SVM Ensemble based Computer-aided-diagnosis Method of Lung Tumor using PET/CT Multi-modality Data
WU Cuiying
ZHOU Tao
LU Huiling
YAO Zhongbao
WANG Yuanyuan
YANG Pengfei
Abstract：To propose a new method that PET/CT computer-aided-diagnosis of lung tumor based on SVM ensemble.Firstly, 2 000 cases of PET, CT and PET/CT in patients with lung cancer from clinic were collected, and the ROI of the same lesion location for three modal images was extracted.Secondly, according to the different characteristics of CT, PET and PET/CT, shape feature, gray feature, Tamura and GLCM feature and other features were extracted from CT ,PET, PET/CT image ROI,and the 80,98 and 98 dimensional feature space were constitued and the individual classifier in different feature space was constructed, including CT-SVM, PET-SVM, PET/CT-SVM;Thirdly, CT-SVM,PET-SVM and PET/CT-SVM were ensemble to use for computer-aided-diagnosis for lung tumor.The experimental results show that this method can effectively improve the diagnostic accuracy of lung tumor.
Keywords：PET/CTPositron emission fomographCTLung cancerEnsemble support vector machineComputer-aided-diagnosis
Publication Date：2017-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：6( 207-212 )