Abstract #4477
Normalized Wall Thickening Patterns for Detecting Cardiac Functional Abnormality from Cine MRI Images
Mai Wael 1 , El-Sayed H. Ibrahim 2 , and Ahmed Fahmy 1
1
Nile University, Cairo, Egypt,
2
University
of Michigan, Ann Arbor, MI, United States
A method is presented for detecting regional wall motion
abnormality based on capturing the variation in
myocardial thickness during the cardiac cycle from
standard cine MRI images. The extracted wall thickness
patterns are normalized relative to the average
epicardial radius, mapped to lower dimensions using
principal component analysis, and then classified into
normal or abnormal using the maximum likelihood
criterion with leave-one-out method. The developed
method provides automatic assessment of regional
abnormality for each segment in each slice; therefore,
it could be a valuable tool for automatic and fast
determination of regional wall motion abnormality from
conventional untagged cine images.
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