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My B.Tech. seminar presentation based on Shahi, L. P., Behnam, H., Shalbaf, A., & Sani, Z. A. (2011, February). Noise reduction in echocardigraphy images using Contourlet transform. In Biomedical Engineering (MECBME), 2011 1st Middle East Conference on (pp. 420-423). IEEE.
Citation preview
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.
3/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
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.
4/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
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Noise Reduction In Echocardiography Images Using Contourlet Transform
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.
6/25
dtetttxft ftj
t
2*X ,STFT
Noise Reduction In Echocardiography Images Using Contourlet Transform
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
7/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
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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dts
ttx
sss xx
*1
, ,CWT
Translation(The location of
the window)
Scale
Mother Wavelet
Noise Reduction In Echocardiography Images Using Contourlet Transform
8
Dept. of ECE, MBCET
Shannon WaveletY(t) = 2 sinc(2t) – sinc(t)
t=5, s=2
time
Noise Reduction In Echocardiography Images Using Contourlet Transform
fig. 9.1
fig. 9.2
Dept. of ECE, MBCET
9/25
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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Noise Reduction In Echocardiography Images Using Contourlet Transform
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
11/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
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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Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
SUBSAMP &
BLUR
SUBSAMP &
BLUR
SUBSAMP &
BLUR
3 Level LPD
13/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
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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Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
Frequency partitioning when l = 3
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Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
The Contourlet filter bank
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Noise Reduction In Echocardiography Images Using Contourlet Transform
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
Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
Echocardiogram images
18/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
Courtesy: Mr.Kjetil LenesDept. of ECE, MBCET
Echocardiogram images (cont…)
19/25Courtesy: Mr. Kjetil LenesCourtesy: Mr.Kjetil LenesDept. of ECE, MBCET
Analytical Results Anaytical results
Criteria used Mean Square Error (MSE)
Peak Signal-to- noise Ratio (PSNR)
20/25
2
1
1( )
N
i ii
MSE p qMN
2 120log
n
PSNRMSE
Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
Analytical Results (cont..)
Signal to MSE
Contrast Speckle Ratio (CSR)
21/25
101
2
1
2
10log( )
N
iN
i ii
piSMSE
p q
2 2
|
|CSR
Noise Reduction In Echocardiography Images Using Contourlet Transform
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
22/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
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.
23/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
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.
24/25
Noise Reduction In Echocardiography Images Using Contourlet Transform
Dept. of ECE, MBCET
THANK YOU
25/25Dept. of ECE,
MBCET
Noise Reduction In Echocardiography Images Using Contourlet Transform