Abstract
The paper presents Iterated Conditional Modes based method for nuclei recognition in cytological images. It approximates nuclei by circles and ellipses. The first step is to find coordinates and sizes of circles. To find good configuration of circles, Iterated Conditional Modes (ICM) approach is employed to maximize the probability of configuration given image data. However, nucleus shape appears to be more elliptical than circular. Unfortunately, the process of finding nuclei using ellipses is computationally expensive, because at one point ellipses have three parameters (minor axis, major axis and angle), while circle have only one parameter (radius). To tackle this problem, we proposed heuristic procedure to estimate ellipses based on previously determined circles. To test the effectiveness of the method, it was applied to recognize disks in synthetically generated images and nuclei in microscopic images of breast cancer tissue.
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The research was supported by National Science Centre, Poland (2015/17/B/ST7/03704).
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Skobel, M., Kowal, M., Korbicz, J. (2018). Nuclei Recognition Using Iterated Conditional Modes Approach. In: Kurzynski, M., Wozniak, M., Burduk, R. (eds) Proceedings of the 10th International Conference on Computer Recognition Systems CORES 2017. CORES 2017. Advances in Intelligent Systems and Computing, vol 578. Springer, Cham. https://doi.org/10.1007/978-3-319-59162-9_34
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DOI: https://doi.org/10.1007/978-3-319-59162-9_34
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