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Evaluation of State of the Art Methods for Segmenting Muscle Cells
Li HX(李海星); Yang YM(杨永明); Wang ZZ(王振洲)
作者部门机器人学研究室
会议名称7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
会议日期July 31 - August 4, 2017
会议地点Hawaii, USA
会议主办者IEEE Robotics and Automation Society
会议录名称2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
出版者IEEE
出版地New York
2017
页码1130-1134
收录类别EI ; CPCI(ISTP)
EI收录号20183905873655
WOS记录号WOS:000447628700203
产权排序1
ISBN号978-1-5386-0489-2
摘要

Segmentation of muscle cells is important and challenging in microscopy imaging applications. There are many segmentation algorithms available in the literature and they depend on different image features such as pixel intensity value, color and textures. In this paper, three state of the art image segmentation methods: Slope Difference Thresholding and Iterative Erosion based method(SDAIE), SMASH method and CellSegm method were evaluated and compared. To compare the performance of the algorithms and assist the users to understand each method better, different types of muscle cell images and six segmentation evaluation metrics were used. The experimental results showed that the Slope Difference Thresholding and Iterative Erosion based method is more robust than the other two methods.

语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/22844
专题机器人学研究室
通讯作者Wang ZZ(王振洲)
作者单位Shenyang Institute of Automation, Chinese Academy of Sciences, China
推荐引用方式
GB/T 7714
Li HX,Yang YM,Wang ZZ. Evaluation of State of the Art Methods for Segmenting Muscle Cells[C]//IEEE Robotics and Automation Society. New York:IEEE,2017:1130-1134.
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