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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)
Department机器人学研究室
Conference Name7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
Conference DateJuly 31 - August 4, 2017
Conference PlaceHawaii, USA
Author of SourceIEEE Robotics and Automation Society
Source Publication2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
PublisherIEEE
Publication PlaceNew York
2017
Pages1130-1134
Indexed ByEI ; CPCI(ISTP)
EI Accession number20183905873655
WOS IDWOS:000447628700203
Contribution Rank1
ISBN978-1-5386-0489-2
Abstract

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.

Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/22844
Collection机器人学研究室
Corresponding AuthorWang ZZ(王振洲)
AffiliationShenyang Institute of Automation, Chinese Academy of Sciences, China
Recommended Citation
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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