Classification of breast masses in mammogram images using KNN
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Breast cancer is one of the most deadly diseases for women. Mammogram is very important imaging technique used diagnosis in early stages of breast cancer. In this study, a decision support system which helps experts to examine mammogram images in the fight against breast cancer is developed. In this study, firstly several preprocesses are applied to mammogram to make image clear and segmentation of mass is provided with an appropriate threshold value. After the segmentation processes, features of the tumor mass are obtained. The obtained features are classified as normal, benign or malignant using kNN (k-nearest neighbours) classifiers. In this study, its have been were shown that, effect of kurtosis, skewness and wavelet energy features on classification performance is shown. As a result, it has been seen that, these features improve the classification performance. © 2015 IEEE.
Açıklama
2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- 113052
Anahtar Kelimeler
Classification (of information), Decision support systems, Diseases, Higher order statistics, Image classification, Image segmentation, Mammography, Nearest neighbor search, X ray screens, Breast Cancer, Breast mass, Classification performance, K-nearest neighbours, Mammogram images, Segmentation process, Threshold-value, Wavelet energy feature, Medical imaging
Kaynak
2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings
WoS Q Değeri
Scopus Q Değeri
N/A
