Gelişmiş Arama

Basit öğe kaydını göster

dc.contributor.authorAksebzeci, Bekir Hakan
dc.contributor.authorKayaalti, Omer
dc.date.accessioned2021-07-29T07:34:17Z
dc.date.available2021-07-29T07:34:17Z
dc.date.issued2017en_US
dc.identifier.isbn978-1-5386-0633-9
dc.identifier.urihttps://hdl.handle.net/20.500.12573/880
dc.description.abstractNowadays, one of the most common types of cancer is breast cancer. The early and accurate diagnosis of breast cancer has great importance in the treatment of the disease. In the diagnosis of breast cancer, histopathological analysis of cell and tissue specimens taken by biopsy is considered as the gold standard. Histopathological analysis is a tedious process that is highly dependent on the knowledge and experience of the pathologists. In this study; it is aimed to develop a computer-aided system that can reduce the workload of pathologists and help them in their diagnosis. An image set containing benign and malignant tumor images of breast cancer has been studied. To perform texture analysis on tumor images; first order statistics, Gabor and gray-level co-occurrence matrix (GLCM) feature extraction methods have been applied. Then, various classifiers were applied to the obtained feature matrices and their performances were compared. The highest classification accuracy was achieved 82.06% by Random Forests classifier with feature combination of Gabor and GLCM methods. The results presented here show that computer-assisted diagnosis of breast cancer is a promising field.en_US
dc.description.sponsorshipIEEE Turkey Secten_US
dc.language.isoturen_US
dc.publisherIEEE345 E 47TH ST, NEW YORK, NY 10017 USAen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectmachine learningen_US
dc.subjectimage classificationen_US
dc.subjecttexture featuresen_US
dc.subjecthistopathological imagesen_US
dc.subjectBreast canceren_US
dc.titleComputer-Aided Classification of Breast Cancer Histopathological Imagesen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentAGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümüen_US
dc.relation.journal2017 MEDICAL TECHNOLOGIES NATIONAL CONGRESS (TIPTEKNO)en_US
dc.relation.publicationcategoryKonferans Öğesi - Ulusal - Kurum Öğretim Elemanıen_US


Bu öğenin dosyaları:

DosyalarBoyutBiçimGöster

Bu öğe ile ilişkili dosya yok.

Bu öğe aşağıdaki koleksiyon(lar)da görünmektedir.

Basit öğe kaydını göster