计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
11期
159-162,179
,共5页
图像分割%非下采样轮廓变换%灰度共生矩阵%特征提取%特征融合
圖像分割%非下採樣輪廓變換%灰度共生矩陣%特徵提取%特徵融閤
도상분할%비하채양륜곽변환%회도공생구진%특정제취%특정융합
image segmentation%non-subsampled contourlet transform%gray level co-occurrence matrix%feature extracted%features fusion
针对海量CT图像分割中特征提取的难题，提出一种非下采样轮廓变换（NSCT）和灰度共生矩阵（GLCM）相融合的CT图像特征提取算法。首先采用NSCT对CT图像进行多尺度、多方向分解，并采用GLCM提取子带图像的共生特征量，然后对共生特征量进行主成分分析，消除冗余特征量，构成多特征矢量，最后利用支持向量机完成多特征矢量空间的划分，实现CT图像分割。实验结果表明，NSCT-GLCM能够较好地提取CT图像特征，提高了CT图像分割准确率，可以为医生诊断提供辅助信息。
針對海量CT圖像分割中特徵提取的難題，提齣一種非下採樣輪廓變換（NSCT）和灰度共生矩陣（GLCM）相融閤的CT圖像特徵提取算法。首先採用NSCT對CT圖像進行多呎度、多方嚮分解，併採用GLCM提取子帶圖像的共生特徵量，然後對共生特徵量進行主成分分析，消除冗餘特徵量，構成多特徵矢量，最後利用支持嚮量機完成多特徵矢量空間的劃分，實現CT圖像分割。實驗結果錶明，NSCT-GLCM能夠較好地提取CT圖像特徵，提高瞭CT圖像分割準確率，可以為醫生診斷提供輔助信息。
침대해량CT도상분할중특정제취적난제，제출일충비하채양륜곽변환（NSCT）화회도공생구진（GLCM）상융합적CT도상특정제취산법。수선채용NSCT대CT도상진행다척도、다방향분해，병채용GLCM제취자대도상적공생특정량，연후대공생특정량진행주성분분석，소제용여특정량，구성다특정시량，최후이용지지향량궤완성다특정시량공간적화분，실현CT도상분할。실험결과표명，NSCT-GLCM능구교호지제취CT도상특정，제고료CT도상분할준학솔，가이위의생진단제공보조신식。
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.
