Software at CIS : lddmm-dti : About

Diffusion Tensor Imaging (DTI) probes and quantifies the anisotropic diffusion of water molecules in biological tissues, making it possible to noninvasively infer the architecture of the underlying structures. The measurement at each voxel in a DTI image volume is a symmetric second order tensor. Orientation of the principle eigenvector of the diffusion tensor is known to align with fibre tracts in the brain. Consequently, DTI is becoming a routine magnetic resonance imaging technique for studying fiber orientation in biological tissue.

lddmm-dti-vector is a program for large deformation diffeomorphic metric mapping of vector fields. The optimal mapping is the endpoint of a geodesic path on the manifold of diffeomorphisms connecting two vector fields. Finding the optimal mapping and the geodesic path is formulated as a variational problem over a vector field. The variational optimization of the energy functional is performed in a steepest descent scheme. A coarse to fine multi-resolution matching strategy is used to reduce ambiguity issues and computation load.

lddmm-dti-tensor is a program for large deformation diffeomorphic metric mapping of tensor fields. The optimal mapping is the endpoint of a geodesic path on the manifold of diffeomorphisms connecting two tensor fields. Finding the optimal mapping and the geodesic path is formulated as a variational problem over a vector field. The variational optimization of the energy functional is performed in a steepest descent scheme. A hierarchical multi-resolution and multi-kernel-width matching strategy is used to reduce ambiguity issues and computation load.

Last Modified: Monday, 25th April, 2011 @ 11:19am