Abstract #1541

SAFT: Split-Algorithm for Fast T2 Mapping

Tom Hilbert^1,2,3, Jean-Philippe Thiran^2,3, Reto Meuli², Gunnar Krueger^2,3,4, and Tobias Kober^1,2,3

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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