Wavelet Image Interpolation (WII): A wavelet-based approach to enhancement of digital mammography images

Abstract

Cancer detection using mammography focuses, in part, on characteristics of tiny microcalcifications, including the number, size, and spatial arrangement of the microcalcifications, as well as morphological features of individual microcalcifications. We have developed state-of-theart wavelet-based methods to enhance the resolution of microcalcifications visible on digital mammograms, aimed at 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. We found that our proposed procedure is efficient and useful in capturing relevant clinical information in the context of digital mammographie imaging. Our proposed methodology was tested by an experienced radiologist using 40 images from the University of South Florida Digital Database for Screening Mammography (DDSM). © Springer-Vorlag Berlin Heidelberg 2007.