Segmentation Method of Overlapped nuclei in FISH Image 


Vol. 16,  No. 2, pp. 131-140, Apr.  2009
10.3745/KIPSTB.2009.16.2.131


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  Abstract

This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.

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[IEEE Style]

M. R. Jeong, B. C. Ko, J. Y. Nam, "Segmentation Method of Overlapped nuclei in FISH Image," The KIPS Transactions:PartB , vol. 16, no. 2, pp. 131-140, 2009. DOI: 10.3745/KIPSTB.2009.16.2.131.

[ACM Style]

Mi Ra Jeong, Byoung Chul Ko, and Jae Yeal Nam. 2009. Segmentation Method of Overlapped nuclei in FISH Image. The KIPS Transactions:PartB , 16, 2, (2009), 131-140. DOI: 10.3745/KIPSTB.2009.16.2.131.

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