Constrained diffusion kurtosis imaging using ternary quartics & MLE

Diffusion kurtosis imaging (DKI) is a recent improvement over diffusion tensor imaging that characterizes tissue by quantifying non‐gaussian diffusion using a 3D fourth‐order kurtosis tensor. DKI needs to consider three constraints to be physically relevant. Further, it can be improved by considering the Rician signal noise model. A DKI estimation method is proposed that considers all three constraints correctly, accounts for the signal noise and incorporates efficient gradient‐based optimization to improve over existing methods.

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