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Abstract #3607

Three-dimensional cardiac T1 mapping using subspace and sparsity constrained direct estimation

Thibault Marin1, Paul K. Han1, Yue Zhuo1, Yanis Djebra1,2, Fang Liu1, Georges El Fakhri1, and Chao Ma1
1Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, 2LTCI, Telecom Paris, Institut Polytechnique de Paris, Paris, France

Cardiac T1 mapping is a powerful MR imaging technique for quantitative assessment of microstructural changes in myocardial tissues. Existing methods are limited in terms of spatial coverage and through-plane resolution due to limitations in acquisition speed and the presence of cardiac and respiratory motion. This work presents a direct reconstruction framework, which allows estimation of 3D T1 maps from sparsely sampled k-space data using physical modeling through the Bloch equation, low-rank constraints on the dynamic images and sparsity constraints on the estimated T1 maps.

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