A Noninvasive System for Gliomas Diagnosis Based on Tamura Texture, Discrete Wavelet Transformation and Pyramid Histogram of Oriented Gradient
文献类型：会议论文
| 作者 | Huang Z(黄钲)1,2,5 ; Ke, Wenbing3; Zhang, Zhenyu4; Zhao YW(赵忆文)1,5; Zhao XG(赵新刚)1,5; Song GL(宋国立)1,5
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| 出版日期 | 2019 |
| 会议日期 | July 29 - August 2, 2019 |
| 会议地点 | Suzhou, China |
| 关键词 | Gliomas Diagnosis Support Vector Machine Ant Colony Algorithm Discrete Wavelet Transformation |
| 页码 | 542-547 |
| 英文摘要 | The glioma is regarded as one of the most common malignant brain tumors, which is a serious threat to the life of patients. The early detection of gliomas can contribute to make up a suitable surgery scheme and thus improve the survival rate of patients. Conventional methods to diagnosis gliomas rely mostly on the clinical experiences of radiologists, which is of low efficiency and accuracy. To improve the detection accuracy of the gliomas, an automatic diagnosis system based on T2-weighted brain images is presented in this paper. In this system, brain images are labeled with normal, glioma and the other kinds of tumors, in addition, hybrid features including discrete wavelet transformation (DWT), Tamura texture and pyramid histogram of oriented gradient (PHOG) are extracted, and ant colony algorithm (ACA) is combined with support vector machine (SVM) to build up classifiers. The experiment results show that the accuracy, specificity and sensitivity of this method can reach 91.11%, 86.91% and 94.21%, respectively. |
| 产权排序 | 2 |
| 会议录 | Proceedings of 9th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-0769-1 |
| WOS记录号 | WOS:000569550300109 |
| 源URL | [http://ir.sia.cn/handle/173321/26838]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Song GL(宋国立) |
| 作者单位 | 1.State Key Laboratary of Robotics, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang, CO 110016 China 2.University of Chinese Academy of Sciences, Beijina 100049, China 3.State Grid Qianshan Country Electric Power Supply Company, Anqing 246300, China 4.School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China 5.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Huang Z,Ke, Wenbing,Zhang, Zhenyu,et al. A Noninvasive System for Gliomas Diagnosis Based on Tamura Texture, Discrete Wavelet Transformation and Pyramid Histogram of Oriented Gradient[C]. 见:. Suzhou, China. July 29 - August 2, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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