Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/919316
- Title
- Microscopic image segmentation based on color pixels classification
- Author/Creator
-
Park, Mira;
Jin, Jesse S.;
Xu, Min;
Wong, W. S. Felix;
Luo, Suhuai;
Cui, Yue
- Institution
- The University of Newcastle. Faculty of Science & Information Technology, School of Design, Communication and Information Technology
- Description
- The computer-assisted microscopy systems can increase the accuracy of the analysis. To guarantee correct results in computer-assisted microscopy, accurate nuclei segmentation is crucially important since images segmentation is the first step towards image understanding and image analysis. In this paper, we present clustering techniques to segment homogeneous clusters in RGB color space and then label each cluster as a different region. According to the evaluation process, 97% of nuclei pixels were correctly delineated with our algorithm and on average 90% of nuclei were correctly detected. Our methods could be of value to computer-based systems designed to objectively interpret microscopic images by accurate nuclei segmentation.
- Relation
- 1st International Conference on Internet Multimedia Computing and Service (ICIMCS 2009). Proceedings of the 1st International Conference on Internet Multimedia Computing and Service, ICIMCS 2009 (Kunming, China 23-25 November, 2009) p. 61-67
- Publisher Link
- http://dx.doi.org/10.1145/1734605.1734622
- Date
- 2009
- Publisher
- ACM
- Keyword(s)
-
cervical cancer;
cell segmentation;
K-mean clustering
- Resource Type
- conference paper
- Identifier
- http://hdl.handle.net/1959.13/919316
- Identifier
- ISBN:9781605588407
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