Breast cancer classification in pathological images based on hybrid features

Author:

Yu CuiruORCID,Chen Houjin,Li Yanfeng,Peng Yahui,Li Jupeng,Yang Fan

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Reference41 articles.

1. Ferlay J, Soerjomataram I, Ervik M et al (2015) Breast cancer statistics. World Cancer Research Fund International. https://www.wcrf.org/int/cancer-facts-figures/data-specific-cancers/breast-cancer-statistics . Accessed 16 January 2015

2. Veta M, van Diest PJ, Kornegoor R et al (2013) Automatic nuclei segmentation in h&e stained breast cancer histopathology images. PLoS One 8(7):e70221

3. Petushi S, Garcia FU, Haber MM et al (2006) Large-scale computations on histology images reveal grade-differentiating parameters for breast cancer. BMC Med Imaging 6(1):1–11

4. Vink JP, Van Leeuwen MB, Van Deurzen CHM et al (2013) Efficient nucleus detector in histopathology images. J Microsc 249(2):124–135

5. Sabeena BK, Nair MS, Bindu GR (2014) Automatic segmentation and classification of mitotic cell nuclei in histopathology images based on Active Contour Model. International Conference on Contemporary Computing and Informatics on IEEE, pp 740–744

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