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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