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Abstract #0385

Fast Relaxation Parameter Mapping from Undersampled Data

Mariya Doneva1, Christian Stehning2, Peter Brnert2, Holger Eggers2, Alfred Mertins1

1University of Luebeck, Luebeck, Germany; 2Philips Research Europe, Hamburg, Germany

The quantitative assessment of MR parameters like T1, T2, ADC, etc. requires the acquisition of multiple images of the same anatomy, which results in long scan times. However, these data can be described by a model with only a few parameters and in that sense they are highly compressible. Thus, Compressed Sensing (CS) could be applied to accelerate the data acquisition. In this work we introduce a model-based reconstruction from undersampled data, which performs simultaneous image reconstruction and parameter mapping and demonstrate it for the example of T1 mapping.