Digital image enhancement algorithms for 2D ultrasound imaging systems - Zhang, Fan (2008)
Speckle affects human interpretation of medical ultrasound images and degrades the accuracy of computer-assisted diagnosis. The state-of-the-art speckle reduction techniques have limited capability in preserving important image features and details. In this thesis, an effective speckle reduction algorithm, i.e., Laplacian pyramid based nonlinear diffusion (LPND), is proposed. The novelty of the proposed algorithm lies in extending the conventional single-scale nonlinear diffusion to a multiscale framework, i.e., Laplacian pyramid. From simulation and phantom studies, an average gain of 1.55 dB and 1.34 dB in contrast-to-noise ratio (CNR) were obtained compared with recently-developed speckle reducing anisotropic diffusion (SRAD) and nonlinear coherent diffusion (NCD), respectively. The visual comparison of despeckled in vivo ultrasound images also demonstrates that LPND effectively suppresses speckles as well as preserves edges and detailed structures. To further enhance fuzzy boundaries in ultrasound images, Laplacian pyramid based nonlinear diffusion and shock filter (LPNDSF) is proposed. The proposed LPNDSF has demonstrated its ability to sharpen image edges and suppress speckle simultaneously. LPND and LPNDSF may be used to improve the performance of computer-assisted diagnosis such as segmentation and boundary detection.