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Abstract #2356

An Outlier Rejection Algorithm for ASL Time Series : Validation with ADNI Control Data

Sudipto Dolui 1,2 , Ze Wang 3,4 , David A. Wolk 1 , and John A. Detre 1,2

1 Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States, 2 Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States, 3 Hangzhou Normal University, Hangzhou, Zhejiang, China, 4 Department of Psychiatry and Radiology, University of Pennsylvania, Pennsylvania, United States

The averaging procedure in ASL MRI to overcome low SNR can be undermined by large artifacts present in only a small number of tag-control pairs. We proposed a novel method, named structural correlation based outlier rejection (SCOR), for removing outlier pairs based on i) structural similarity between mean CBF and individual CBF maps and ii) mean GM CBF of individual maps outside physiologically meaningful range. The performance of SCOR is assessed using repeated control scans obtained at 3 months interval from the ADNI database. Compared to alternative options, SCOR demonstrates superior performance by providing much better agreement between the two sessions.

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