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Abstract #0084

Multiscale Image Reconstruction for MR Fingerprinting

Eric Y. Pierre 1 , Dan Ma 1 , Yong Chen 2 , Chaitra Badve 2 , and Mark A. Griswold 1,2

1 Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, United States, 2 Department of Radiology, Case Western Reserve University & University Hospitals, Cleveland, Ohio, United States

To perform parameter mapping, Magnetic Resonance Fingerprinting (MRF) relies on highly efficient, highly undersampled trajectories to acquire the image series, yielding images contaminated by high aliasing noise. We propose an iterative multiscale method to denoise these images so as to reduce the length of image series required for accurate parameter mapping. The proposed method is shown to allow the simultaneous T1, T2, field inhomogeneity and proton density estimation at 1.17 mm 2 resolution in vivo from a single 5.1s acquisition, representing a potential 4-fold increase in acquisition speed for MRF methods.

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