9 December 2015 Automatic segmentation and classification of tendon nuclei from IHC stained images
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Proceedings Volume 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015); 98170J (2015) https://doi.org/10.1117/12.2228579
Event: Seventh International Conference on Graphic and Image Processing, 2015, Singapore, Singapore
Abstract
Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu’s thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu’s thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.
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Chan-Pang Kuok, Po-Ting Wu, I-Ming Jou, Fong-Chin Su, Yung-Nien Sun, "Automatic segmentation and classification of tendon nuclei from IHC stained images", Proc. SPIE 9817, Seventh International Conference on Graphic and Image Processing (ICGIP 2015), 98170J (9 December 2015); doi: 10.1117/12.2228579; https://doi.org/10.1117/12.2228579
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