Literature DB >> 19818861

Brain tractography using Q-ball imaging and graph theory: Improved connectivities through fibre crossings via a model-based approach.

Stamatios N Sotiropoulos1, Li Bai, Paul S Morgan, Cris S Constantinescu, Christopher R Tench.   

Abstract

Brain tractography techniques utilize a set of diffusion-weighted magnetic resonance images to reconstruct white matter tracts, non-invasively and in-vivo. Streamline tracking techniques propagate curves from a seed to imply connectivity to distal voxels. Alternative approaches have been developed that attempt to quantify connection strength between all voxels and the seed. Tractography based on graph theory is amongst them. Despite its potential, graph-based tracking through complex fibre configurations has not been extensively studied and existing methods have inherent limitations. Anatomically unlikely connections may be identified in fibre crossing regions, by assigning relatively high connection strengths to all crossing populations. In this study, we discuss these limitations and present a new approach for robustly propagating through fibre crossings, as described by the orientation distribution functions (ODFs) derived from Q-ball imaging. Each image voxel is treated as a graph node and graph arcs connect neighbouring voxels. Weights representative of both structural and diffusivity features are assigned to each arc. To account for the existence of crossing fibre populations within a voxel, complex ODFs are decomposed into components representative of single-fibre populations and an image multigraph is created. The multigraph is searched exhaustively, but efficiently, to find the strongest paths and assign connectivity strengths between a seed and all the other image voxels. A comparison with the existing graph-based tractography as well as Q-ball driven front evolution tractography is performed on simulated data, and on human Q-ball imaging data acquired from five healthy volunteers. The new approach improves the connection strengths through fibre crossing regions, reducing the strengths of paths that are less anatomically plausible. Copyright (c) 2009 Elsevier Inc. All rights reserved.

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Year:  2009        PMID: 19818861     DOI: 10.1016/j.neuroimage.2009.10.001

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  18 in total

1.  Distributed corpus callosum involvement in amyotrophic lateral sclerosis: a deterministic tractography study using q-ball imaging.

Authors:  G Caiazzo; D Corbo; F Trojsi; G Piccirillo; M Cirillo; M R Monsurrò; F Esposito; Gioacchino Tedeschi
Journal:  J Neurol       Date:  2013-10-15       Impact factor: 4.849

2.  Fast approximate stochastic tractography.

Authors:  Juan Eugenio Iglesias; Paul M Thompson; Cheng-Yi Liu; Zhuowen Tu
Journal:  Neuroinformatics       Date:  2012-01

3.  A Bayesian model of shape and appearance for subcortical brain segmentation.

Authors:  Brian Patenaude; Stephen M Smith; David N Kennedy; Mark Jenkinson
Journal:  Neuroimage       Date:  2011-02-23       Impact factor: 6.556

4.  Cellular Automata Tractography: Fast Geodesic Diffusion MR Tractography and Connectivity Based Segmentation on the GPU.

Authors:  Andac Hamamci
Journal:  Neuroinformatics       Date:  2020-01

5.  Human brain asymmetry in microstructural connectivity demonstrated by diffusional kurtosis imaging.

Authors:  Chu-Yu Lee; Ali Tabesh; Travis Nesland; Jens H Jensen; Joseph A Helpern; Maria V Spampinato; Leonardo Bonilha
Journal:  Brain Res       Date:  2014-09-17       Impact factor: 3.252

6.  Fasciculography: robust prior-free real-time normalized volumetric neural tract parcellation.

Authors:  Hon Pong Ho; Fei Wang; Xenophon Papademetris; Hilary P Blumberg; Lawrence H Staib
Journal:  IEEE Trans Med Imaging       Date:  2011-09-12       Impact factor: 10.048

7.  A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography.

Authors:  Iman Aganj; Christophe Lenglet; Neda Jahanshad; Essa Yacoub; Noam Harel; Paul M Thompson; Guillermo Sapiro
Journal:  Med Image Anal       Date:  2011-01-26       Impact factor: 8.545

8.  Tracking and validation techniques for topographically organized tractography.

Authors:  Dogu Baran Aydogan; Yonggang Shi
Journal:  Neuroimage       Date:  2018-07-02       Impact factor: 6.556

9.  Three-dimensional interactive and stereotactic human brain atlas of white matter tracts.

Authors:  Wieslaw L Nowinski; Beng Choon Chua; Guo Liang Yang; Guo Yu Qian
Journal:  Neuroinformatics       Date:  2012-01

Review 10.  Tractography: where do we go from here?

Authors:  Saad Jbabdi; Heidi Johansen-Berg
Journal:  Brain Connect       Date:  2011-08-30
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