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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/927220
- Automatic cell segmentation in microscopic color images using ellipse fitting and watershed
Jin, J. S.;
- The University of Newcastle. Faculty of Science & Information Technology, School of Design Communication and Information Technology
- This paper presents an efficient and innovative method for the automated counting of cells in a microscopic image. The performance of watershed-based algorithms for the segmentation of clustered cells has been well demonstrated. The strength of our algorithm lies in the fact that it incorporates knowledge of color in the image. Our method uses the watershed transform with iterative shape alignment and is shown to be more accurate in retaining cell shape. We report a sensitivity of 97% and specificity of 96% when all color bands are used. Our methods could be of value to computer-based systems designed to objectively interpret microscopic images, since they provide a means for accurate cell segmentation.
- 2010 IEEE/ICME International Conference on Complex Medical Engineering (IEEE/ICME 2010). Proceedings of the IEEE/ICME International Conference on Complex Medical Engineering, CME2010 (Gold Coast, Qld 13-15 July, 2010) p. 69-74
- Publisher Link
- Institute of Electrical and Electronics Engineers (IEEE)
automatic cell segmentation;
cell automated counting;
- Resource Type
- conference paper
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