Non-subsampled contourlet transform based spatially adaptive shrinkage for speckle reduction of medical ultrasound image

Chengzhi Deng; Shengqian Wang

doi:10.1117/12.832430

30 October 2009 Non-subsampled contourlet transform based spatially adaptive shrinkage for speckle reduction of medical ultrasound image

Chengzhi Deng, Shengqian Wang

Author Affiliations +

Proceedings Volume 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 74972J (2009) https://doi.org/10.1117/12.832430
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Speckle is a multiplicative noise that degrades ultrasound images. In this paper, a statistical spatially adaptive approach for speckle reduction in medical ultrasound images based posterior conditional means (PCM) estimation in the nonsubsampled contourlet domain is proposed. In this framework, a new class of statistical model for nonsubsampled contourlet coefficients is proposed. And the proposed method uses the Gaussian distribution for speckle noise and normal inverse Gaussian distribution for modeling the statistics of nonsubsampled contourlet coefficients in a logarithmically transformed ultrasound images. Experiments are carried out using synthetically speckled and real ultrasound images. The experimental results demonstrate that the proposed method performs better than several other existing methods in terms of quantitative performance as well as in term of visual quality of the images.

Citation Download Citation

Chengzhi Deng and Shengqian Wang "Non-subsampled contourlet transform based spatially adaptive shrinkage for speckle reduction of medical ultrasound image", Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74972J (30 October 2009); https://doi.org/10.1117/12.832430

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