|本期目录/Table of Contents|

[1]吴翠颖,周涛△,陆惠玲,等.基于集成SVM的肺部肿瘤PET/CT三模态计算机辅助诊断方法*[J].生物医学工程研究,2017,03:207-212.
 WU Cuiying,ZHOU Tao,LU Huiling,et al.SVM Ensemble based Computer-aided-diagnosis Method of Lung Tumor using PET/CT Multi-modality Data[J].Journal of Biomedical Engineering Research,2017,03:207-212.
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基于集成SVM的肺部肿瘤PET/CT三模态计算机辅助诊断方法*(PDF)

《生物医学工程研究》[ISSN:1006-6977/CN:61-1281/TN]

期数:
2017年03期
页码:
207-212
栏目:
出版日期:
2017-09-25

文章信息/Info

Title:
SVM Ensemble based Computer-aided-diagnosis Method of Lung Tumor using PET/CT Multi-modality Data
文章编号:
1672-6278 (2017)03-0207-06
作者:
吴翠颖1周涛2△陆惠玲2姚中宝1王媛媛1杨鹏飞3
1.宁夏医科大学公共卫生和管理学院,银川 750004;2.宁夏医科大学理学院,银川 750004;3.宁夏医科大学总医院核医学科,银川 750004
Author(s):
WU Cuiying1 ZHOU Tao2 LU Huiling2 YAO Zhongbao1WANG Yuanyuan1 YANG Pengfei3
1. School of Public Health and Management, Ningxia Medical University, Yinchuan 750004,China;2. School of Science, Ningxia Medical University, Yinchuan 750004;3. Department of Nuclear Medicine, General Hospital of Ningxia Medical University, Yingchuan 750004
关键词:
PET/CT正电子发射计算机断层显像CT肺部肿瘤集成支持向量机计算机辅助诊断
Keywords:
PET/CTPositron emission fomographCTLung cancer Ensemble support vector machine Computer-aided-diagnosis
分类号:
R318;TP391.41;R734.2
DOI:
10.19529/j.cnki.1672-6278.2017.03.04
文献标识码:
A
摘要:
本研究提出基于集成SVM的肺部肿瘤PET/CT三模态计算机辅助诊断新方法。首先在临床采集肺部肿瘤患者PET、CT和PET/CT各2000例三模态图像数据上提取对同一病灶ROI区域;然后根据CT、PET和PET/CT的不同特点,从三模态图像的ROI区域中提取形状特征、灰度特征、Tamura纹理特征和GLCM特征等不同特征分别构成80、98、98维特征分量,并分别在不同特征空间里构造个体分类器,包括CT-SVM、PET-SVM、PET/CT-SVM;最后,基于相对多数投票原则,对CT-SVM、PET-SVM和PET/CT-SVM进行集成,识别对肺部肿瘤。实验结果表明,该方法能够有效提高肺部肿瘤的诊断正确率。
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.

参考文献/References

备注/Memo

备注/Memo:
(收稿日期:2016-07-01) 国家自然科学基金资助项目(81160183,61561040);宁夏自然科学基金资助项目(NZ16067);宁夏高教项目(NGY2016084)。△通信作者Email:109356310@qq.com
更新日期/Last Update: 2017-09-25