A Novel Global Tractography Algorithm Based on an Adaptive Spin Glass Model

This paper introduces a novel framework for global diffusion MRI tractography inspired from a spin glass model. The entire white matter fascicle map is parameterized by pieces of fibers called spins. Spins are encouraged to move and rotate to align with the main fiber directions, and to assemble into longer chains of low curvature. Moreover, they have the ability to adapt their quantity in regions where the spin concentration is not sufficient to correctly model the data. The optimal spin glass configuration is retrieved by an iterative minimization procedure, where chains are finally assimilated to fibers. As a result, all brain fibers appear as growing simultaneously until they merge with other fibers or reach the domain boundaries. In case of an ambiguity within a region like a crossing, the contribution of all neighboring fibers is used determine the correct neural pathway. This framework is tested on a MR phantom representing a 45 degrees crossing and a real brain dataset. Notably, the framework was able to retrieve the triple crossing between the callosal fibers, the corticospinal tract and the arcuate fasciculus.