Abstract
This paper proposes a novel cell nucleus segmentation method for color esophageal biopsy image. For each nucleus of cell image, based on color characteristics of cell nucleus, a threshold separating the nucleus can be detected automatically in each RGB color component. According to the thresholds, two fuzzy domains are established for each color component with bell-curve and S-curve membership functions. Then we propose a novel growing snake to extract cell nucleus boundary. Described in polar coordinates, the proposed snake is driven by the potential energy and the growing energy integrating the fuzzification information of tristimulus components. The proposed model has low computation cost and strong anti-noise ability. The experiments on a number of cell images show encouraging results.
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© 2004 Springer-Verlag Berlin Heidelberg
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Hu, M., Ping, X., Ding, Y. (2004). Applying Fuzzy Growing Snake to Segment Cell Nuclei in Color Biopsy Images. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_105
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DOI: https://doi.org/10.1007/978-3-540-30497-5_105
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24127-0
Online ISBN: 978-3-540-30497-5
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