A Spatially Adaptive Filter Reducing A Spatially Adaptive Filter Reducing Arc Stripe Noise for Sector Scan Arc Stripe Noise for Sector Scan

Medical Ultrasound ImagingMedical Ultrasound Imaging

Qianren Xu

Mohamed Kamel

Magdy M. A. Salama

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OutlineOutline

• Introduction

• Method

• Experiment Results

• Conclusion

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IntroductionIntroduction

• 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.

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The Source of the Arc Stripe NoiseThe 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.

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The properties of these noiseThe 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

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Proposed FilterProposed Filter

It consists of two components:

Radially adaptivefiltering operators

Common Gaussianfiltering operator+

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Radially Adaptive Filtering Operators:Radially Adaptive Filtering Operators:Basic Radial Filtering Operators at Special DirectionsBasic Radial Filtering Operators at Special Directions

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op

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op

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Radially Adaptive Filtering Operators:Radially Adaptive Filtering Operators:Radial Filtering Operators at Arbitrary DirectionsRadial 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

,4,3,2,1,4

1

mopopm

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4/)1(1

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m

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The Combined FilterThe Combined Filter

Weighted Summation of the Radial Filtering Operator and Gaussian Filtering Operator:

),('4

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m

mmrgg opopop

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

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An Example of the Combined FilterAn Example of the Combined Filter

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5.0 rg

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Selection of ParametersSelection of Parameters

),('4

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m

mmrgg opopop

1. The weight ωg and ωg are determined by the ratio of non-directional and arc stripe noise components

2. The Gaussian standard deviation σ of opg and opm are determined by the size of non-directional and arc stripe noise noises respectively

3. The size of filter mask is determined by noise size

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Testing Image on the Radial FilterTesting Image on the Radial Filter

(b) Filtered image by the radial filter(a) Original testing image

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Filtered image by Gaussian filter

Filtered image by the proposed filter

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Example IIExample II

(a) The original image of fetus (b) The filtered image

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ConclusionConclusion

• 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.

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Thanks for your timeThanks for your time

Questions?