Using Adaptive Median Filter for Noise Removal from Image to Diagnose Breast Cancer

Breast cancer is one of the main causes of fatality among women around the world. Mammography is a basic screening technique in fast diagnosis of tumor in the breast. The main goal of mammography is to recognize small masses/tumors in the shortest time, since these masses can be the sign of cancer. But due to existence of noise, low and opaque contrast and fuzziness of mammograms’ images, diagnosis of small masses is difficult. Hence, the images of mammograms shall be improved. Recovering the images is carried out for better display of mammographic special features including mass and micro classification, and exaggeration of certain properties is done for simple and fast diagnosis. “Makendor” and “Helali” reviewed different techniques of removing noise and image enhancement in order to determine the enhancement technique appropriate to mammogram’s images. Mammograms remove the noise by linear and non-linear filtering techniques. The operations of these techniques are measured by using Root Mean Square Error (RMSE) and Peak Signal Noise Rate (PSNR). Finally, the contrast of images is improved by histogram techniques.