Abstract. Cancer detection using mammography focuses on characteristics of tiny microcalcifications, including the number, size, and spatial arrangement of microcalcification clusters as well as morphological features of individual microcalcifications. We developed state-of-theart wavelet-based methods to enhance the resolution of microcalcifications visible in digital mammograms, thereby improving the specificity of breast cancer diagnoses. In our research, we develop, refine, and evaluate a Wavelet Image Interpolation (WII) procedure and create accompanying software to implement it. WII involves the application of an inverse wavelet transformation to a coarse or degraded image and constructed detail coefficients to produce an enhanced higher resolution image. The construction of detail coefficients is supervised by the observed image and innate regular scaling assessed by a statistical model. Methodology we propose was tested by an experienced radiologist in a blind study using...
Gordana Derado, F. DuBois Bowman, Rajan Patel, Mar