An Adaptive Enhancement Method for Ultrasound Images
In this paper, we present a novel adaptive method for ultrasound (US) image enhancement. It is based on a new measure of perceptual saliency and the view-dependent feature on US images. By computing this measure on an US image, speckle noise is reduced and perceptual salient boundaries of organs are enhanced. Because of the curvature gradient based saliency measure, this method can enhance more types of salient structures than the well-known saliency network method. Meanwhile, the proposed method does not depend on the closure measure. This makes it more appropriate to enhance real images than other existing methods. Moreover, the local analysis of speckle patterns leads a good performance in speckle reduction for US images. Experimental results show the proposed enhancement approach can provide a good assistant for US image segmentation and image-guided diagnosis.
KeywordsBeam Axis Speckle Pattern Speckle Noise Perceptual Saliency Speckle Reduction
Unable to display preview. Download preview PDF.
- 2.Sha’ashua, A., Ullman, S.: Structural saliency: The detection of globally salient structures using a locally connected network. In: ICCV, pp. 321–327 (1988)Google Scholar
- 3.Herault, L., Horaud, R.: Figure-ground discrimination: A combinational optimization approach. IEEE Trans. on PAMI 15 (1993)Google Scholar
- 4.Guy, G., Medioni, G.: Inferring global perceptual contours from local features. In: DARPA Image Understanding workshop, pp. 881–892 (1993)Google Scholar
- 5.Sharkar, S., Boyer, K.: Quantitative measures of change based on feature organization: Eigenvalues and eigenvectors. In: CVPR, pp. 478–483 (1996)Google Scholar
- 6.Mahamud, S., Williams, L.R., Thornber, K.K., Xu, K.: Segmentation of multiple salient closed contours from real images. IEEE Trans. on PAMI 25(4), 433–444 (2003)Google Scholar
- 8.Xie, J., Tsui, H.T., Lau, T.K.: Edge enhancement based on salient structure extration. In: Asian Conference on Computer Vision, pp. 1152–1157 (2004)Google Scholar
- 9.Schueler, C.F., Lee, H.L., Wade, G.: Fundamentals of digital ultrasonic imaging. IEEE Trans. Sonics Ultrasound (1984)Google Scholar
- 10.Tuthill, T.A., Sperry, R.H., Parker, K.J.: Deviations from rayleigh statistics in ultrasonic speckle. Ultrason. Imaging 10 (1988)Google Scholar
- 11.Vilanova, J.S., Sung, K.K.: Multi-scale vectorridge-detection for perceptual organization without edges. MIT A.I. Memo (1992)Google Scholar
- 13.Wang, J.K., Li, X.B.: A system for segmenting ultrasound images. In: ICPR, pp. 456–461 (1998)Google Scholar