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Abstract #5087

Automated Assessment of Ghost Artifacts in MRI

Sotirios A. Tsaftaris1,2, Xiangzhi Zhou2, Rohan Dharmakumar2

1Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, United States; 2Radiology, Northwestern University, Chicago, IL, United States

Flow artifacts in MR images can appear as image ghosts within and outside the body cavity. Technical improvements to suppress these ghosts often rely on expert scoring or on semi-automated methods demanding tissue segmentation to evaluate the efficacy of the methods. These approaches can be labor/computation intensive, introduce observer bias, or error-prone if tissue segmentation is used. Herein we propose two fully automated image-processing methods relying on the statistical properties of background pixels to assess the presence of flow artifacts (appearing as image ghosts) without requiring segmentation. We demonstrate that the automated methods are as effective as image scoring approaches that rely on expert reviewers.