To solve problems such as low recognition rate of abnormal cross section and inability to rule out special structural effects,a method based on one-class support vector machine(OCSVM)is proposed to detect coronary lesion.By using coronary cross section resampling and feature selection based on maximum mutual information,the method achieves a relatively high recognition rate.At first,the coronary cross section is resampled based on gradient flux using cubic spline interpolation,and multi-scale feature vector...
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