Model Averaging and Bootstrap Consensus‐based Uncertainty Reduction in Diffusion MRI Tractography

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dc.contributor.authorGruen, J.en_US
dc.contributor.authorvan der Voort, G.en_US
dc.contributor.authorSchultz, T.en_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-03-22T15:07:14Z
dc.date.available2023-03-22T15:07:14Z
dc.date.issued2023
dc.description.abstractDiffusion magnetic resonance imaging (dMRI) tractography has the unique ability to reconstruct major white matter tracts non‐invasively and is, therefore, widely used in neurosurgical planning and neuroscience. In this work, we reduce two sources of uncertainty within the tractography pipeline. The first one is the model uncertainty that arises in crossing fibre tractography, from having to estimate the number of relevant fibre compartments in each voxel. We propose a mathematical framework to estimate model uncertainty, and we reduce this type of uncertainty with a model averaging approach that combines the fibre direction estimates from all candidate models, weighted by the posterior probability of the respective model. The second source of uncertainty is measurement noise. We use bootstrapping to estimate this data uncertainty, and consolidate the fibre direction estimates from all bootstraps into a consensus model. We observe that, in most voxels, a traditional model selection strategy selects different models across bootstraps. In this sense, the bootstrap consensus also reduces model uncertainty. Either approach significantly increases the accuracy of crossing fibre tractography in multiple subjects, and combining them provides an additional benefit. However, model averaging is much more efficient computationally.en_US
dc.description.number1
dc.description.sectionheadersInvited Article
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14724
dc.identifier.issn1467-8659
dc.identifier.pages217-230
dc.identifier.urihttps://doi.org/10.1111/cgf.14724
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14724
dc.publisherEurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.rightsCC BY-NC Attribution-NonCommercial 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectdiffusion MRI
dc.subjecttractography
dc.subjectuncertainty
dc.subjectmodel averaging
dc.subjectbootstrapping
dc.titleModel Averaging and Bootstrap Consensus‐based Uncertainty Reduction in Diffusion MRI Tractographyen_US
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