Purpose. To develop a method for identifying abnormalmyocardial function based on studying the normalized wallmotion pattern\nduring the cardiac cycle. Methods. The temporal pattern of the normalized myocardial wall thickness is used as a feature vector to\nassess the cardiac wall motion abnormality. Principal component analysis is used to reduce the feature dimensionality and the\nmaximum likelihood method is used to differentiate between normal and abnormal features. The proposed method was applied on\na dataset of 27 cases from normal subjects and patients. Results.The developed method achieved 81.5%, 85%, and 88.5% accuracy\nfor identifying abnormal contractility in the basal, midventricular, and apical slices, respectively. Conclusions. A novel feature\nvector, namely, the normalized wall thickness, has been introduced for detecting myocardial regional wall motion abnormality.\nThe proposed method provides assessment of the regional myocardial contractility for each cardiac segment and slice; therefore,\nit could be a valuable tool for automatic and fast determination of regional wall motion abnormality from conventional cine MRI\nimages.
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