Literature DB >> 12489097

A framework based on spin glass models for the inference of anatomical connectivity from diffusion-weighted MR data - a technical review.

J-F Mangin1, C Poupon, Y Cointepas, D Rivière, D Papadopoulos-Orfanos, C A Clark, J Régis, D Le Bihan.   

Abstract

A family of methods aiming at the reconstruction of a putative fascicle map from any diffusion-weighted dataset is proposed. This fascicle map is defined as a trade-off between local information on voxel microstructure provided by diffusion data and a priori information on the low curvature of plausible fascicles. The optimal fascicle map is the minimum energy configuration of a simulated spin glass in which each spin represents a fascicle piece. This spin glass is embedded into a simulated magnetic external field that tends to align the spins along the more probable fiber orientations according to diffusion models. A model of spin interactions related to the curvature of the underlying fascicles introduces a low bending potential constraint. Hence, the optimal configuration is a trade-off between these two kind of forces acting on the spins. Experimental results are presented for the simplest spin glass model made up of compass needles located in the center of each voxel of a tensor based acquisition. Copyright 2002 John Wiley & Sons, Ltd.

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Year:  2002        PMID: 12489097     DOI: 10.1002/nbm.780

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  14 in total

1.  MR tractography with diffusion tensor imaging in clinical routine.

Authors:  T H Nguyen; M Yoshida; J L Stievenart; M T Iba-Zizen; L Bellinger; A Abanou; K Kitahara; E A Cabanis
Journal:  Neuroradiology       Date:  2005-04-19       Impact factor: 2.804

2.  Probabilistic anatomical connectivity derived from the microscopic persistent angular structure of cerebral tissue.

Authors:  Geoffrey J M Parker; Daniel C Alexander
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-05-29       Impact factor: 6.237

3.  Preliminary experience with visualization of intracortical fibers by focused high-resolution diffusion tensor imaging.

Authors:  T Jaermann; N De Zanche; P Staempfli; K P Pruessmann; A Valavanis; P Boesiger; S S Kollias
Journal:  AJNR Am J Neuroradiol       Date:  2007-10-18       Impact factor: 3.825

4.  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

5.  Tracking and validation techniques for topographically organized tractography.

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

6.  Quantitative assessment of a framework for creating anatomical brain networks via global tractography.

Authors:  Longchuan Li; James K Rilling; Todd M Preuss; Matthew F Glasser; Frederick W Damen; Xiaoping Hu
Journal:  Neuroimage       Date:  2012-03-30       Impact factor: 6.556

7.  Simultaneous multi-scale diffusion estimation and tractography guided by entropy spectrum pathways.

Authors:  Vitaly L Galinsky; Lawrence R Frank
Journal:  IEEE Trans Med Imaging       Date:  2014-12-18       Impact factor: 10.048

Review 8.  Diffusion MRI at 25: exploring brain tissue structure and function.

Authors:  Denis Le Bihan; Heidi Johansen-Berg
Journal:  Neuroimage       Date:  2011-11-20       Impact factor: 6.556

9.  Improving DTI tractography by including diagonal tract propagation.

Authors:  Paul A Taylor; Kuan-Hung Cho; Ching-Po Lin; Bharat B Biswal
Journal:  PLoS One       Date:  2012-09-06       Impact factor: 3.240

10.  Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging.

Authors:  Muriel Perrin; Yann Cointepas; Arnaud Cachia; Cyril Poupon; Bertrand Thirion; Denis Rivière; Pascal Cathier; Vincent El Kouby; André Constantinesco; Denis Le Bihan; Jean-François Mangin
Journal:  Int J Biomed Imaging       Date:  2008
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