Nuclei Segmentation in Histopathology Images
In the field of computational histopathology, nuclei segmentation is one of the important tasks. In the following works, we evaluate:
Test nuclei feature descriptors for disease stage classification of Gliomas with machine learning models
Example Nuclei Segmentation with color decomposition active contours 
 V. B. S. Prasath, K. Fukuma, B. J. Aronow, H. Kawanaka. Cell nuclei segmentation in glioma histopathology images with color decomposition based active contours. IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), Washington, DC, USA. Proc. IEEE. pp. 1734-1736, Nov 2015. doi:10.1109/BIBM.2015.7359944. Poster available at figshare: 10.6084/m9.figshare.1588805
 K. Fukuma, V. B. S. Prasath, H. Kawanaka, B. J. Aronow, H. Takase. A study on nuclei segmentation, feature extraction and disease stage classification for human brain histopathological images. International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES), York, UK, Sep 2016. Procedia Computer Science, 96, pp. 1202-1020, Sep 2016. doi:10.1016/j.procs.2016.08.164
 T. Hayakawa, V. B. S. Prasath, H. Kawanaka, B. J. Aronow, S. Tsuruoka. Computational nuclei segmentation methods in digital pathology - A survey. Archives of Computational Methods in Engineering, 28(1), 1-13, January 2021. doi:10.1007/s11831-019-09366-4
Nuclei segmentation and feature extraction for disease stage classification in Glioblastoma Multiforme.
Automatic nuclei segmentation in glioma histopathology with adaptive filtering based entropy thresholding.
Tomohiro Hayakawa. Nuclei detection and segmentation in glioma histopathology images. Graduate School of Engineering, Mie University, Japan, 2017.
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