@inproceedings{b0b5d264d42743c496b49f2c70191b8e,
title = "Level set and region based surface propagation for diffusion tensor MRI segmentation",
abstract = "Diffusion Tensor Imaging (DTI) is a relatively new modality for human brain imaging. During the last years, this modality has become widely used in medical studies. Tractography is currently the favorite technique to characterize and analyse the structure of the brain white matter. Only a few studies have been proposed to group data of particular interest. Rather than working on extracted fibers or on an estimated scalar value accounting for anisotropy as done in other approaches, we propose to extend classical segmentation techniques based on surface evolution by considering region statistics defined on the full diffusion tensor field itself. A multivariate Gaussian is used to approximate the density of the components of diffusion tensor for each sub-region of the volume. We validate our approach on synthetical data and we show promising results on the extraction of the corpus callosum from a real dataset.",
author = "Mika{\"e}l Rousson and Christophe Lenglet and Rachid Deriche",
year = "2004",
month = jan,
day = "1",
language = "English (US)",
isbn = "3540226753",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer- Verlag",
pages = "123--134",
editor = "Milan Sonka and Kakadiaris, {Ioannis A.} and Jan Kybic",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
note = "International Workshop on Computer Vision Approaches to Medical Image Analysis, CVAMIA 2004 and International Workshop on Mathematical Methods in Biomedical Image Analysis, MMBIA 2004 held in conjunction with 8th European Conference on Computer Vision, ECCV 2004 ; Conference date: 15-05-2004 Through 15-05-2004",
}