肺部CT图像特征的设备无关性研究

doi:10.3969/j.issn.1001-2400.2016.01.028

J4 ›› 2016, Vol. 43 ›› Issue (1): 157-161+179.doi: 10.3969/j.issn.1001-2400.2016.01.028

肺部CT图像特征的设备无关性研究

李海霞1,2;张擎3;王青4;尹义龙3,5;郝凡昌1,2

(1. 山东政法学院山东省高校证据鉴识重点实验室，山东济南 250014;
2. 山东政法学院信息学院，山东济南 250014;
3. 山东大学计算机科学与技术学院，山东济南 250012;
4. 山东大学齐鲁医院放射科，山东济南 250101;
5. 山东财经大学计算机科学与技术学院，山东济南 250014)

收稿日期:2014-10-10 出版日期:2016-02-20 发布日期:2016-04-06
作者简介:李海霞(1976- ), 女, 副教授, 博士, E-mail: lihaixiajinan@gmail.com．
基金资助:
NSFC-广东联合基金资助项目(U1201258)；高等学校博士学科点专项科研基金资助项目(20110131130004)；山东省高校证据鉴识重点实验室(山东政法学院)开放课题资助项目(KFKT(SUPL)-201409)；山东政法学院科研资助项目(2012Z23B)

Study of sensor interoperability of features on lung CT images

LI Haixia1,2;ZHANG Qing3;WANG Qing4;YIN Yilong3,5;HAO Fanchang1,2

(1. Evidence Forensic Lab. in Colleges and Univ. of Shandong Province, Shandong Univ. of Political Science and Law, Jinan 250014, China;
2. School of Information, Shandong Univ. of Political Science and Law, Jinan 250014, China;
3. School of Computer Science and Technology, Shandong Univ., Jinan 250101, China;
4. Radiology department of Qilu hospital of Shandong Univ., Jinan 250012;
5. School of Computer Science and Technology, Shandong Univ. of Finance and Economics, Jinan 250014, China)

Received:2014-10-10 Online:2016-02-20 Published:2016-04-06

摘要/Abstract

摘要：

选择具有设备无关性的图像特征是未得到充分关注的重要问题之一．基于计算机断层扫描图像上的肺部疾病分类问题，笔者研究了几种常用的灰度和纹理特征的设备无关性，结合图像特征的设备无关性和区分性，提出了一种特征评价准则，进行特征选择．并在来自3个不同设备的数据集上进行实验．结果表明了设备无关性特征对图像处理的重要性，同时显示设备无关性特征可提高相关算法的通用性，并验证了笔者提出的特征评价准则的合理性和有效性．

关键词: 设备无关性, 特征选择, CT图像, 肺部疾病

Abstract:

Selecting features with high sensor interoperability is of great importance but it is not been investigated enough. Based on the application of classifying lung diseases on CT (Computed Tomography) images, the sensor interoperability of 4 features is studied. An evaluation criterion is proposed to select features by considering interoperability and discrimination ability of features. After doing experiments on 3 different datasets, it is shown that sensor interoperability affects the disease recognition or information retrieval methods. Moreover, the rationality and effectiveness of the proposed feature evaluation criterion is verified.

Key words: sensor interoperability, feature election, computed tomography, lung disease

李海霞;张擎;王青;尹义龙;郝凡昌. 肺部CT图像特征的设备无关性研究[J]. J4, 2016, 43(1): 157-161+179.

LI Haixia;ZHANG Qing;WANG Qing;YIN Yilong;HAO Fanchang. Study of sensor interoperability of features on lung CT images[J]. J4, 2016, 43(1): 157-161+179.

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肺部CT图像特征的设备无关性研究

Study of sensor interoperability of features on lung CT images

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