Abstract
In this paper, we study the concept of adaptive thresholding and present a new adaptive bottom-hat filter for the extraction of nuclei and analysis of malignancy in an image. The adaptiveness of the used structure element enables a more accurate and location-wise processing of areas in order to extract nuclei clearly for further processing such as classification of morphological features. In addition to the adaptive method we will present a color channel manipulation as a preprocessing step that adduces real benefit for the extraction phase. Some preliminary results are presented to illustrate the true potential of our method in the analysis of breast cancer. These results show that the color channel manipulation together with adaptive filtering extract the image in such a way that mainly only the nuclei is present.
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Acknowledgement
This research work was supported by ARTEMIS Joint Undertaking under Grant Agreement no 621439 (ALMARVI). The utilized histopathological breast cancer images are acquired from BioMediTech, University of Tampere.
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Ikonen, T., Haataja, K., Toivanen, P., Tolonen, T., Isola, J. (2017). Nuclei Malignancy Analysis Based on an Adaptive Bottom-Hat Filter. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_19
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DOI: https://doi.org/10.1007/978-3-319-53480-0_19
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