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Abstract #4460

Information Quantification of Subsequent Acquisitions for Minimizing Synthetic MRI Reconstruction Uncertainty

Drew Mitchell1, David Fuentes1, Jason Stafford1, James Bankson1, and Ken-Pin Hwang1

1Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States

A mutual information-based mathematical framework is developed to quantify the information content of various acquisition parameters and subsampling approaches. A recursive conditional formulation quantifies information content given previous acquisitions. This framework is applied to 3D QALAS. Mutual information between reconstructed M0, T1, and T2 uncertainty and measurement noise is calculated for an in silico phantom and the results applied to measurements on a System Standard Model 130 phantom. Reconstructions from these measurements demonstrate the potential use of information theory in guiding pulse sequence design to maximize reconstruction quality.

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