Myocardial tissue characterization using pattern recognition procedures on backs cattered ultrasonic signals

Abstract

Pattern recognition techniques were applied to backacattered signals obtained in vitro from normal and abnormal canine and human heart samples. Orthogonal tranaforms, 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.