Reliable shape modeling and clustering of white matter fiber tracts is essential for clinical and anatomical studies that use diffusion tensor imaging (DTI) tractography techniques...
In this paper, we present a kernel-based approach to the clustering of diffusion tensors and fiber tracts. We propose to use a Mercer kernel over the tensor space where both spati...
A statistical model of the fiber bundles is calculated as the average and standard deviation of a parametric representation of the fiber tracts, using the coefficients of the 3D q...
Mahnaz Maddah, W. Eric L. Grimson, Simon K. Warfie...
A new framework is presented for clustering fiber tracts into anatomically known bundles. This work is motivated by medical applications in which variation analysis of known bundle...
Mahnaz Maddah, Andrea J. U. Mewes, Steven Haker, W...
Diffusion tensor imaging (DTI) has become the major modality to study properties of white matter and the geometry of fiber tracts of the human brain. Clinical studies mostly focus ...
Isabelle Corouge, P. Thomas Fletcher, Sarang C. Jo...
We propose a manifold learning approach to fiber tract clustering using a novel similarity measure between fiber tracts constructed from dual-rooted graphs. In particular, to gene...
Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero, Al...