Abstract
The paper describes our experiments of automated digital histological image analysis. In our study we investigated two tasks. The primary goal was to develop a simple and effective automated scheme of cell nuclei counting. The second goal was to demonstrate that for histological images with homogeneous background we can apply a binarization technique and approximately calculate the number of nuclei in the image. The experiments were done on two public datasets of histological images. The experiments have demonstrated acceptable level of calculation results.
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Lukashevich, M., Starovoitov, V. (2019). Cell Nuclei Counting and Segmentation for Histological Image Analysis. In: Ablameyko, S., Krasnoproshin, V., Lukashevich, M. (eds) Pattern Recognition and Information Processing. PRIP 2019. Communications in Computer and Information Science, vol 1055. Springer, Cham. https://doi.org/10.1007/978-3-030-35430-5_8
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DOI: https://doi.org/10.1007/978-3-030-35430-5_8
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