A Comprehensive Analysis: Automated Ovarian Tissue Detection Using Type P63 Pathology Color Images
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-41920-6_54
Reference21 articles.
1. Kiruthika, V., Ramya, M.: Automatic segmentation of ovarian follicle using K-means clustering. In: 2014 Fifth International Conference on Signal and Image Processing (ICSIP), pp. 137–141 (2014)
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3. Kelsey, T.W., Caserta, B., Castillo, L., Wallace, W.H.B., Gonzálvez, F.C.: Proliferating Cell Nuclear Antigen (PCNA) allows the automatic identification of follicles in microscopic images of human ovarian tissue. arXiv preprint arXiv:1008.3798 (2010)
4. Muskhelishvili, L., Wingard, S.K., Latendresse, J.R.: Proliferating cell nuclear antigen—a marker for ovarian follicle counts. Toxicologic Pathology 33, 365–368 (2005)
5. Lamprecht, M.R., Sabatini, D.M., Carpenter, A.E.: CellProfiler™: free, versatile software for automated biological image analysis. Biotechniques 42, 71 (2007)
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