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The nucleus segmentation results have been validated by three expert hematologists.
We get an average accuracy of 92% for nucleus segmentation and 70% for cytoplasm segmentation.
Since the cytoplasm segmentation process depends on the result of the nucleus segmentation, hence, the 8% (100 - 92%) error yielded by the nucleus segmentation affects directly on the cytoplasm extraction accuracy.
Cell nucleus segmentation: A semi-automated segmentation algorithm was developed to accurately delineate boundaries of cell nuclei [ 30].
Nucleus segmentation was achieved by applying an intensity threshold to the maximum intensity projection of the grayscale image.
The proposed scheme has two parts: The nucleus segmentation part is based on morphological analysis, and the cytoplasm segmentation is based on pixel-intensity thresholding.
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This paper presents the METINUS Plus (METhod of Immunohistochemical NUclei Segmentation Plus) method that has been developed for localization and quantification of the regulatory T cells' nuclei.
(1) Nuclei Segmentation.
The frontend software Modular Interactive Nuclei Segmentation (MINS; X.L., M. Kang, P. Xenopoulos, S.M.-D.
Validation of cell nuclei segmentation: One hundred cells were randomly selected from 10 CARS images for each subtype of four breast cancer lesions: DCIS, IG-IDC, HG-IDC, and ILC, to validate the semi-automated segmentation algorithm.
A nuclear protein, NHP6a, was C-terminally tagged with iRFP, an infrared fluorescent protein (Filonov et al., 2011 ; Hansen and O'Shea, 2013 ), to visualize the nucleus for segmentation purposes.
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