Abstract #1019

A novel fat and iron quantification technique with non-rigid motion-corrected averaging based on non-local means

Huiwen Luo^1,2, Curtis Wiens¹, Ann Shimakawa³, Scott B. Reeder^1,4,5,6,7, Kevin M. Johnson^1,4, and Diego Hernando^1,4

¹Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Electronic engineering, Tsinghua University, Beijing, People's Republic of China, ³Global MR Applications and Workflow, GE Healthcare, Madison, WI, United States, ⁴Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ⁵Biomedical engineering, University of Wisconsin-Madison, Madison, WI, United States, ⁶Medicine, University of Wisconsin-Madison, Madison, WI, United States, ⁷Emergency Medicine, University of Wisconsin-Madison, Madison, WI, United States

In this study, we developed and validated a free-breathing fat and R2* quantification technique using a multi-average 2D sequential acquisition with non-rigid motion-corrected averaging based on a non-local means (NLM) approach. The proposed technique was applied to simulated data as well as free-breathing liver acquisitions in volunteers. Both direct averaging and the proposed NLM technique were applied to the data to improve SNR. Compared to direct averaging, the proposed NLM technique resulted in improved image quality without motion artifacts, as well as accurate fat and R2* measurements in both simulations and in vivo acquisitions.

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