Fiber tractography using entropy spectrum pathways

A method for fiber tractography, comprising:

• acquiring, via an imaging system, diffusion weighted MRI data comprising a plurality of voxels, wherein the plurality of voxels defines a lattice, each voxel connected by a path;
• inputting the MRI data into a computer processor data having instructions stored therein for causing the computer processor to execute the steps of:
• calculating intravoxel diffusion characteristics from the MRI data;
• calculating a transition probability for each path on the lattice, wherein the transition probability is weighted according the intravoxel characteristics;
• calculating an entropy for each path;
• ranking the paths between two voxels according to entropy to determine a maximum entropy;
• calculating a connection between a global structure of the probability with a local structure of the lattice for one or more highest ranked paths;
• determining one or more fiber tracts corresponding to the highest ranked paths using ray tracing, wherein potential equals entropy;
• and
• generating an output comprising a display corresponding to the one or more fiber tracts.

A method for fiber tractography, comprising:

• acquiring, via an imaging system, multi-shell diffusion weighted MRI data comprising a plurality of voxels, wherein the plurality of voxels define locations on a lattice, each location connected by a path;
• in a computing device, executing the steps of:
• performing a spherical wave decomposition on the data to define a set of spherical wave decomposition coefficients;
• using the spherical wave decomposition coefficients, generating a coupling matrix for diffusion connectivity at multiple scales, wherein the coupling matrix defines interactions between locations on the lattice;
• using the coupling matrix, computing transition probabilities and equilibrium probabilities for a plurality of interactions between locations on the lattice;
• using the computed transition probabilities to represent angular and scale distributions of potential paths between locations on the lattice;
• applying a geometric optics tractography algorithm to the transition probabilities to construct possible pathways, each possible pathway having an eigenvector and an eigenvalue;
• calculating eigenmodes for the possible pathways;
• ranking the possible pathways according to their eigenmode;
• defining a preselected number of pathways from the ranked pathways;
• and
• displaying the preselected number of pathways on a visual display.