Evaluating denoising performances of basic filters in the detection of microcalcifications on mammogram images

This research evaluates the denoising abilities of some image-processing filters used in facilitating early detection microcalcifications breast tissues. The mean, median and Gaussian were employed to denoise mammogram images microcalcification phantoms various densities. performances assessed by evaluating mean squared error (MSE), peak signal-to-noise ratio (PSNR), (SNR). All experiments carried out on MATLAB R2020a platform. results revealed that filter recorded optimal performance with all 3 types added noises compared filters. PSNR value heterogeneous phantom (PVAL/H) was superior those less dense (PVAL/E), (PVAL), extremely (PVAL/G) for tested this work agree high contrast original image PVAL/H.