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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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