The Partial Volume Problem in MR Fingerprinting from a Bayesian Perspective
Debra F. McGivney1, Anagha Deshmane2, Yun Jiang2, Dan Ma1, and Mark A. Griswold1
1Radiology, Case Western Reserve University, Cleveland, OH, United States, 2Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
Magnetic resonance fingerprinting (MRF) is a technique that allows us to produce quantitative maps of tissue parameters such as T1 and T2 relaxation times, however it is susceptible to artifacts due to the partial volume effect. The aim of this work is to provide a blind solution to the partial volume problem in MRF using the Bayesian statistical framework. A complete description of the algorithm is presented as well as applications to in vivo data.
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