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Abstract #3131

High-Resolution Diffusion Kurtosis Imaging (DKI) Enabled by Segmented Position Orientation Adaptive Smoothing (POAS)

Siawoosh Mohammadi1, Karsten Tabelow2, Thorsten Feiweier3, Joerg Polzehl2, Nikolaus Weiskopf1

1Wellcome Trust Centre for Neuroimaging at UCL, ION UCL, UCL, London, United Kingdom; 2Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany; 3Healthcare Sector, Siemens AG, Erlangen, Bayern, Germany


Recent studies suggest that Diffusion Kurtosis Imaging (DKI) is more sensitive to gray microstructure than the well-known diffusion tensor imaging (DTI). However, DKI suffers from a low signal-to-noise ratio (SNR), since it is based on multiple and high b-value data. Thus, in-vivo high-resolution DKI with small voxel sizes has not been available on clinical scanners. We aimed to overcome the low SNR issue by using a novel version of the position orientation adaptive smoothing (POAS), which is separately applied on grey and white matter masks.