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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