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Title: | A Bayesian method with reparameterization for diffusion tensor imaging - art. no. 69142J |
Authors: | Zhou, Diwei Dryden, Ian L. Koloydenko, Alexey Li, Bai |
Keywords: | Diffusion tensor imaging Multi-tensor model Bayesian method Monte Carlo simulation |
Issue Date: | 2008 |
Publisher: | © Society of Photo-optical Instrumentation Engineers (SPIE) |
Citation: | ZHOU, D. ... et al., 2008. A Bayesian method with reparameterization for diffusion tensor imaging [69142J]. Medical Imaging 2008: Image Processing, 69142J (March 11, 2008); doi:10.1117/12.771697 |
Abstract: | A multi-tensor model with identifiable parameters is developed for diffusion weighted MR images. A new parameterization method guarantees the symmetric positive-definiteness of the diffusion tensor. We set up a Bayesian method for parameter estimation. To investigate properties of the method, Monte Carlo simulated data from three distinct DTI direction schemes have been analyzed. The multi-tensor model with automatic model selection has also been applied to a healthy human brain dataset. Standard tensor-derived maps are obtained when the single-tensor model is fitted to a region of interest with a single dominant fiber direction. High anisotropy diffusion flows and main diffusion directions can be shown clearly in the FA map and diffusion ellipsoid map. For another region containing crossing fiber bundles, we estimate and display the ellipsoid map under the single tensor and double-tensor regimes of the multi-tensor model, suitably thresholding the Bayes factor for model selection. |
Description: | ZHOU, D. ... et al., 2008. A Bayesian method with reparameterization for diffusion tensor imaging [69142J]. Medical Imaging 2008: Image Processing, 69142J (March 11, 2008) http://dx.doi.org/10.1117/12.771697 Copyright 2008 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for
personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial
purposes, or modification of the content of the paper are prohibited. |
Sponsor: | European Commission FP6 Human Resources and Mobility program |
Version: | Published |
DOI: | 10.1117/12.771697 |
URI: | https://dspace.lboro.ac.uk/2134/17102 |
Publisher Link: | http://dx.doi.org/10.1117/12.771697 |
ISBN: | 978-0-8194-7098-0 |
ISSN: | 0277-786X |
Appears in Collections: | Published Articles (Maths)
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