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A Spatially Adaptive Filter Reducing Arc Stripe Noise for Sector Scan Medical Ultrasound Imaging

A Spatially Adaptive Filter Reducing Arc Stripe Noise for Sector Scan Medical Ultrasound Imaging. Qianren Xu Mohamed Kamel Magdy M. A. Salama. Outline. Introduction Method Experiment Results Conclusion. Introduction. Sector scan ultrasound images usually have arc stripes;

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A Spatially Adaptive Filter Reducing Arc Stripe Noise for Sector Scan Medical Ultrasound Imaging

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  1. A Spatially Adaptive Filter Reducing Arc Stripe Noise for Sector Scan Medical Ultrasound Imaging Qianren Xu Mohamed Kamel Magdy M. A. Salama

  2. Outline • Introduction • Method • Experiment Results • Conclusion

  3. Introduction • Sector scan ultrasound images usually have arc stripes; • They do not represent the physical structure of the tissue; • Thus they can be viewed as a kind of noise.

  4. The Source of the Arc Stripe Noise Assume that there are point targets with same size. The lateral size of image of these points increase beyond focal zone. These laterally wider images will be superimposed on the far sides of the focal location, and thus these target points that are originally separated will show as arc stripes in far-field and near-field.

  5. The properties of these noise Special geometric properties of the arc stripe noise: • Circular symmetry. • The intensity and size of the arc stripes change with the radial depth. The proposed filter is based on the geometric properties

  6. Proposed Filter It consists of two components: Radially adaptivefiltering operators Common Gaussian filtering operator +

  7. Radially Adaptive Filtering Operators:Basic Radial Filtering Operators at Special Directions y x

  8. Radially Adaptive Filtering Operators:Radial Filtering Operators at Arbitrary Directions The filtering operator at any azimuth angle θ is determined by soft weighted summation of neighbor basic radial filtering operators

  9. The Combined Filter Weighted Summation of the Radial Filtering Operator and Gaussian Filtering Operator: Radial filtering operators aim to reduce random directional noise Common Gaussian filter is used 1) to counteract the radial stripe artifact, and 2) suppress the non-directional noise

  10. An Example of the Combined Filter

  11. Selection of Parameters • The weight ωg and ωg are determined by the ratio of non-directional and arc stripe noise components • The Gaussian standard deviation σof opg and opm are determined by the size of non-directional and arc stripe noise noises respectively • The size of filter mask is determined by noise size

  12. Testing Image on the Radial Filter (a) Original testing image (b) Filtered image by the radial filter

  13. Filtered image by Gaussian filter Filtered image by the proposed filter

  14. Example II (a) The original image of fetus (b) The filtered image

  15. Conclusion • This paper identifies a significant noise, the arc stripes in sector scan medical ultra-sound image, and generalizes the characteristics of the arc stripe noise. • The proposed filtering algorithm deals with the arc stripe noise by utilizing the geometric characteristics of the special noise, • The parameters of the filter are adapted with the radial depth in order to effectively smooth noise and deblur the useful image detail. • The results show that the proposed filter obviously enhances image quality and is superior to common smoothing filter.

  16. Thanks for your time Questions?

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