Please use this identifier to cite or link to this item: http://hdl.handle.net/11400/10109
Title: Computer-based malignancy grading of astrocytomas employing a support vector machines classifier, the WHO grading system, and the regular staining diagnostic procedure Hematoxylin-Eosin
Authors: Γκλώτσος, Δημήτριος
Σπυρίδωνος, Παναγιώτα Π.
Πεταλάς, Π.
Κάβουρας, Διονύσης Α.
Ραβαζούλα, Παναγιώτα
Contributors: Αραπαντώνη-Δαδιώτη, Πετρούλα
Λέκκα, Ι.
Νικηφορίδης, Γεώργιος Χ.
Item type: Journal article
Keywords: Classification;Biopsy;Ταξινόμηση;Βιοψία
Subjects: Medicine
Biomedical engineering
Ιατρική
Βιοϊατρική τεχνολογία
Issue Date: 11-May-2015
2004
Publisher: Journal of Reproductive Medicine
Abstract: OBJECTIVE: To investigate and develop an automated technique for astrocytoma malignancy grading compatible with the clinical routine. STUDY DESIGN: One hundred forty biopsies of astrocytomas were collected from 2 hospitals. The degree of tumor malignancy was defined as low or high according to the World Health Organization grading system. From each biopsy, images were digitized and segmented to isolate nuclei from background tissue. Morphologic and textural nuclear features were quantified to encode tumor malignancy. Each case was represented by a 40-dimensional feature vector. An exhaustive search procedure in feature space was utilized to determine the best feature combination that resulted in the smallest classification error. Low and high grade tumors were discriminated using support vector machines (SVMs). To evaluate the system performance, all available data were split randomly into training and test sets. RESULTS: The best vector combination consisted of 3 textural and 2 morphologic features. Low and high grade cases were discriminated with an accuracy of 90.7% and 88.9%, respectively, using an SVM classifier with polynomial kernel of degree 2. CONCLUSION: The proposed methodology was based on standards that are common in daily clinical practice and might be used in parallel with conventional grading as a second-opinion tool to reduce subjectivity in the classification of astrocytomas.
Language: English
Citation: Glotsos, D., Spyridonos, P., Petalas, P., Cavouras, D., Ravazoula, P., et al. (April 2004). Computer-based malignancy grading of astrocytomas employing a Support Vector Machines Classifier, the WHO grading system, and the regular staining diagnostic procedure Hematoxylin-Eosin. Analytical and Quantitative Cytology and Histology. 26(2). pp. 77-83. 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/11400/10109
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