Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization

doi:10.1007/s11042-016-3486-z

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 机器人视觉团队

	Segmentation of liver cyst in ultrasound image based on adaptive threshold algorithm and particle swarm optimization
	Zhu, Haijiang 1; Zhuang, Zhanhong 1; Zhou, Jinglin 1; Zhang, Fan 1; Wang, Xuejing 1; Wu, Yihong2
刊名	MULTIMEDIA TOOLS AND APPLICATIONS
	2017-03-01
卷号	76 期号:6 页码:8951-8968
关键词	Ultrasound Image Wellner's Thresholding Algorithm Particle Swarm Optimization Segmentation Of Liver Cyst
DOI	10.1007/s11042-016-3486-z
文献子类	Article
英文摘要	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.
WOS关键词	CLASSIFICATION ; VECTOR ; TUMOR
WOS研究方向	Computer Science ; Engineering
语种	英语
WOS记录号	WOS:000399017800059
资助机构	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
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/15078]
专题	自动化研究所_模式识别国家重点实验室_机器人视觉团队
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.