Abstract #0120

Image quality transfer benefits tractography of low-resolution data

Daniel C. Alexander¹, Aurobrata Ghosh¹, Samuel A. Hurley², and Stamatios N. Sotiropoulos²

¹Computer Science, UCL, London, United Kingdom, ²FMRIB, Oxford University, Oxford, United Kingdom

We show benefits of image quality transfer to tractography. Diffusion MRI super-resolution through image quality transfer enables recovery of thin tracts in a dataset with low spatial resolution (2.5mm isotropic). Specifically, we reconstruct four pathways arising from the motor area that have been distinguished before when using high (1.25mm) resolution HCP data. Quantitative results confirm that image quality transfer enhances tractography more than standard interpolation. The results highlight the major potential of image quality transfer in learning information from bespoke high quality data sets to enhance the specificity of information derived from more modest but readily available data.

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