@inproceedings{5930f70d94cb4bbbbadd32c97b58fc33,
title = "Deterministic Group Tractography with Local Uncertainty Quantification",
abstract = "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.",
keywords = "Population analysis, Tractography, Uncertainty quantification",
author = "Holm, {Andreas Nugaard} and Aasa Feragen and {Dela Haije}, Tom and Sune Darkner",
year = "2019",
doi = "10.1007/978-3-030-05831-9_30",
language = "English",
isbn = "978-3-030-05830-2",
series = "Mathematics and Visualization",
publisher = "Springer",
pages = "377--386",
editor = "Bonet-Carne, {Elisenda } and Grussu, {Francesco } and Ning, {Lipeng } and Sepehrband, {Farshid } and Tax, {Chantal M. W. }",
booktitle = "Computational Diffusion",
edition = "226249",
note = "International Workshop on Computational Diffusion MRI, CDMRI 2018 held with International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2018 ; Conference date: 20-09-2018 Through 20-09-2018",
}