EVALUATION OF DIGITAL FILTERS FOR SIMILARITY ANALYSIS BETWEEN TOMOSYNTHESIS AND 2D MAMMOGRAPHIC IMAGES

Breast cancer is the second leading cause of cancer death in women. Tomosynthesis is a new technique of additional exam that was created in order to improve the early detection of such disease. This technique shows a reconstructed image from different projections of the breast, reducing, this way, the effect of quantum noise due to the small thickness of the object of study. This paper aims at comparing the 3D reconstructed image with some filtered 2D polymethylmethacrylate (PMMA) images using structural similarity index (SSIM). We tested Wiener, Non-local Means, and Adaptive Median digital filters, which were applied at a region of interest of a 2D conventional mammography acquired in combo mode. From this work, we could quantify the level of similarity from different digital filters. Wiener and Adaptive Median filters increased the similarity between the 2D and the 3D tomosynthesis image, in terms of luminance, contrast and structure. However, the image with Nonlocal Means decreased significantly the similarity between the pair of compared images, proving the ineffective of this filter in reducing quantum noise.