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. Nagel^1,5

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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