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Abstract #1206

Reconstruction of DCE tracer kinetic parameters from under-sampled data with a flexible model consistency constraint

Yi Guo1, Sajan Goud Lingala1, and Krishna S Nayak1

1Electrical Engineering, University of Southern California, Los Angeles, CA, United States

Recently, it has been shown that DCE-MRI tracker-kinetic (TK) parameter maps can be directly estimated from under-sampled (k,t)-space data. Two major limitations of this approach are that 1) the gradient of a complicated cost function with respect to each TK parameter needs to be computed, and 2) it does not allow for any TK model deviation in the data. In this work, we present an alternative formulation where instead of forcing every voxel to follow the selected TK model, the model consistency is used as a constraint with a weighting penalty. This method is uniquely compatible with the use of multiple or nested TK models, and we show that it provides more accurate TK parameter restoration.

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