MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Conditional Correlation as a Measure of Mediated Interactivity in fMRI and MEG/EEG
IEEE Transactions on Signal Processing
Tubular Anisotropy Segmentation
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Airway Tree Extraction with Locally Optimal Paths
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Brain Connectivity Using Geodesics in HARDI
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Geodesic Methods in Computer Vision and Graphics
Foundations and Trends® in Computer Graphics and Vision
Tubular Structure Segmentation Based on Minimal Path Method and Anisotropic Enhancement
International Journal of Computer Vision
Blood flow computation in phase-contrast MRI by minimal paths in anisotropic media
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
CUDA-accelerated geodesic ray-tracing for fiber tracking
Journal of Biomedical Imaging - Special issue on Parallel Computation in Medical Imaging Applications
Globally minimal path method using dynamic speed functions based on progressive wave propagation
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
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Using geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method optimises a global criterion, and hence is less sensitive to local perturbations such as noise or partial volume effects, and (ii) the method is fast, allowing to infer on a large number of connexions in a reasonable computational time. Here, we propose an improved fast marching algorithm to infer on geodesic paths. Specifically, this procedure is designed to achieve accurate front propagation in an anisotropic elliptic medium, such as DTI data. We evaluate the numerical performance of this approach on simulated datasets, as well as its robustness to local perturbation induced by fiber crossing. On real data, we demonstrate the feasibility of extracting geodesics to connect an extended set of brain regions.