Deterministic Group Tractography with Local Uncertainty Quantification

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

While tractography is routinely used to trace the white-matter connectivity in individual subjects, the population analysis of tractography output is hampered by the difficulty of comparing populations of curves. As a result, analysis is often reduced to population summaries such as TBSS, or made pointwise with similar interaction of remote and nearby tracts. As an easy-to-use alternative, we propose population-wide tractography in MNI space, by simultaneously considering diffusion data from the entire population, registered to MNI. We include voxel-wise quantification of population variability as a measure of uncertainty. The group tractography algorithm is illustrated on a population of subjects from the Human Connectome Project, obtaining robust population estimates of the white matter tracts.

Original languageEnglish
Title of host publicationComputational Diffusion : International MICCAI Workshop, Granada,
EditorsElisenda Bonet-Carne, Francesco Grussu, Lipeng Ning, Farshid Sepehrband, Chantal M. W. Tax
PublisherSpringer
Publication date2019
Edition226249
Pages377-386
ISBN (Print)978-3-030-05830-2
ISBN (Electronic)978-3-030-05831-9
DOIs
Publication statusPublished - 2019
EventInternational Workshop on Computational Diffusion MRI, CDMRI 2018 held with International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 - Granada, Spain
Duration: 20 Sep 201820 Sep 2018

Conference

ConferenceInternational Workshop on Computational Diffusion MRI, CDMRI 2018 held with International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018
LandSpain
ByGranada
Periode20/09/201820/09/2018
SeriesMathematics and Visualization
ISSN1612-3786

    Research areas

  • Population analysis, Tractography, Uncertainty quantification

ID: 223569891