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Advanced Cancer Cell Characterization and Quantification of Microscopy Images
Theodosios Goudas and Ilias Maglogiannis
University of Central Greece, Department of Computer Science and Biomedical Informatics, Lamia, Greece[email protected]
[email protected]
Abstract. In this paper we present an advanced image analysis tool for the accurate characterization and quantification of cancer and apoptotic cells in microscopy images. Adaptive thresholding and Support Vector Machines classifiers were utilized for this purpose. The segmentation results are improved through the application of morphological operators such as Majority Voting and a Watershed technique. The proposed tool was evaluated on breast cancer images by medical experts and the results were accurate and reproducible.
Keywords: Image Analysis, SVM, Breast Cancer, Cancer cell, Adaptive Thresholding, Watershed, MCF-7
LNAI 7297, p. 315 ff.
[email protected]
© Springer-Verlag Berlin Heidelberg 2012