Track-Density Imaging & Noise: When Super-Resolution Quality Does Not Yield Accuracy

Thijs Dhollander¹, ², Louise Emsell¹, ³, Wim Van Hecke¹, ³, Frederik Maes¹, ², Stefan Sunaert¹, ³, Paul Suetens¹, ²

Track-density imaging (TDI) is a recently proposed technique to achieve super-resolution from diffusion weighted imaging datasets, by performing massive fiber tracking and counting the tracks in each voxel of a high resolution grid. In this work, the effect of noise in the data on the final TDI is investigated. The findings indicate that caution is needed: many discovered patterns of structures might mostly be caused by noise rather than true anatomy, although they look plausible and do not resemble the traditional impression of noise. Tools such as bootstrapping, combined with certain maps can highlight regions where caution is due.