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Advanced cancer cell characterization and quantification of microscopy images

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Autore
Goudas, T.; Maglogiannis, I.
Data
2012
DOI
10.1007/978-3-642-30448-4_40
Soggetto
Adaptive Thresholding
Breast Cancer
Cancer cell
Image Analysis
MCF-7
SVM
Watershed
Cancer cells
Artificial intelligence
Cells
Diseases
Image segmentation
Support vector machines
Watersheds
Medical imaging
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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. © 2012 Springer-Verlag.
URI
http://hdl.handle.net/11615/28080
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