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- W2013661872 abstract "AbstractThe aim of this work is to assist pathologists in the evaluation of tumour cells in microscopic breast images where we distinguish three kinds of cells: positive tumour cells for oestrogen receptor, negative tumour cells for oestrogen receptor, and non-tumour cells. This work has proven to be very difficult because of the variability of cells’ size, shape (morphology) and distribution. Conventional methods for segmentation like thresholding and edge detection are unable to resolve this problem. The herein proposed method is a hybrid approach combining segmentation and classification to ensure better results. While the morphological processes are used for artefact elimination and cell segmentation, the classification algorithm is used to automatically classify all existing cells in the image. The paper contains also a comparative study between fuzzy c-means clustering algorithm and neural network-based classification. The proposed approach was applied on several microscopic breast cancer cells imag..." @default.
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- W2013661872 date "2013-02-01" @default.
- W2013661872 modified "2023-09-26" @default.
- W2013661872 title "A hybrid approach for oestrogen receptor status evaluation" @default.
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- W2013661872 doi "https://doi.org/10.1179/1743131x11y.0000000037" @default.
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