Xinjiang Local Liver Hydatid CT Images Classification and Research based -wavelet Transform
KONG Ximei
Murat Hamit
YAN Chuanbo
YAO Juan
SUN Jing
Abstract：To explore classification value for Xinjiang local liver hydatid using two kinds of wavelet transform methods.This two methods consists of sym4 and db4 wavelet.Two wavelet methods were used to extract texture feature of region of interest focal zone,sta-tistical method was used to select the optimal texture feature from the set of extracted features.The C4.5 Decision Tree was employed as a classifier.The results of C4.5 Decision Tree for sym4 and db4 wavelet analysis methods were evaluated using accuracy,sensitivity and specificity and the area under the ROC curve(AUC).The results showed that the accuracy rate of sym4 wavelet classifing normal liver and poly -cystic liver hydatid reached to 92.5%;the accuracy rate of db4 wavelet classification reached to 97.5%.The experimental results show that db4 wavelet methods is able to achieve higher classification accuracy effectiveness,it can lay a foundation which is subsequent based -content diagnostic system of Xinjiang local liver hydatid.
Keywords：Xinjiang Local Liver HydatidWavelet transformationRegion of InterestC4.5 Decision TreeModel evaluation
Publication Date：2016-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：7( 162-167,174 )