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. © 2012 Springer-Verlag.
CITATION STYLE
Goudas, T., & Maglogiannis, I. (2012). Advanced cancer cell characterization and quantification of microscopy images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7297 LNCS, pp. 315–322). https://doi.org/10.1007/978-3-642-30448-4_40
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