Automated detection of breast cancer lesions using adaptive thresholding and morphological operation

Abstract

One of the imaging modalities for early detection of breast cancer is ultrasonography (USG). The detection is based on lesions identification. Radiologists still manually conduct early detection of the lesions. Hence, the detection results tend to be subjective and may cause different interpretations due to the different level of knowledge and experience of the radiologists. In this research, the proposed method for the detection of automatic lesions uses 30 images consisting of 20 images benign lesions and 10 images of malignant lesions. At the pre-processing stage, adaptive median filter is applied and is followed by adaptive thresholding method at the segmentation process. The final stage uses morphological operations. The result shows that the proposed method successfully achieved the accuracy of 95.19%, sensitivity of 84.13% and specificity of 96.2%. These results indicate that the system can be used to assist the experts or operators from radiology team more objectively in breast cancer lession detection.