkins, Namgyun Lee, Vidya Rajagopalan, Meng Law, Natasha Leporé

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

1 Citation (Scopus)


In this paper we investigate the effect of single-shell q-space diffusion sampling strategies and applicable multiple-fiber analysis methods on fiber orientation estimation in Diffusion MRI. Specifically, we develop a simulation based on an in-vivo data set and compare a two-compartment “ball-and-stick” model, a constrained spherical deconvolution approach, a generalized Fourier transform approach, and three related methods based on transforms of Fourier data on the sphere. We evaluate each method for N D 20, 30, 40, 60, 90 and 120 angular diffusion-weighted samples, at SNR D 18 and diffusion-weighting b D 1;000 s=mm2, common to clinical studies. Our results quantitatively show the methods are most distinguished from each other by their fiber detection ability. Overall, the “ball-and-stick” model and spherical deconvolution approach were found to perform best, yielding the least orientation error, and greatest detection rate of fibers.

Original languageEnglish
Title of host publicationComputational Diffusion MRI and Brain Connectivity
EditorsThomas Schultz, Gemma Nedjati-Gilani, Archana Venkataraman, Lauren O’Donnell, Eleftheria Panagiotaki
Place of PublicationCham
Number of pages12
ISBN (Electronic)9783319024752
ISBN (Print)9783319024745
Publication statusPublished - 1 Jan 2014
Externally publishedYes
EventMedical Image Computing and Computer Assisted Intervention Workshop on Computational Diffusion MRI - Nagoya, Japan
Duration: 22 Sep 201322 Sep 2013

Publication series

NameMathematics and Visualization
ISSN (Print)1612-3786
ISSN (Electronic)1612-3786


WorkshopMedical Image Computing and Computer Assisted Intervention Workshop on Computational Diffusion MRI

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