Today the treatment and diagnosis of diseases heavily rely on medical images. These images are produced in huge
amount, which causes a bottleneck in the process of investigation.
One of the most important diseases, which heavily rely on images,
is Breast Cancer. We introduce a classification system based on a
hybrid feature extractor that relies on Completed Local Binary
Pattern (CLBP), Singular Value Decomposition (SVD), Gabor
Filter, Wavelet Transform and Support Vector Machines
classifier (SVM). The purpose of this research is to increase the
level of classification automation of Breast Cancer (BC)
Histopathological image. The Experimental approach was used to
investigate the effect of the proposed algorithm which has shown
promising results. These results were benchmarked against a
standard dataset of BC Histopathological image |
