Noise reduction in echocardiography images using Contourlet Transform

Noise Reduction In Echocardiography Images Using

Contourlet Transform

Presented by:

Jerrin Thomas Panachakel

Roll No.: 17

S7 E.C.E

MBCET

.

Guided by:

Asst.Prof. Naveen S.

Dept. of E.C.E.

MBCET

3rd July, 2011

OverviewIntroductionNeed for Contourlet transformContourlet transformIterative noise-free filterinEchocardiogramAnalytical resultsQualitative resultsConclusion

2/25Dept. of ECE,

MBCET

Noise Reduction In Echocardiography Images Using Contourlet Transform

IntroductionEchocardiogram: Sonogram of heartMajor constraint : Noises (especially

SPE) affecting the images.Proposed method for denoising based on

Contourlet transform.Evaluation based on both graphical and

mathematical analysis.

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Dept. of ECE, MBCET

Why Contourlet?Natural signals are highly non-

stationary :i.e.; frequency changes with time

Conventional transform techniques fail to give simultaneous information about frequency domain and time domain behaviour of a signal.

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Dept. of ECE, MBCET

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Different in Time Domain

Same in Frequency Domain

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x(t) X(Ω) Y(Ω)y(t)

Dept. of ECE, MBCET

SHORT TIME FOURIER TRANSFORMDeveloped by Dennis Gabor (1946)

To analyze only a small section of the signal at a time -- a technique called Windowing the Signal.

The Segment of Signal is Assumed Stationary

Discarded due to its inability to give appreciable resolution simultaneously in both time and frequency domains.

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dtetttxft ftj

t

2*X ,STFT


6

Window functionDept. of ECE,

MBCET

Wavelet Transform Wavelet Transform

An alternative approach to the short time Fourier transform to overcome the resolution problem

Wavelet Small wave Means the window function is of finite length

Advantages: Supports Multiresolution Supports Localization Supports Critical Sampling

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Dept. of ECE, MBCET

DEFINITION OF CONTINUOUS WAVELET TRANSFORM

Mother Wavelet A prototype for generating the other window functions All the used windows are its dilated or compressed and shifted

versions

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sss xx

*1

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Translation(The location of

the window)

Scale

Mother Wavelet


8

Dept. of ECE, MBCET

Shannon WaveletY(t) = 2 sinc(2t) – sinc(t)

t=5, s=2

time


fig. 9.1

fig. 9.2

Dept. of ECE, MBCET

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What more was needed?Directionality: The representation should

contain basis elements oriented at a variety of directions, much more than the few directions that are offered by separable wavelets.

Anisotropy: To capture smooth contours in images, the representation should contain basis elements using a variety of elongated shapes with different aspect ratios.

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Dept. of ECE, MBCET

Contourlet TransformDeveloped by Minh and MartinTwo dimensional transformHas all the advantages of Wavelet along

with other advantages such as improved ability to capture directional information and enhanced anisotropy.

Consists of two parts:Laplacian pyramidDirectional filter bank

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Dept. of ECE, MBCET

Laplcaian PyramidDeveloped by Burt and AdelsonDecomposes the original image into a

hierarchy of images such that each level corresponds to a different band of image frequencies

Supports multi-resolution analysis.

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Dept. of ECE, MBCET

SUBSAMP &

BLUR

SUBSAMP &

BLUR

SUBSAMP &

BLUR

3 Level LPD

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Courtesy:: My classmate Yedu Manmathan

Dept. of ECE, MBCET

Directional Filter BankDeveloped by Barberger and Smith.The filter bank takes in high frequencies

of input signals and divided them into 2L bands.

High frequencies of the image contains information about the directions.

The amount of directional information that can be enhanced depends on the value of L.

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Dept. of ECE, MBCET

Frequency partitioning when l = 3

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Dept. of ECE, MBCET

The Contourlet filter bank

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Dept. of ECE, MBCET

EchocardiogramSonogram of heart.Images heart using standard ultrasonic imaging

technique.allows

assessment of cardiac valve areas and function. any abnormal communications between the left and

right side of the heart. any leaking of blood through the valves (valvular

regurgitation). calculation of the cardiac output as well as

the ejection fraction.17/25


Dept. of ECE, MBCET

Echocardiogram images

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Courtesy: Mr.Kjetil LenesDept. of ECE, MBCET

Echocardiogram images (cont…)

19/25Courtesy: Mr. Kjetil LenesCourtesy: Mr.Kjetil LenesDept. of ECE, MBCET

http://commons.wikimedia.org/wiki/User:Ekko



Analytical Results Anaytical results

Criteria used Mean Square Error (MSE)

Peak Signal-to- noise Ratio (PSNR)

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Dept. of ECE, MBCET

Analytical Results (cont..)

Signal to MSE

Contrast Speckle Ratio (CSR)

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Dept. of ECE, MBCET

Comparison of different evaluation criteriaCrtieri

aDifferent Methods

Median filter

Wiener filter

Wavelett Contourlet

PSNR 10.1735 4.2383 4.8102E-004

2.8073E-004

SMSE 38.0561 41.8589 81.3092 83.6479

CSR 4.3605 4.3904 4.6318 4.8102

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Dept. of ECE, MBCET

ConclusionThe method uses novel Contourlet

approach for denoising echocardiogram signals.

Unmatched improvement in denoising of echocardiogram signal is achieved without significant data loss.

A denoising efficiency of this magnitude will prove as a step further to automation of echocardiogram analysis.

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Dept. of ECE, MBCET

REFERENCES

D. L. Donoho, M. Vetterli, R. A. DeVore, and I. Daubechies, “WAVELET-BASED CONTOURLET TRANSFORM AND ITS APPLICATION TO IMAGE CODING” IEEE Trans. Inform. Th., vol. 44,no. 6, pp. 2435–2476, October 2008.

S. Mallat, “A WAVELET TOUR OF SIGNAL

PROCESSING”, 2nd ed. Academic Press, 1999.

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Dept. of ECE, MBCET

THANK YOU

25/25Dept. of ECE,

MBCET


Education

Noise reduction in echocardiography images using Contourlet Transform