Examination and Classification of Mammography Images with the RLBP Method

Year 2021, Volume: 4 Issue: 2, 59 - 64, 15.12.2021

Muhammed Mustafa Kelek , Enes Cengiz , Yüksel Oğuz , Ahmet Yönetken

https://doi.org/10.53448/akuumubd.978181

Cited By: 4

Abstract

Breast cancer is the most common type of cancer in women worldwide. Breast cancer, which can happen to every woman, can also be seen in men. The physical and mental state of people is very important in breast cancer. The breast tissues should be examined at intervals in order to be cautious against breast cancer. The breast tissues should be examined periodically in order to be cautious against breast cancer. These tissues are examined by experts. However, misdiagnoses made during the examination adversely affect the treatment process. For this reason, it is more beneficial to process and examine these tissues in digital environment. In this study, classification of breast cancer was made with ANN. Features were extracted using the Rotated Local Binary Pattern (RLBP) method on mammography images. These features were trained by ANN whose parameters have been determined. As a result of the training, a success rate of 87.82% was achieved in the binary classification classified as benign and malignant, and 80.95% in the triple background tissue classification classified as Fatty, Fatty-Glandüler and Dense-Glandüler.

Keywords

Mammogram, Artificial Neural Network (ANN), RLBP, Breast Cancer.

RLBP Metodu ile Mamografi Görüntülerinin İncelenmesi ve Sınıflandırılması

Abstract

Göğüs kanseri dünya genelinde kadınlarda en çok karşılaşılan kanser türüdür. Günümüzde her kadının başına gelebilecek olan göğüs kanseri, erkeklerde de görülebilmektedir. Göğüs kanserinde insanların fiziksel ve zihinsel halleri çok etkilidir. Göğüs kanserine karşın tedbirli olabilmek için belirli aralıklarla göğüs dokularının incelenmesi gerekmektedir. Bu dokular, uzmanlar tarafından incelenmektedir. Ancak inceleme esnasında yapılan yanlış teşhisler tedavi sürecini olumsuz etkilemektedir. Bu sebeple, bu dokuların sayısal ortamda işlenip incelenmesi daha faydalı olmaktadır. Bu çalışmada, YSA ile göğüs kanserinin sınıflandırması yapılmıştır. Mamografi görüntüleri üzerinde Döndürülmüş Yerel İkili Örüntü (RLBP) metodu kullanılarak öznitelikler çıkarılmıştır. Bu öznitelikler, parametreleri belirlenmiş olan YSA aracılığı ile eğitilmiştir. Eğitim sonucunda iyi ve kötü huylu olarak sınıflandırılan ikili sınıflandırmada %87,82 ve Yağlı, Yağlı-Glandüler ve Yoğun-Glandüler olarak sınıflandırılan üçlü arka plan doku sınıflandırmasında %80,95 başarı oranı elde edilmiştir.

Keywords

Mamogram, Yapay Sinir Ağı (YSA), RLBP, Göğüs Kanseri.

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