Four image interpolation techniques for ultrasound breast phantom data acquired using Fischer's full field digital mammography and ultrasound system (FFDMUS): a comparative approach

In computer-aided analysis of mammograms, a fast processing analysis for mammograms benefits and facilitate the real time application and is also useful for radiologist to do on-line diagnosis. Down sampling is widely applied to reduce the size of large images and improve the processing speed. This paper presents the performance evaluations among several interpolation techniques (bilinear, bicubic, wavelet and Lanczos) for ultrasound breast phantom data. We also compared lesion segmentation results of down sampled images with the results of original images. Two major metrics: the Hausdorff distance measure (HDM) and polyline distance measure (PDM) were applied to measure the performance of the segmentation. We conclude that without scarifying the quality of ultrasound images, we increase the speed of system processing using our down sampling strategies. Moreover, among the four different technologies, the Lanczos algorithm can achieve the best performance.