Abstract #0435

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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