Mean apparent propagator (MAP) MRI provides an efficient representation of the three-dimensional q-space signal that is used to characterize the diffusional characteristics of the tissue. The standard implementation of MAP-MRI imposes soft constraints, leaving the possibility for negative values of the propagator; we observed that such physically unjustifiable reconstructions are widespread throughout the brain. Here, we introduce a new framework based on sum-of-squares optimization that guarantees the non-negativity of the reconstructed propagator, thus yielding improved estimates of the propagator as well as the scalar measures derived from it.
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