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Abstract #2208

Structure tensor enhanced quantitative susceptibility mapping (ST-QSM)

Agnese Tamanti1, Kristian Bredies2, Marco Castellaro3, Stefan Ropele4, Berkin Bilgic5, and Christian Langkammer4

1University of Verona, Verona, Italy, 2Institute of Mathematics and Scientific Computing, University of Graz, Graz, Austria, 3Department of Information Engineering, University of Padova, Padova, Italy, 4Department of Neurology, Medical University of Graz, Graz, Austria, 5Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, MGH, Boston, MA, United States

Quantitative susceptibility mapping (QSM) is an MRI technique enabling the reconstruction of a basic physical property in vivo. However, retrieving susceptibility maps from the MRI phase data requires an ill-posed inverse problem to be solved, which is often achieved using regularization approaches. In this abstract, we extend an existing QSM algorithm by incorporating weights from the linear structure tensor (ST) of the magnitude images to stabilize the regularization. The new algorithm yields improvements regarding the visual appearance and the quantitative performance of the susceptibility maps obtained.

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