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Abstract #1541

SAFT: Split-Algorithm for Fast T2 Mapping

Tom Hilbert1,2,3, Jean-Philippe Thiran2,3, Reto Meuli2, Gunnar Krueger2,3,4, and Tobias Kober1,2,3

1Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland, 2Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 3LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 4Siemens Medical Solutions USA, Inc., Boston, MA, United States

Numerous iterative reconstruction techniques have been published in the past, facilitating the calculation of quantitative parameter maps based on undersampled k-space data. Model-based approaches, for example, iteratively minimize a cost function that comprises a formulation of the signal behavior. Minimizing this non-linear problem yields the quantitative parameter maps, but is numerically challenging and thus accompanied with reduced robustness and long reconstruction times compared to a direct Fourier transform. Here we suggest a method to split the optimization problem of a model-based T2 mapping into sub-problems which are solved alternately. The splitting results in a more robust reconstruction with less computational cost.

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