Abstract #3072

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

Emeline Darçot¹, Jerome Yerly^1,2, Tom Hilbert^1,3,4, Roberto Colotti¹, Maxime Pellegrin⁵, Elena Najdenovska^1,2, Tobias Kober^1,3,4, Matthias Stuber^1,2, 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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