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Segmentation of cervical nuclei using SLIC and pairwise regional contrastRatna Saha et al. Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul.
AbstractA framework to detect and segment nuclei from cervical cytology images is proposed in this study. Poor contrast, spurious edges, degree of overlap, and intensity inhomogeneity make the nuclei segmentation task more complex in overlapping cell images. The proposed technique segments cervical nuclei by merging over-segmented SLIC superpixel regions using a novel region merging criteria based on pairwise regional contrast and image gradient contour evaluations. The framework was evaluated using the first overlapping cervical cytology image segmentation challenge - ISBI 2014 dataset. The result shows that the proposed framework outperforms the state-of-the-art algorithms in nucleus detection and segmentation accuracies.
Cited byShakoor A, Gao W, Zhao L, Jiang Z, Sun D. Shakoor A, et al. Microsyst Nanoeng. 2022 Apr 29;8:47. doi: 10.1038/s41378-022-00376-0. eCollection 2022. Microsyst Nanoeng. 2022. PMID: 35502330 Free PMC article. Review.
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