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Abstract #3072

Compressed Sensing with Signal Averaging Reduces Motion Artifacts in Fluorine-19 MRI

Emeline Darçot1, Jerome Yerly1,2, Tom Hilbert1,3,4, Roberto Colotti1, Maxime Pellegrin5, Elena Najdenovska1,2, Tobias Kober1,3,4, Matthias Stuber1,2, and Ruud B van Heeswijk1

1Radiology, University Hospital of Lausanne (CHUV)-University of Lausanne (Unil), Lausanne, Switzerland, 2Center for Biomedical Imaging (CIBM), Lausanne, Geneva, Switzerland, 3Advanced Clinical Imaging Technology (HC CMEA SUI DI PI), Siemens Healthcare AG, Lausanne, Switzerland, 4Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 5Angiology service, University Hospital of Lausanne (CHUV)-University of Lausanne (Unil), Lausanne, Switzerland

In addition to conventional signal averaging, compressed sensing (CS) can be applied to fluorine-19 MRI to improve its low signal-to-noise ratio. For a given acquisition time and CS algorithm, an N-averages N-fold-undersampled dataset results in higher sensitivity than a fully sampled non-averaged dataset. However, it is still unclear whether averaging changes the sensitivity to motion artifacts for an undersampled acquisition.We therefore tested the hypothesis that an N-averages N-fold undersampled acquisition is more robust against motion artifacts than a fully sampled non-averaged acquisition when both are reconstructed with CS.

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