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Abstract #1304

Iterative Reconstruction of 23Na Multi-Channel Breast Data Using Compressed Sensing Combined with Anatomical 1H Prior Knowledge

Sebastian Lachner1, Olgica Zaric2, Matthias Utzschneider1, Lenka Minarikova2, Stefan Zbyn3, Bernhard Hensel4, Siegfried Trattnig2, Michael Uder1, and Armin M. Nagel1,5

1Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 2High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 3Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland, 4Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany, 5Division of Medical Physics in Radiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany

An iterative reconstruction algorithm for sodium magnetic resonance imaging (23Na MRI) with multi-channel receiver coils is implemented and compared to a conventional gridding reconstruction. Based on compressed sensing (CS) it utilizes a total variation (TV(2)), combined with anatomical weighting factors (AnaWeTV(2)) to preserve known tissue boundaries. Simulated and measured 23Na multi-channel data sets of the female breast were reconstructed. The TV(2) and in particular the AnaWeTV(2) lead to an improved image quality, due to effective noise reduction and the highlighting of structure. The presented CS reconstruction is beneficial especially for high undersampling factors.

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