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Abstract #1472

Using Second Order Statistic Analysis of Images to Quantify and Optimize Parallel Acquisition Strategies for 3He MRI of Human Lung

Maxim Terekhov1, Julien Rivoire1, Ursula Wolf2, Christian Hoffmann2, Janet Friedrich1, Sergej Karpuk3, Laura Maria Schreiber1

1Department of Radiology, Section of Medical Physics, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany; 2Department of Radiology, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany; 3Institute of Physics, Johannes Gutenberg University, Mainz, Germany

The parallel acquisition being used for hyperpolarized 3He lung MRI significantly gain the signal-to-noise ratio of images by reducing amount of phase encodings and using higher flip angle. Because of the magnetization losses in each rf-excitation the k-space is always weighted by encoding trajectory and flip angle leading to trade-off between SNR and image low-pass filtering. In general, the changes in arbitrary direction and distance can be described by texturebased second order statistic of the morphology. In this work we perform the gray-level-cooccurrence-matrix analysis of the 3He lung images to improve the optimization strategy for the parallel 3He MRI.