Diffusion MRI is a powerful approach to quantify brain architecture. However, diffusion scalar maps derived from raw data are sensitive to the data quality and processing choices. Many quality control algorithms exist that perform a robust check of raw diffusion data, there is a lack of QCs for inspecting the derived maps from different diffusion approaches. We present a novel QC algorithm for processed scalar maps using mean skeleton values (in the context of tract-based spatial statistics) and structural similarity metric based on the scalar maps. The algorithm builds on clustering of scalar diffusion metrics from 18609 UK Biobank individuals.
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