QuickBundles, a Method for Tractography Simplification

Diffusion MR data sets produce large numbers of streamlines which are hard to visualize, interact with, and interpret in a clinically acceptable time scale, despite numerous proposed approaches. As a solution we present a simple, compact, tailor-made clustering algorithm, QuickBundles (QB), that ove...

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Main Authors: Garyfallidis, Eleftherios, Brett, Matthew, Correia, Marta Morgado, Williams, Guy B., Nimmo-Smith, Ian
Format: Online
Language:English
Published: Frontiers Media S.A. 2012
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518823/
id pubmed-3518823
recordtype oai_dc
spelling pubmed-35188232012-12-17 QuickBundles, a Method for Tractography Simplification Garyfallidis, Eleftherios Brett, Matthew Correia, Marta Morgado Williams, Guy B. Nimmo-Smith, Ian Neuroscience Diffusion MR data sets produce large numbers of streamlines which are hard to visualize, interact with, and interpret in a clinically acceptable time scale, despite numerous proposed approaches. As a solution we present a simple, compact, tailor-made clustering algorithm, QuickBundles (QB), that overcomes the complexity of these large data sets and provides informative clusters in seconds. Each QB cluster can be represented by a single centroid streamline; collectively these centroid streamlines can be taken as an effective representation of the tractography. We provide a number of tests to show how the QB reduction has good consistency and robustness. We show how the QB reduction can help in the search for similarities across several subjects. Frontiers Media S.A. 2012-12-11 /pmc/articles/PMC3518823/ /pubmed/23248578 http://dx.doi.org/10.3389/fnins.2012.00175 Text en Copyright © 2012 Garyfallidis, Brett, Correia, Williams and Nimmo-Smith. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Garyfallidis, Eleftherios
Brett, Matthew
Correia, Marta Morgado
Williams, Guy B.
Nimmo-Smith, Ian
spellingShingle Garyfallidis, Eleftherios
Brett, Matthew
Correia, Marta Morgado
Williams, Guy B.
Nimmo-Smith, Ian
QuickBundles, a Method for Tractography Simplification
author_facet Garyfallidis, Eleftherios
Brett, Matthew
Correia, Marta Morgado
Williams, Guy B.
Nimmo-Smith, Ian
author_sort Garyfallidis, Eleftherios
title QuickBundles, a Method for Tractography Simplification
title_short QuickBundles, a Method for Tractography Simplification
title_full QuickBundles, a Method for Tractography Simplification
title_fullStr QuickBundles, a Method for Tractography Simplification
title_full_unstemmed QuickBundles, a Method for Tractography Simplification
title_sort quickbundles, a method for tractography simplification
description Diffusion MR data sets produce large numbers of streamlines which are hard to visualize, interact with, and interpret in a clinically acceptable time scale, despite numerous proposed approaches. As a solution we present a simple, compact, tailor-made clustering algorithm, QuickBundles (QB), that overcomes the complexity of these large data sets and provides informative clusters in seconds. Each QB cluster can be represented by a single centroid streamline; collectively these centroid streamlines can be taken as an effective representation of the tractography. We provide a number of tests to show how the QB reduction has good consistency and robustness. We show how the QB reduction can help in the search for similarities across several subjects.
publisher Frontiers Media S.A.
publishDate 2012
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3518823/
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