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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
Source PublicationMULTIMEDIA TOOLS AND APPLICATIONS
2017-03-01
Volume76Issue:6Pages:8951-8968
SubtypeArticle
AbstractTo 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.
KeywordUltrasound Image Wellner's Thresholding Algorithm Particle Swarm Optimization Segmentation Of Liver Cyst
WOS HeadingsScience & Technology ; Technology
DOI10.1007/s11042-016-3486-z
WOS KeywordCLASSIFICATION ; VECTOR ; TUMOR
Indexed BySCI
Language英语
Funding OrganizationNational 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 Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000399017800059
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15078
Collection模式识别国家重点实验室_机器人视觉
Affiliation1.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
Recommended Citation
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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