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Abstract #5162

A new pattern for Autocalibrated Parallel Imaging Reconstruction for GRASE: APIR4GRASE

Chaoping Zhang1, Alexandra Cristobal-Huerta2, Juan Antonio Hernández-Tamames2, Stefan Klein1, and Dirk H.J. Poot1,2,3

1Departments of Medical Informatics and Radiology, Erasmus MC, Rotterdam, Netherlands, 2Departments of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, 3Imaging Science and Technology, Delft University of Technology, Delft, Netherlands

We propose a subsampled interleaved parallel acquisition pattern for Autocalibrated Parallel Imaging Reconstruction for GRASE (APIR4GRASE) which considers different echoes during each refocusing of the GRASE as if they originated from different coil channels. APIR4GRASE eliminates ghosting artifacts caused by the phase and amplitude modulations in traditional GRASE split sampling pattern and achieves an additional acceleration factor of 1.3 compared to a fully sampled GRASE k-space. In addition, multiple contrast (spin echo and gradient echo) images are reconstructed. Experiments on a phantom demonstrate the effectiveness of our method.

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