Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spectral Grouping Using the Nyström Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Unsupervised Classification of Calcified Arterial Lesions
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
International Journal of Computer Vision
Volumetric Shape Model for Oriented Tubular Structure from DTI Data
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Probabilistic clustering and quantitative analysis of white matter fiber tracts
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Nonlinear registration of diffusion MR images based on fiber bundles
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Coclustering for cross-subject fiber tract analysis through diffusion tensor imaging
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Hierarchical fiber clustering based on multi-scale neuroanatomical features
MIAR'10 Proceedings of the 5th international conference on Medical imaging and augmented reality
Automated atlas-based clustering of white matter fiber tracts from DTMRI
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
High-Dimensional white matter atlas generation and group analysis
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Fiber segmentation using constrained clustering
ICMB'10 Proceedings of the Second international conference on Medical Biometrics
Abstractive representation and exploration of hierarchically clustered diffusion tensor fiber tracts
EuroVis'08 Proceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization
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We present a novel method for finding white matter fiber correspondences and clusters across a population of brains. Our input is a collection of paths from tractography in every brain. Using spectral methods we embed each path as a vector in a high dimensional space. We create the embedding space so that it is common across all brains, consequently similar paths in all brains will map to points near each other in the space. By performing clustering in this space we are able to find matching fiber tract clusters in all brains. In addition, we automatically obtain correspondence of tractographic paths across brains: by selecting one or several paths of interest in one brain, the most similar paths in all brains are obtained as the nearest points in the high-dimensional space.