Features extraction algorithm of CT image based on GNSCT-LCM
Zhang Ren-shan · Computer Engineering and Applications Journal · 2014
Feature extraction is a key problem for the mass CT image segmentation, a novel features extraction algorithm of CT image is proposed based on Non-Subsampled Contourlet Transform(NSCT)and Gray Level Co-occurrence Matrix(GLCM)in this paper. Firstly, CT image is multi-scale, multi direction decomposed by the NSCT, and the co-occurrence features of sub-images are extracted by GLCM, and then the redundant features are eliminated by the principal component analysis and feature vectors are composed, finally CT image is segmented by the support vector machine based on multi-feature vector space. The experimental results show that the proposed algorithm can extract features of CT image,and has improved the segmentation accuracy of CT images, can provide assisted information for the doctor diagnosis.