Can Model Weighting Improve the Accuracy of DCE-MRI Parameter Estimation?

Many pharmacokinetic models have been proposed for analyzing dynamic contrast enhanced MRI with different assumptions. It is difficult to select which model is most appropriate for a particular study. To address this limitation, we have taken an approach in which multiple models are weighted by a factor determined by how well they fit the data. We analyze each voxel in a DCE-MRI data set with an array of models and compute the Akaike Information Criteria for each fit. The AIC is then used to determine the statistically optimal model on a voxel-by-voxel basis.

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