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Abstract #3622

General Closed-Form Expressions for DKI Parameters and Their Application to Fast and Robust DKI Computation Based on Outlier Removal

Yoshitaka Masutani1, Shigeki Aoki2

1Radiology, The University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan; 2Radiology, Juntendo Hospital, Bunkyo-ku, Tokyo, Japan

Non-Gaussianity quantification of water diffusion through diffusional kurtosis imaging (DKI) is expected in clinical applications such as classification of abnormal tissues. For faster computation of DKI parameters; K, D, and S0, we show that it is possible to obtain general closed-form expressions also for data sets by more than three b-values. In addition, we propose a fast and robust computation technique based on greedy removal of outlier sample pair of b-value and DWI signal. By using six data sets of brain from clinical MR scanner, the technique was proved to be fast, robust and effective for clinical DKI.