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Abstract #3956

Spatial biases in Magnetic Resonance Fingerprinting parameter maps arising from undersampling patterns

Gregor Körzdörfer1,2, Thomas Kluge1, Josef Pfeuffer1, Matthias Gebhardt3, Dan Ma4, Yun Jiang4, Mark Griswold4,5, and Mathias Nittka1

1Application Development, Siemens Healthcare, Erlangen, Germany, 2Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany, 3Physics department, Siemens Healthcare, 4Department of Biomedical Engineering, Case Western Reserve University, OH, United States, 5Dept. of Radiology, Case Western Reserve University and University Hospitals of Cleveland, OH, United States

Magnetic Resonance Fingerprinting (MRF) is an MR technique that generates parameter maps by matching pseudo randomly generated MR signals with a precalculated dictionary. In order to acquire the signals in a reasonable time, rapid imaging techniques with high undersampling factors are necessary. We show a detailed analysis of the artifacts originating from this and their impact on measured signals and subsequently on parameter maps. Additionally, an analytical approach of predicting undersampling artifacts is proposed. With the help of this approach, a more robust and time efficient sampling of signals in MRF can be designed.

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