A Comparative Study of Filters for Denoising Mammograms
Sunita Sarangi, Nrusingha Prasad Rath, Harish Kumar Sahoo · 2021 International Conference on Intelligent Technologies (CONIT) · 2021
Mammogram is an effective tool for analyzing breast images for screening breast cancer and other abnormalities. The preprocessing of mammogram includes eliminating the noise effects which may be added during image acquisition. In this work, Mean, Gaussian, Wiener, Median, Weighted median and Hybrid median filters performances are analyzed as denoising methods applied to mammograms. The quantitative measures like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM) are used as means of performance comparison parameters.