A novel approach for Enhancing Mammographic Images
Amit Kamra, Richa Sharma · International Journal of System of Systems Engineering · 2023
In order to reduce the risk factor connected with the disease, preclinical identification of breast cancer is essential, and mammography is one of the finest screening methods. In this study work, we propose a brand-new method for improving poor-quality mammography pictures. Contrast limited adaptive histogram equalisation (CLAHE) and morphological operations (MOs) are two image processing methods we recommend using. The median filter, low pass Gaussian filtering, MOs, and wavelet decomposition are the next steps in the suggested technique after removing noise. Applying our suggested method to mammogram images from the Mammographic Image Analysis Society (MIAS) dataset to assess how effective it is. We use the peak signal noise ratio (PSNR), mean square error (MSE), and root mean square error (RMSE) as three common picture quality measures to assess our method. These measurements allow us to evaluate the improvement in image quality brought about by our suggested strategy quantitatively.