Journal
FRONTIERS IN NEUROSCIENCE
Volume 6, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2012.00175
Keywords
tractography; diffusion MRI; fiber clustering; white matter segmentation; dimensionality reduction; clustering algorithms; DTI
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Funding
- Medical Research Council [MC_U105579212] Funding Source: researchfish
- MRC [MC_U105579212] Funding Source: UKRI
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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.
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