Abstract
There are numerous cells nuclei analysis algorithms. The lacunarity is the texture analysis algorithm and could be applied for binary or grayscale images of cells nuclei. The cells in Papanicolaou process are stained so numerous conversions to grayscale or binary images are possible. The optimization of RGB color space using weights is proposed for polynomial based analysis using lacunarity and the cell area of binary image. Obtained results show significant differences for best and worst cases for the number of cells of atypical and correct classes with similar cells area.
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Oszutowska–Mazurek, D., Mazurek, P., Sycz, K., Waker–Wójciuk, G. (2016). Color Space Optimization for Lacunarity Method in Analysis of Papanicolaou Smears. In: Choraś, R. (eds) Image Processing and Communications Challenges 7. Advances in Intelligent Systems and Computing, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-319-23814-2_23
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DOI: https://doi.org/10.1007/978-3-319-23814-2_23
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