Myocardial Tissue Characterization Using Pattern Recognition Procedures on Backscattered Ultrasonic Signals

Pattern recognition techniques were applied to backscattered signals obtained in vitro from normal and abnormal canine and human heart samples. Orthogonal transforms, in conjunction with the variance criterion, comprised the feature extractors. The minimum-distance (MD) and nearest-neighbor (NN) rules were used as classifiers. When the MD rule was used, the magnitude of the DFT gave the best performance for both canine and human samples. When the NN rule was used, all the transforms performed comparably. The classification performances were improved for both species when the NN rule was used with feature extractors containing phase information.