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Abstract #2933

Model Regularization with Blind Deconvolution

Jacob U. Fluckiger1, Matthias C. Schabel1, Edward VR DiBella1

1University of Utah, Salt Lake City, UT, USA

We have developed an alternating minimization with model (AMM) algorithm for estimating the arterial input function directly from measured tissue activity curves. This method uses an analytic form for the AIF to regularize noise in measured DCE-MRI data. Simulations show the AMM method performs nearly as well as conventional deconvolution with a known AIF.