Knowledge Commons of Institute of Automation，CAS
| Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization | |
Zhu, Haijiang1; Zhuang, Zhanhong1; Zhou, Jinglin1; Zhang, Fan1 ; Wang, Xuejing1; Wu, Yihong2
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| 发表期刊 | MULTIMEDIA TOOLS AND APPLICATIONS
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| 2017-03-01 | |
| 卷号 | 76期号:6页码:8951-8968 |
| 文章类型 | Article |
| 摘要 | To find the optimum threshold of an image is still an important research topic in the recent years. This paper presents a segmentation of liver cyst for ultrasound image through combining Wellner's thresholding algorithm with particle swarm optimization (PSO). The proposed method firstly obtains an optimal parameter, which expressed as a percentage or fixed amount of dark objects against a white background in a gray image, of Wellner's thresholding algorithm by PSO method. And then the gray image is binarized according to the optimized parameter. Finally, a semi-automatic method for locating and identifying multiple liver cysts or single liver cyst of ultrasound images is performed. For a validation, the results of the proposed technique are compared with those of other segmented methods. We also tested 92 ultrasound images of the liver cysts by our software. The corrected identification rate of the single liver cysts is 97.7%, and that of multiple liver cysts is 87.5 %. Experimental results demonstrate that the proposed technique is reliable on segmenting the contour of liver cyst and identifying single or multiple liver cysts. |
| 关键词 | Ultrasound Image Wellner's Thresholding Algorithm Particle Swarm Optimization Segmentation Of Liver Cyst |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1007/s11042-016-3486-z |
| 关键词[WOS] | CLASSIFICATION ; VECTOR ; TUMOR |
| 收录类别 | SCI |
| 语种 | 英语 |
| 项目资助者 | National High Technology Research and Development Program of China (863 Program)(2015AA020504) ; National Natural Science Foundation of China(61473025) ; Fundamental Research Funds for the Central Universities(YS1404) ; State Key Laboratory of Synthetical Automation for Process Industry at the Northeastern University in China |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000399017800059 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/15078 |
| 专题 | 多模态人工智能系统全国重点实验室_机器人视觉 |
| 作者单位 | 1.Beijing Univ Chem Technol, Coll Informat & Technol, Beijing 100029, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhu, Haijiang,Zhuang, Zhanhong,Zhou, Jinglin,et al. Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2017,76(6):8951-8968. |
| APA | Zhu, Haijiang,Zhuang, Zhanhong,Zhou, Jinglin,Zhang, Fan,Wang, Xuejing,&Wu, Yihong.(2017).Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization.MULTIMEDIA TOOLS AND APPLICATIONS,76(6),8951-8968. |
| MLA | Zhu, Haijiang,et al."Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization".MULTIMEDIA TOOLS AND APPLICATIONS 76.6(2017):8951-8968. |
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