title: An advanced image analysis tool for the quantification and characterization of breast cancer in microscopy images.
abstract: The paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images. The proposed tool utilizes adaptive thresholding and a Support Vector Machines classifier. The segmentation results are enhanced through a Majority Voting and a Watershed technique, while an object labeling algorithm has been developed for the fast and accurate validation of the recognized cells. Expert pathologists evaluated the tool and the reported results are satisfying and reproducible.
authors: Department of Digital Systems, University of Piraeus, Grigoriou Lampraki 126, PC 18532, Piraeus, Greece, goudas@unipi.gr.
authors: Theodosios
authors: T
authors: Goudas
authors: Ilias
authors: I
authors: Maglogiannis
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008853:Microscopy / Q000295:instrumentation*; D010363:Pattern Recognition, Automated / Q000379:methods*; D060388:Support Vector Machine