Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/10111
Title: Automatic segmentation of routinely H&E stained microscopic images by combining support vector machine clustering and active contour models
Authors: Γκλώτσος, Δημήτριος
Σπυρίδωνος, Παναγιώτα Π.
Κάβουρας, Διονύσης Α.
Ραβαζούλα, Παναγιώτα
Αραπαντώνη-Δαδιώτη, Πετρούλα
Contributors: Νικηφορίδης, Γεώργιος Χ.
Item type: Journal article
Keywords: Biopsy;Automation;Βιοψία;Αυτοματοποίηση
Subjects: Technology
Biomedical engineering
Τεχνολογία
Βιοϊατρική τεχνολογία
Issue Date: 11-May-2015
2004
Publisher: Journal of Reproductive Medicine
Abstract: To develop a method for the automated segmentation of images of routinely hematoxylin-eosin (H-E)-stained microscopic sections to guarantee correct results in computer-assisted microscopy. Clinical material was composed 50 H-E-stained biopsies of astrocytomas and 50 H-E-stained biopsies of urinary bladder cancer. The basic idea was to use a support vector machine clustering (SVMC) algorithm to provide gross segmentation of regions holding nuclei and subsequently to refine nuclear boundary detection with active contours. The initialization coordinates of the active contour model were defined using a SVMC pixel-based classification algorithm that discriminated nuclear regions from the surrounding tissue. Starting from the boundaries of these regions, the snake fired and propagated until converging to nuclear boundaries. The method was validated for 2 different types of H-E-stained images. Results were evaluated by 2 histopathologists. On average, 94% of nuclei were correctly delineated. The proposed algorithm could be of value in computer-based systems for automated interpretation of microscopic images.
Language: English
Citation: Glotsos, D., Spyridonos, P., Cavouras, D., Ravazoula, I., Dadioti, P., et al. (December 2004). Automatic segmentation of routinely H&E stained microscopic images by combining support vector machine clustering and active contour models. Analytical and Quantitative Cytology and Histology. 26(6). pp. 331-341. Journal of Reproductive Medicine: 2004.
Journal: Analytical and Quantitative Cytology and Histology
Type of Journal: With a review process (peer review)
Access scheme: Embargo
License: Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες
URI: http://hdl.handle.net/11400/10111
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