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A new feature-enhanced speckle reduction method based on multiscale analysis for ultrasound B-mode imaging

초록/요약

Effective speckle reduction in ultrasound B-mode imaging is important for enhancing image quality and improving accuracy in image analysis and understanding. In this paper, a new feature-enhanced speckle reduction (FESR) method based on multiscale analysis and feature enhancement filtering is proposed for ultrasound B-mode imaging. In FESR, clinical features (e.g., boundaries and borders of lesions) are selectively emphasized by edge, coherence and contrast enhancement filtering from fine to coarse scales while simultaneously suppressing speckle development via robust diffusion filtering. From the simulation study, the proposed FESR method showed statistically-significant improvements in edge preservation, mean structure similarity, speckle signal-to-noise ratio and contrast-to-noise ratio (CNR) compared to other speckle reduction methods, e.g., oriented speckle reducing anisotropic diffusion (OSRAD), nonlinear coherent diffusion (NCD), Laplacian pyramid nonlinear diffusion (LPND) and nonlinear multiscale wavelet diffusion (NMWD). Similarly, the FESR method outperformed over the OSRAD, NCD, LPND and NMWD methods in terms of CNR, i.e., 10.70±0.06 vs. 9.00±0.06, 9.37±0.06, 9.78±0.06, and 9.85±0.06, respectively. Reconstructed B-mode images developed using the five speckle reduction methods were reviewed by three radiologists to evaluate each radiologist’s diagnostic preferences. Significant preferences was shown for the FESR methods in liver and kidney images in terms of conspicuity, margin sharpness and contrast for all three radiologists, p<0.0001. However, the FESR method did not show statistically-significant improvement in conspicuity for the thyroid images. These results demonstrate that the proposed FESR method can improve the image quality of ultrasound B-mode imaging by enhancing the visualization of features of lesions while effectively suppressing speckle noise.

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