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|Title:||Improved Detection of Breast Cancer Nuclei using Modular Neural Networks||Authors:||Schnorrenberg, Frank
Schizas, Christos N.
Kollias, Stefanos D.
Kyriacou, Kyriacos C. ItemCrisRefDisplayStrategy.rp.deleted.icon
|Keywords:||Biomedical;Breast cancer Nuclei;Modular Neural Network||Issue Date:||2000||Publisher:||IEEE Engineering in Medicine and Biology Society||Source:||Engineering in Medicine and Biology Magazine, IEEE, Vol. 19, no. 1, (2000), pp.48-63||Abstract:||Discusses the analysis of nuclei in histopathological sections with a system that closely simulates human experts. The evaluation of immunocytochemically stained histopathological sections presents a complex problem due to many variations that are inherent in the methodology. In this respect, many aspects of immunocytochemistry remain unresolved, despite the fact that results may carry important diagnostic, prognostic, and therapeutic information. In this article, a modular neural network-based approach to the detection and classification of breast cancer nuclei stained for steroid receptors in histopathological sections is described and evaluated.||URI:||http://ktisis.cut.ac.cy/handle/10488/133||ISSN:||0739-5175||DOI:||10.1109/51.816244||Rights:||© 2008 IEEE Engineering in Medicine and Biology Society||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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