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Abstract #1355

Analyzing the Bayesian Approach to Partial Volume in Magnetic Resonance Fingerprinting

Debra McGivney1, Anagha Deshmane2, Yun Jiang2, and Mark Griswold1,2

1Radiology, Case Western Reserve University, Cleveland, OH, United States, 2Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States

We present work to optimize the parameters used in the Bayesian approach to partial volume in MRF. Care needs to be taken when choosing parameter values to balance effects from noise and over regularization of the solution. MRF brain data from a normal volunteer is analyzed to determine the optimal parameters in separating white matter from gray matter and gray matter from CSF. Parameter choices are confirmed by examining the results from our algorithm in regions of pure white matter.

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