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Abstract #1289

Motion Artifacts Reduction by Parallel Acquisition with Non-prolonged Deghosting Algorithm (PANDA)

Gaojie Zhu1, Xiang Zhou1, Hai Luo1, Bin Wang1, Xia Liu1, Ziyue Wu2, Leping Zha1,2, and Qing-San Xiang3

1Advanced Applications, Alltech Medical Systems, Chengdu, People's Republic of China, 2Advanced Applications, Alltech Medical Systems America, Solon, OH, United States, 3Radiology, University of British Columbia, Vancouver, BC, Canada

Patient motion produces artifacts in MRI due to k-space data corruption. Ghosted images can be considered as a combination of ghost-free images and ghost masks. If two ghosted images contain the same ghost-free image component and different ghost components, the images and the ghost components can be separated. For images fully sampled with array coils, multiple images can be produced with parallel reconstruction with differently selected raw data subsets. In this work, we propose a new motion artifacts reduction algorithm, which regenerates a new k-space dataset based on data consistency, and then decomposes images into mostly ghost-free images and ghost masks.

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