Multi-scale Synthetic Filtering Method for Ultrasonic Image Enhancement

In this paper, a novel ultrasonic image enhancement method, i.e., multi-scale synthetic filtering (MSF) method is proposed for effectively suppressing speckle noise and enhancing structured region. The proposed MSF method is composed of the modified nonlinear coherence diffusion (NCD) model and the adaptive directional filter (ADF) both applied in multi-scale domain. Due to the difference in frequency characteristics of speckle and edge, Laplacian pyramid is adopted to analyze ultrasonic images. On each Laplacian sub-band, the modified NCD is performed to suppress speckle noise while preserving anatomical edges. Then, the ADF is applied to each synthesized images to sharpen and enhance detailed boundaries. The performance of the proposed MSF method is compared with the speckle reducing anisotropic diffusion (SRAD). For quantitative analysis, the contrast-to-noise ratio (CNR) values were computed on in vivo carotid artery ultrasound images. When compared with the SRAD, the average CNR gain of the proposed MSF method was 0.42 dB. The average processing time of the proposed method is 8.1 ms per one frame. The clinical evaluations and short running time indicate that the proposed MSF method can improve the diagnostic confidence in medical ultrasound imaging.